Difference between revisions of "IS484 IS Project Experience (FinTech)"

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=== Course Description: ===
 
=== Course Description: ===
'''IS484 is cancelled for AY2021/22 Term 2. Will resume in AY2022/23 Term 1.''' <br>
 
'''Please seek sponsors and plan for IS483 for AY2021/22 Term 2.''' <br>
 
 
 
* This is an SMU-X course designed in collaboration with participating Banks, FinTechs, and other FIs, to serve as project sponsors.  Collectively, industry sponsors will supply a minimum of 5 projects ideas to select from.   
 
* This is an SMU-X course designed in collaboration with participating Banks, FinTechs, and other FIs, to serve as project sponsors.  Collectively, industry sponsors will supply a minimum of 5 projects ideas to select from.   
 
* Students will form teams of 5 or 6, and select one the project ideas to work on.  Project selections do not need to be unique, meaning multiple teams can select the same project idea.
 
* Students will form teams of 5 or 6, and select one the project ideas to work on.  Project selections do not need to be unique, meaning multiple teams can select the same project idea.
Line 10: Line 7:
 
* Sponsors will specify the technologies to be used, including; development tools/languages, OS, database, 3rd party libraries, target deployment environment e.g. cloud environment.
 
* Sponsors will specify the technologies to be used, including; development tools/languages, OS, database, 3rd party libraries, target deployment environment e.g. cloud environment.
 
* Student project teams will be expected to develop a working software application prototype, to be delivered to the sponsor at the end of the course.
 
* Student project teams will be expected to develop a working software application prototype, to be delivered to the sponsor at the end of the course.
 +
 +
=== Course Prerequisites: ===
 +
1. Software Project Management (IS212) is a pre-requisite or a co-requisite. <br>
 +
2. Any two (2) track courses '''from the track that you are declaring''' for your project. One of these courses can be a co-requisite.
  
 
=== Project Timeline: ===
 
=== Project Timeline: ===
Line 17: Line 18:
 
! Activities || Timeline || Term 1/ Term 2 || Action By
 
! Activities || Timeline || Term 1/ Term 2 || Action By
 
|-
 
|-
! Project Sourcing and Registration || Week -14 to Week -10 || Form teams. Review the below set of predefined projects provided by Citibank, OCBC or NETS. Fill up the Project Team Signup Sheet at the below link, listing your preferred projects. FT Track Coordinator will finalize the matching of teams to projects. || Students
+
! Project Sourcing and Registration || Week -14 to Week -10 || Form teams. Review the below set of predefined projects provided by Citibank, OCBC, NETS, UBS, and others. Fill up the Project Team Signup Sheet at the below link, listing your preferred projects. FT Track Coordinator will finalize the matching of teams to projects. || Students
 
|-
 
|-
 
! Project Matching || Week -10 || FT Track Coordinator will finalize the matching of teams to projects. || FT Track Coordinator
 
! Project Matching || Week -10 || FT Track Coordinator will finalize the matching of teams to projects. || FT Track Coordinator
Line 31: Line 32:
 
! Finals || Week 14 to Week 16 || Presentation ||Students, Supervisor, Reviewer (Optional: Sponsor, Track Coordinator)
 
! Finals || Week 14 to Week 16 || Presentation ||Students, Supervisor, Reviewer (Optional: Sponsor, Track Coordinator)
 
|}
 
|}
 
=== IS484 Project Wiki: ===
 
Project teams to maintain their documentation here: <br>
 
[[IS484 Project Wiki Home Page]]
 
  
 
=== Project Team Signup Sheet: ===
 
=== Project Team Signup Sheet: ===
AY2020/21 Term 1 <br>
 
https://docs.google.com/spreadsheets/d/1IDAhC4JiK3RuKnIDQMG5UjJ6I1IiImo81Lu13wAuUxE/edit?usp=sharing <br>
 
AY2020/21 Term 2 - CANCELED <br>
 
https://docs.google.com/spreadsheets/d/1IDAhC4JiK3RuKnIDQMG5UjJ6I1IiImo81Lu13wAuUxE/edit#gid=1043528005 - CANCELED <br>
 
AY2021/22 Term 1 <br>
 
https://docs.google.com/spreadsheets/d/1IDAhC4JiK3RuKnIDQMG5UjJ6I1IiImo81Lu13wAuUxE/edit#gid=86226209 <br>
 
AY2021/22 Term 2 - CANCELED <br>
 
AY2022/23 Term 1 <br>
 
https://docs.google.com/spreadsheets/d/1IDAhC4JiK3RuKnIDQMG5UjJ6I1IiImo81Lu13wAuUxE/edit#gid=155160571 <br>
 
 
=== Current Projects ===
 
  
{| class="wikitable centered" width="95%"
+
AY2024/25 Term 2 <br>
!Item
+
https://docs.google.com/spreadsheets/d/1q-2qNkXGcjPxybU52s-1cazP5k4zhHTYRn7SKxz5Hjg/edit?gid=0#gid=0 <br>
!Project Sponsor
 
!Project Description
 
!Project Deliverables
 
!Project Stakeholders
 
|-
 
|width="2%"|<!-- Item--> 1
 
|width="10%"|<!-- Sponsor--> NETS
 
|width="30%"|<!-- Project Description --> '''Transform Internet Online Direct Debit via Web3.0''' - Web 3.0 blockchain identity which offers privacy, control, openness and interoperability is a powerful catalyst to transform the usability and technology for Internet Online Direct Debit. The Web3.0 blockchain identity is a viable secure substitute for the end-user’s internet banking ID credentials and will also streamline the user experience for Internet Online Direct Debit from a Web2 to a Web3 experience. Students will be tasked to build a prototype which contains the following:
 
* A prototype bank app to simulate the registration of a Web3.0 id (blockchain id) thru the existing banking credentials and to be the mobile app to enable a Web3.0 login and notification for internet direct debit payments.
 
* A blockchain host to support the Web3.0 login and payment processing functionality which may include a blockchain smart contract to bridge Web3.0 and legacy payment processing of the banking institutions. 
 
* A banking payment simulator host to register and demonstrate successful payment processing and reference to Web3.0 audit trail.
 
|width="30%"|<!-- Project Deliverables --> Students are expected to deliver a prototype which can accomplish the following:
 
* Demonstrate the registration of a Web3.0 id (blockchain id) thru the existing banking credentials via a prototype banking app.
 
* Demonstrate Web3.0 login and notification for internet direct debit payments.
 
* Demonstrate capability on use of blockchain host to substitute and support the online internet direct debit payment processing functionality which may include a blockchain smart contract to bridge Web3.0 and legacy payment processing of the banking institutions.
 
* A banking payment simulator host to register and demonstrate successful payment processing and reference to Web3.0 audit trail.
 
Project sponsors will share sufficient context so students can understand the context of internet online direct debit to enable the students to design suitable solutions to overcome the problem statement. A sample high level conceptual design, explanation of this roles and responsibilities of the components and other useful details will be available.
 
|width="20%"|<!-- Project Stakeholders -->
 
Project Coordinator: David Woo Chee Keong <br>
 
DavidWoo@nets.com.sg <br> <br>
 
Project Mentor: TBD <br>
 
email TBD
 
|-
 
|width="2%"|<!-- Item--> 2
 
|width="10%"|<!-- Sponsor--> NETS
 
|width="30%"|<!-- Project Description --> '''Interoperable QR payments using EMVCo QR''' - EMVCo QR implementations currently requires consumers to download and deposit funds in multiple payment apps in order to pay to the whole spectrum of EMVCo QR merchants as opposed to only needing to use their favorite payment app. EMVCo QR merchants need to sign-up, settle and reconcile with multiple payment providers as opposed to a single party. EMVCo QR labels currently need to be replaced physically when a merchant decides to ADD or REMOVE QR payment options. Students are asked to create an interoperable payment solution using EMVCo QR which can accomplish the following:
 
* Allow users to use their favorite payment apps to pay to all EMVCo QR merchants as opposed to users having to download multiple payment apps in order to pay to  merchants accepting different payment apps.
 
* Allow merchants to accept payment from all payment apps and receive settlement including consolidated reporting from only one acquirer versus settlement with multiple acquirers each representing different payment app providers.
 
* Allowing a unified and streamlined QR payload which is merchant centric and do not need replacement if the merchant decide to switch acquiring relationships.
 
* Develop an eco-system prototype comprising mockup payment apps, merchants, EMVCo QR labels, EMVCo QR switch (if applicable) and sample transaction and settlement reporting dashboards.
 
|width="30%"|<!-- Project Deliverables --> Students are expected to deliver a prototype which can accomplish the following:
 
* Working eco-system prototype comprising mock\up payment apps, merchants, EMVCo QR labels, EMVCo QR switch (if applicable) and sample transaction and settlement reporting dashboards received by both consumers, merchants and the scheme.
 
* The prototype should be able to highlight and demonstrate key concepts which are key to enabling such an interoperable QR payment scheme.
 
Project sponsors will share sufficient context so students can understand EMVCo QR and the QR payment landscape to enable the students to design suitable solutions to overcome the problem statements.
 
A sample high level conceptual design, explanation of this roles and responsibilities of the components and other useful details will be available.
 
|width="20%"|<!-- Project Stakeholders -->
 
Project Coordinator: David Woo Chee Keong <br>
 
DavidWoo@nets.com.sg <br> <br>
 
Project Mentor: TBD <br>
 
email TBD
 
|-
 
|}
 
  
=== Archived Projects (no longer available) ===
+
=== Current Projects - FY2024/25 Term 2 ===
{| class="wikitable centered" width="95%"
 
!Item
 
!Project Sponsor
 
!Project Description
 
!Project Deliverables
 
!Project Stakeholders
 
|-
 
|width="2%"|<!-- Item--> X
 
|width="10%"|<!-- Sponsor--> Citibank
 
|width="30%"|<!-- Project Description --> '''Derivative & Structured Product Performance Dashboard''' - Derivative & Structured products are complex and its crucial for Bankers and investment counselors to have a consistent view for how these products perform for our clients. Apart from product performance it’s important to know product lifecycle events and any risks that may be detrimental to private bank clients. This dashboard will allow visualization of such complex information in an organized and intuitive manner.
 
Bankers and Investment counselors (ICs) act on market trends and guidance from research teams to create customized financial products for clients. These products are created to cater to a variety financial risks and client preferences.
 
|width="30%"|<!-- Project Deliverables --> The ask is to create an analytics dashboard that:
 
* Allows users to view cumulative financial performance of the products.
 
* Surface product performance details, including possible risks from changes in the market conditions etc.
 
* Filter and show a summary of upcoming product milestone details – such as interest payments, premiums due etc. Allow this data to be sorted and filtered to show details for one or more clients.
 
* Visualize this data using charts, tables etc. in a simple, uncluttered fashion.
 
|width="20%"|<!-- Project Stakeholders -->
 
Project Coordinator: Kulkarni, Kaushik <br> 
 
kaushik.achala.kulkarni@citi.com <br> <br>
 
Project Mentor: Awan, Kashif
 
|-
 
|width="2%"|<!-- Item--> X
 
|width="10%"|<!-- Sponsor--> Citibank
 
|width="30%"|<!-- Project Description --> '''Preventive Cross-Platform Risk Assessment''' - Multiple applications are constructed together to support one of the largest Custodian banking platforms. Any of the components malfunctioning will affect productivity and also lead to a breach of the market deadline. We are seeking for an AI risk monitoring and assessment tool to enhance the platform resilience to another level.
 
AI machine learning Platform to provide risk assessment of cross application health status and prediction of downtime.
 
To do this, they need real time access of:
 
* Application through-put performance.
 
* End-to-end application cross-platform health assessment.
 
* Daily average volume vs. real time system load.
 
|width="30%"|<!-- Project Deliverables --> Students will be tasked to build a UI which:
 
* Contains a dashboard that provides a real time view of platform health status.
 
* Leverages machine learning / deep learning algorithms which suggests and predicts potential system downtime, potential SLA breaches, and identifies trigger points / bottle necks.
 
* Is able to construct end-to-end flows across different platforms.
 
|width="20%"|<!-- Project Stakeholders -->
 
Project Coordinator: Ho, Ricky <br> 
 
ricky.ho@citi.com <br> <br>
 
Project Mentor: Balusa, Ashok
 
|-
 
|width="2%"|<!-- Item--> X
 
|width="10%"|<!-- Sponsor--> Citibank
 
|width="30%"|<!-- Project Description --> (Old name: Document Scrutiny using a Rules Engine)
 
'''Document processing using Cognitive OCR''' - Currently the Document Scrutiny process is a manual task which requires human intervention for regulatory validations. This process is error prone and time consuming.
 
A Rules Engine is need with these features:
 
* Perform Data Validations & Scrutiny for the received Transactions & Documents.
 
* Rules can be configured through UI & saved to the application at any point of time.
 
* A rich UI experience is needed for user friendly & easy rules configuration.
 
|width="30%"|<!-- Project Deliverables --> A solution or program which can accomplish the following:
 
* Download the Documents from Regulators portal for 5-6 countries for Consumer & Corporate banking platform.
 
* Decipher the Rules & Configure the Rules inside the Rule Engine.
 
* Receive the Transactions & the relevant supporting documents. Optical Character Recognition (OCR) & Named Entity Recognition (NER) will be performed by the system.
 
* Perform the Rule validations in an automated way for Transactions & Documents data extracted via the OCR Engine (Currently done manually).
 
|width="20%"|<!-- Project Stakeholders -->
 
Project Coordinator: Gupta, Arvind <br> 
 
shweta4.gupta@citi.com <br> <br>
 
Project Mentor: Mohammad, Thanveer
 
|-
 
|width="2%"|<!-- Item--> X
 
|width="10%"|<!-- Sponsor--> Citibank
 
|width="30%"|<!-- Project Description --> '''Predictive Analysis of Risk Utilization - Phase II''' - Predictive Analysis of Risk Utilization enables Citi's clients and client facing officials to prevent regulatory violations, navigate trading disruptions by proactively take measures to prevent such breaches by allocating funds or by changing their trading strategy.
 
* Citi's institutional clients place millions of orders on any given trading day through its electronic execution platforms.
 
* As orders come in through Citi's systems, they are evaluated against several risk parameters (such as credit limits - Max Daily Notional, Daily Notional, Short Notional, etc) before the order is sent to the market.
 
* This project requires students to build capabilities to the system to predict and alert the clients of potential breach events both in isolation and combination of individual risk parameters.
 
|width="30%"|<!-- Project Deliverables --> Students executing this project will be expected to arrive at comparative machine learning solutions (Random Forest, LTSM and SVM) to predict imminent movement of the risk parameters based on historical trading patterns. <br>
 
Tasks include: <br>
 
*Building adapters to funnel data to a central data pool to run analytics on the data.
 
*Analyzing and find inflection data points and patterns.
 
* Building a user interface/ data conduit that can be used by Citi clients/ users to be notified of any breaches if found.
 
|width="20%"|<!-- Project Stakeholders -->
 
Project Coordinator: Dossii, Shailej P <br> 
 
shailej.p.dossii@citi.com <br> <br>
 
Project Mentor: Kumar, Sudeep
 
|-
 
|width="2%"|<!-- Item--> X
 
|width="10%"|<!-- Sponsor--> Citibank
 
|width="30%"|<!-- Project Description --> '''Equities Pre-Trade Booking Reconciliation''' - Equities Pre-Trade Booking is a manual task at present involving exchange dropcopy feeds, Citi’s internal trade feed for each client. The objective is to develop a tool where clients can review and confirm trades for a given product and market irrespective of execution brokers using exchange dropcopy and broker level reconciliation using blockchain which can be shared across brokers.
 
|width="30%"|<!-- Project Deliverables --> Equities Pre-Trade Booking Reconciliation using Blockchain Ethereum 2.0
 
* Students to analyze the limitations and advantages of using Blockchain Ethereum 2.0 platform for financial data reconciliation.
 
* Develop UI to demonstrate the contents of 2 trade feeds at each block mutation.
 
* Give the final output at EOD in a file format with trade reconciliation exceptions.
 
|width="20%"|<!-- Project Stakeholders -->
 
Project Coordinator: Dossii, Shailej P <br>
 
shailej.p.dossii@citi.com <br> <br>
 
Project Mentor: Kumar, Sudeep
 
|-
 
|width="2%"|<!-- Item--> X
 
|width="10%"|<!-- Sponsor--> Citibank
 
|width="30%"|<!-- Project Description --> '''Machine Learning Model Performance''' - Machine learning models are being trained based on historical data. But in the commercial world, change is expected rapidly which may mark the model biased to the new data as well as scaled old data. Before the model is retained, there are immediate needs to understand what are the leverages that can be applied to interfere with the old model output to achieve the accuracy rate, then capture the business opportunity in a very short turnaround time. When models are unable to digest new data, they will generate inaccurate recommendations and predictions to the business, resulting in missing the opportunities for increased revenue.
 
|width="30%"|<!-- Project Deliverables --> A solution or program which can accomplish the following: <br>
 
* Detect the root cause of low accuracy with a given model input, model output and model binary.
 
* Generate corrective recommendations to increase accuracy without re-building the model.
 
* Perform regression testing with recommendations, to demonstrate the expected accuracy.
 
* The program is expected to be able to analyse any supervisory learning model for the given input and output.
 
|width="20%"|<!-- Project Stakeholders -->
 
Yuqian Song, Head of APAC/EMEA Data Services and Head of Global Advanced Analytics Technology Solutions <br>
 
yuqian.song@citi.com
 
|-
 
|width="2%"|<!-- Item--> X
 
|width="10%"|<!-- Sponsor--> Citibank
 
|width="30%"|<!-- Project Description --> '''Robo-Advisor''' - Student defined project. A robo-advisor that will; classify customers based on their investment experience and risk appetite, recommend a portfolio of investments to customers, provide visualizations / analysis of the customer's investment portfolio, and provide a budgeting and savings dashboard as an extension or the above.
 
|width="30%"|<!-- Project Deliverables --> A solution or program which can accomplish the following: <br>
 
* Customer Classification (via chat)
 
* Portfolio Selection (recommendation to customer)
 
* Visualization (portfolio analysis)
 
* Personal Finance Dashboard (extension on top of the above)
 
|width="20%"|<!-- Project Stakeholders -->
 
Ravinder Rao, Senior Vice President, GCT Data & Analytics <br>
 
ravinder.rao@citi.com
 
|-
 
|width="2%"|<!-- Item--> X
 
|width="10%"|<!-- Sponsor--> Citibank
 
|width="30%"|<!-- Project Description --> '''Private Banking Client Dashboard''' - Citi Private Bank (CPB) Investment Counsellors and Advisors provide frequent consultation to HNWI and UHWNI (high and ultra-high net-worth individuals) on how to manage their Investment portfolios. In order to perform their job they need high speed access to a client's positions, real-time market data and publicly available sentiment on the portfolio's constituents. The portfolio is usually composed of capital market securities and various funds (hedge, mutual, real estate, private equity). Careful thought needs to be put into providing an enriching UX / UI and leveraging machine / deep learning capability to provide robust recommendations. The users will use the information to pro-actively and also reactively service CPB's HNWI and UHNWI clients.
 
|width="30%"|<!-- Project Deliverables --> A working dashboard that provides a real-time view of a client's position. The view should be contextual based on the type of holdings (Cash/Liabilities, Equity, Fixed Income, Derivatives and Alternative Investments). The view would give an instrument and profitability analysis based on market data (Bloomberg / Reuters). Furthermore, there will be a recommendation engine that looks at a client's current / past positions and suggests trade-able ideas to the advisor based on upcoming announcements, trending public sentiment and client's personal interests.
 
|width="20%"|<!-- Project Stakeholders -->
 
Kashif Awan, Private Bank Capital Markets APAC Technology Head
 
kashif.awan@citi.com
 
|-
 
|width="2%"|<!-- Item--> X
 
|width="10%"|<!-- Sponsor--> Citibank
 
|width="30%"|<!-- Project Description --> '''Predictive Analysis of Risk Utilization''' - Citi's institutional clients place millions of orders on any given trading day through its electronic execution platforms. As orders come in through Citi's systems, they are evaluated against several risk parameters(such as credit limits) before the order is sent to the market. While currently, breaches in these parameters can be identified the moment the orders are placed, the next gen evolution of this risk management system requires predictive analytics of such breach events. This will enable Citi's clients and client facing officials to prevent regulatory violations, navigate trading disruptions by proactively take measures to prevent such breaches by allocating funds/ changing their trading strategy etc.
 
|width="30%"|<!-- Project Deliverables --> Students executing this project will be expected arrive at a machine learning solution to predict imminent movement of the risk parameters based on historical trading patterns. The solution should be able to take data feed for supplemental information (Triple witching dates, FTSE/MSCI rebalancing, other events that affect the market such as the Coronavirus threat) to more accurately predict exceptional scenarios. <br>
 
'''Tasks:'''
 
* Understand Citi's current data model for storing historical data. <br>
 
* Build adapters to funnel data to a central data pool to run analytics on the data. <br>
 
* Analyze and find inflection data points and patterns. <br>
 
* Build supplemental data feed to establish market sentiments in the sytem and use that to augment their prediction models. <br>
 
* Build a user interface/ data conduit that can be used by Citi clients/ users to be notified of any breaches if found.
 
|width="20%"|<!-- Project Stakeholders -->
 
Sudeep Kumar, Global Exchange Connectivity & Asia Cash Equities Technology Lead <br>
 
sudeep1.kumar@citi.com
 
|-
 
|width="2%"|<!-- Item--> X
 
|width="10%"|<!-- Sponsor--> Citibank
 
|width="30%"|<!-- Project Description --> '''Customer Mailing Address Analysis''' - Addresses of people and businesses contain important information about them. More data about the locations of those addresses is required to get some insight from addresses. For example the population, geographic and economic indicators, crime rates etc. can be helpful. We need to collect such information about countries and cities to make the addresses usable in models and other analytics.
 
|width="30%"|<!-- Project Deliverables --> A solution or program which can accomplish the following: <br>
 
* Collect information about countries from IMF data. <br>
 
* Collect information about cities from DBPedia data. <br>
 
* Build schedules to keep the above data fresh, as new data is available. <br>
 
* Make this data available to lookup by country and Citi names to be used by models and analytics queries. <br>
 
* Generate an embedding of countries and an embedding of cities, to be used as features in models. <br>
 
* Unstructured addresses (where country, city are not marked separately, but part of large address text) need to be parsed before lookup. <br>
 
* Make this information available by joining the addresses of people and businesses and collected data by countries and cities as join keys. <br>
 
* Measure how much the model performance improves, after using this additional information.
 
|width="20%"|<!-- Project Stakeholders -->
 
Yuqian Song, Head of APAC/EMEA Data Services and Head of Global Advanced Analytics Technology Solutions <br>
 
yuqian.song@citi.com
 
|-
 
|width="2%"|<!-- Item--> X
 
|width="10%"|<!-- Sponsor--> Citibank
 
|width="30%"|<!-- Project Description --> '''Marketing Audience Segmentation''' - Citibank sends merchants’ offers to the relevant customers. For example customers who often buy sports gear should get sports related offers and foodies should get offers from the restaurants. This requires accurate segmentation of customers as well as merchants. 3rd party data can be used to improve marketing audience segmentation.
 
|width="30%"|<!-- Project Deliverables --> A solution or program which can accomplish the following: <br>
 
* Acquire 3rd party e.g. Statista, Euromonitor and map the brand mentions in the transactions, with brand master list in acquired data. <br>
 
* Use brand category-hierarchy to segment the customers for their buying habits, using customer transaction history. <br>
 
* Use brand category-hierarchy to segment merchants by categories of products and services sold and offers made. <br>
 
* Use the category based segments for a broader match between customers and merchants.
 
|width="20%"|<!-- Project Stakeholders -->
 
Yuqian Song, Head of APAC/EMEA Data Services and Head of Global Advanced Analytics Technology Solutions <br>
 
yuqian.song@citi.com
 
|-
 
|width="2%"|<!-- Item--> X
 
|width="10%"|<!-- Sponsor--> OCBC
 
|width="30%"|<!-- Project Description --> '''Online Business Account Maintenance''' - Business Banking provides SME & Corporate customers with a broad range of Cash & Trade products and services. Through our Digital Business Banking channels, customers are able to manage cash, loans, trade finance and perform transactions in their day-to-day business. The current account maintenance form is in PDF for customers to download. Once customer fills up the form, they will email the scan copy to operations. This process takes at least a few days to complete and incurs operation overhead. The task is to digitize the online business account maintenance services:
 
* To analyze the account maintenance form in PDF
 
* Develop UI & microservices to render the form based on configuration & capture the data digitally
 
* Allow customer to authorize the submission digitally with online signature or via SingPass
 
|width="30%"|<!-- Project Deliverables -->
 
* UI & microservices as a dynamic online account maintenance application.
 
* UI is preferred to be developed in ReactJS & microservices developed in Java Springboot
 
Project sponsors will share sufficient context so students can understand how/where this UI brings value to the customers.
 
The sample pdf form, explanation of the validations and other useful details will be shared.
 
|width="20%"|<!-- Project Stakeholders -->
 
Project Coordinator: Lim Dedy Daryono <br>
 
limdd@ocbc.com <br> <br>
 
Project Mentor: Kotla Mutha Ravi Tej <br>
 
RaviTejKotla@ocbc.com
 
|-
 
|width="2%"|<!-- Item--> X
 
|width="10%"|<!-- Sponsor--> OCBC
 
|width="30%"|<!-- Project Description --> '''Host-to-Host (H2H) Modernization''' - Business Banking provides SME & Corporates customer with a broad range of Cash & Trade products and services. Through our H2H integration, customers are able to integrate with their ERP/Accounting system to perform transactions with the bank. The current H2H solution is a secured file transfer channel which supports file transfers between customers and the bank over the internet. Currently there is excessive overhead in managing folder & access controls, as there are thousands of folders that need to be maintained. In addition, H2H integration is scheduled instead of event based, and this also incurs high maintenance overhead. The task is to modernize the H2H setup & maintenance:
 
* To analyze the H2H setup & challenges
 
* Propose a new design, implementation & tool if any to ease the maintenance with better access control
 
|width="30%"|<!-- Project Deliverables -->
 
* New H2H solutions setup for minimal operation maintenance
 
* Event trigger capabilities (instead of scheduled)
 
* H2H is preferred to be on Linux platform with Java components if any
 
Project sponsors will share sufficient context so students can understand how/where the new H2H integration will benefit the customers.
 
|width="20%"|<!-- Project Stakeholders -->
 
Project Coordinator: Lim Dedy Daryono <br>
 
limdd@ocbc.com <br> <br>
 
Project Mentor: Kochupurackal Joseph George <br>
 
JosephK@ocbc.com
 
|-
 
|width="2%"|<!-- Item--> X
 
|width="10%"|<!-- Sponsor--> OCBC
 
|width="30%"|<!-- Project Description --> '''Blockchain Applications''' - GO&T serves as trusted partner to co-create new business capabilities, protect technology infrastructure, manage Group’s IT operations, and run regional processing hubs. Currently there is wide range of documents used by different teams in GO&T, there’s no efficient and automated method for verifying the latest version of documents, retrieval of documents and checking authenticity. This creates operational overhead for staff who rely on getting the approved documents done by other teams. On the NFT digital assets front, due to strong demand on NFT assets, there is no standardized way and repeatable process for production of NFT assets. Business users are not able to iterate fast on digital assets creation to meet demand by customers.  The task is to design and develop blockchain applications for use cases such as:
 
* Document notarization & verification
 
* Production of NFT assets
 
|width="30%"|<!-- Project Deliverables -->
 
* New microservices for API calls to the endpoints of blockchain for document verification.
 
* New microservices for API calls to the endpoints of blockchain for production and management of NFT assets.
 
* New smart contract to store the Hash of the documents on-chain and other meta-data stored off-chain.
 
* New smart contract for NFT assets based on ERC-721 token standard stored on-chain and other NFT meta-data stored off-chain.
 
Project sponsors will share sufficient context so students can understand how and where the blockchain applications can benefit the end users. The sample documents, explanation of the validations and other useful details will be shared.
 
|width="20%"|<!-- Project Stakeholders -->
 
Project Coordinator: Lim Dedy Daryono <br>
 
limdd@ocbc.com <br> <br>
 
Project Mentor: Neo Wei Cheong <br>
 
WeiCheongNeo1@ocbc.com
 
|-
 
|width="2%"|<!-- Item--> X
 
|width="10%"|<!-- Sponsor--> Citibank
 
|width="30%"|<!-- Project Description --> '''Commodities Pricing''' - The Commodities Pricing Platform (Atlas) is a Sales and Trader facing application that provides timely pricing across all Commodities asset classes. The user interface is mainly configuration driven and uses a highly dynamic rule engine to represent relationships between user inputs. These configurations are used as inputs to the rules engine to define products, their defaults and what data transformations should occur based on user inputs. The configuration files the pricing platform uses can span thousands of lines of JSON. Updating this JSON manually represents an operational risk. The aim of this project is to structure the update process and reduce this risk.
 
|width="30%"|<!-- Project Deliverables --> Students will be asked build a UI that will:
 
* Have the ability to create, delete and modify rules engine configurations
 
* Apply validation logic across the configuration to highlight inconsistencies in the rules such as loops, duplicates or conflicts.
 
* The application should provide an intuitive UI/UX, and the ability to create new pricing products without code changes.
 
Project sponsors will share sufficient context so students can understand how/where this application brings value to users.
 
The data will be shared and an explanation of this data structure and other useful details will be available.
 
|width="20%"|<!-- Project Stakeholders -->
 
Project Coordinator: Dossii, Shailej P <br>
 
shailej.p.dossii@citi.com <br> <br>
 
Project Mentor: Ronnie Day <br>
 
email ronnie.day@citi.com
 
|-
 
|width="2%"|<!-- Item--> X
 
|width="10%"|<!-- Sponsor--> Citibank
 
|width="30%"|<!-- Project Description --> '''Preventive Cross-Platform Risk Assessment (II)''' - An AI machine learning platform is needed to provide risk assessments of cross application health status and predictions of downtime, based on realtime access to applications through-put performance data, in order to provide an end-to-end cross platform health assessment including daily average volume vs realtime system load. Students are tasked to build a UI with a dashboard that provides a realtime view of platform health status, leveraging machine learning/ deep learning algorithms to suggest and predict potential system downtime, potential SLA breaches, and identify trigger points /bottle necks.
 
|width="30%"|<!-- Project Deliverables --> Students will be tasked to build a UI that will provide:
 
* Working dashboard with realtime view of platform health status.
 
* View of contextual assessment of platform status.
 
* View of trigger notifications when risk crosses threshold.
 
* View of collected historical information.
 
* Perform system end-to-end calculated risk assessment.
 
* Ability to collect data from different applications in realtime. 
 
|width="20%"|<!-- Project Stakeholders -->
 
Project Coordinator: Dossii, Shailej P <br>
 
shailej.p.dossii@citi.com <br> <br>
 
Project Mentor: Ricky Ho <br>
 
email ricky.ho@citi.com
 
|-
 
|width="2%"|<!-- Item--> X
 
|width="10%"|<!-- Sponsor--> Citibank
 
|width="30%"|<!-- Project Description --> '''Equities Chatbot''' - Citi Equities trading platform receives several queries on a daily basis. The queries currently are being sent and answered through email, symphony chat, Bloomberg chat etc. and an associate’s manual efforts are required to generate a response; either running database queries to fetch results, or leveraging their product knowledge and judgement to make predictions. This project is to create an AI chatbot to automate the process and replicate the efforts of an associate replying to queries received by the Equities team. The AI chatbot is expected to interact with traders and answer their queries. The bot must be capable of:
 
* Running 24/7 to tend to all queries
 
* Generating cohesive and accurate responses to queries in real time
 
* Processing financial jargon and acronyms as input
 
* Running database queries and displaying results
 
* Making trading algorithm predictions for products selected by trader
 
* Logging all activity to be used for analysis of performance
 
|width="30%"|<!-- Project Deliverables --> Students will be tasked to build the following:
 
* Functional chatbot with clean UI and robust backend
 
* Chatbot must use NLP tasks such as Word sense Disambiguation, Named Entity Recognition (NEM) and Sentiment Analysis to ensure nuanced interactions
 
* Must mine text from existing datasets to enrich the bot
 
* Must employ decision making models to make trading algorithm predictions
 
Project Inputs:
 
* Historic queries and responses
 
* Financial acronyms compilation
 
* Product to algorithm mapping
 
* Any FAQs
 
|width="20%"|<!-- Project Stakeholders -->
 
Project Coordinator: Dossii, Shailej P <br>
 
shailej.p.dossii@citi.com <br> <br>
 
Project Mentor: Rajeshkumar Madanlal <br>
 
email rs97865@citi.com
 
|-
 
|width="2%"|<!-- Item--> X
 
|width="10%"|<!-- Sponsor--> Citibank
 
|width="30%"|<!-- Project Description --> '''Data Aggregator''' - Reporting and Statements generation across various countries within Citi is a critical operation for client and service operations within Citi. There is a high level of data redundancy (multiple copies of the same data), manual dependency from operations users to input data, and untimely data availability. In some cases, this becomes a regulatory concern. Students executing this project will be expected to build a middleware application that is capable of extracting data points on demand from various source or upstream systems. The objective is to build a Report On Demand (ROD) framework that can serve as a self-service fully autonomous tool for operations users, to enable:
 
* Flexibility and enable users to retrieve data on-demand
 
* Centralized data aggregation management
 
* Cost-effective and timely response to ever-changing data requirements
 
|width="30%"|<!-- Project Deliverables --> Features of this solution to include:
 
* Ability to upload data a dictionary in a defined format – this format can be specified by the students,
 
* Ability to create data extraction templates from the available data points in the data dictionary.
 
* Once templates are created, they can be run on-demand to extract and store these data points from source systems.
 
Note: The data sources typically are Oracle, MSSQL and No-SQL databases. This can be further extended to File store, HDFS etc.
 
  
Project sponsor will share further context on the various pain points and priorities of the problem statement. Specific use will be defined and shared with the students too.
+
<table width="966" cellpadding="2" cellspacing="0" bgcolor="#f2f2f2" style="background: #f2f2f2; page-break-before: always">
|width="20%"|<!-- Project Stakeholders -->  
+
<tr>
Project Coordinator: Dossii, Shailej P <br>
+
<td width="73" style="border: 1.00pt solid #000000; padding: 0.02in 0.08in"><p class="msonormal" align="center">
shailej.p.dossii@citi.com <br> <br>
+
<b>ID, Term, and BA Status</b></p>
Project Mentor: Sandeep Sharma <br>
+
</td>
email rajeshkumar.madanlal.sharma@citi.com
+
<td width="78" style="border-top: 1.00pt solid #000000; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0.02in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" align="center">
|-
+
<b>Sponsor / Business Vertical</b></p>
|width="2%"|<!-- Item--> X
+
</td>
|width="10%"|<!-- Sponsor--> Citibank
+
<td width="322" style="border-top: 1.00pt solid #000000; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0.02in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" align="center">
|width="30%"|<!-- Project Description --> '''Enabling Efficient On-the-job Training with AI''' - Citi Commercial Bank (CCB) plans to hire hundreds of staff over the next three years to fast-track growth. It is crucial that new hires joining CCB are brought up to speed efficiently on company and role-specific processes and day-to-day functions. A large part of this is done through on-the-job training, where new hires learn more about the various processes, digital platforms and resources as they do their daily work. However, given the complex nature of the business (and hence its processes and systems), it is not always easy for new hires to learn on-the-job. The ask is to create on-the-job training resource(s) and platform for employees where Line Managers / L&D partners can easily:
+
<b>Project Description</b></p>
* Build learning pathways for their teams on the various digital processes and systems that they would have to get familiar with as part of their on-the-job training.
+
</td>
* Upload / maintain use-case driven content for the learning pathways.
+
<td width="320" style="border-top: 1.00pt solid #000000; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0.02in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" align="center">
* Reduce manual on-the-job trainings for new hires.
+
<b>Project Scope</b></p>
|width="30%"|<!-- Project Deliverables --> Students are expected to deliver:
+
</td>
* A working prototype to collate and prioritizes training resource(s) that enables efficient and effective on-the-job learning. The solution should be easy and intuitive to use for both managers and new hires.
+
<td width="151" style="border-top: 1.00pt solid #000000; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0.02in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" align="center">
* The working prototype would demonstrate the use of natural language processing/AI and full stack development skills to build a platform that can deliver summarized and relevant information when users make specific on-the-job queries.
+
<b>Project Stakeholders</b></p>
* The solution must be able to measure the success of on-the-job learning.
+
</td>
* New hires should easily be able to navigate the learning pathways such that they can self-serve and learn on their own and Search for answers to specific on-the-job queries they have on processes / systems.
+
</tr>
 +
<tr valign="top">
 +
<td width="73" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: 1.00pt solid #000000; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0.08in; padding-right: 0.08in"><p class="msonormal" align="center" style="margin-bottom: 0.2in">
 +
Project #1</p>
 +
<p class="msonormal" align="center" style="margin-bottom: 0.2in">FY2024/25
 +
<br/>
 +
Term 2</p>
 +
<p class="msonormal" align="center">Fulfills BA</p>
 +
</td>
 +
<td width="78" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal">
 +
OCBC - Consumer Banking</p>
 +
</td>
 +
<td width="322" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" style="margin-bottom: 0.2in">
 +
<font color="#000000"><b>Fast Data Acquisition for Real-time
 +
Analytics</b></font><font color="#000000"><br/>
 +
Core Banking
 +
processes a high volume of customer transactions including
 +
transfers, deposits and payments in an RDBMS (say PostgreSQL).
 +
There is a need to analyze the data real-time to detect any
 +
anomalies and generate operational reports. The application
 +
transaction database in optimized for high-availability and write
 +
performance, not analytics.<br/>
 +
<br/>
 +
Therefore, there is a need
 +
for a real-time ingestion framework to stream transaction data
 +
from the source to the target operational data store (ODS), for
 +
real-time analytics.<br/>
 +
<br/>
 +
Traditional batch ETL processes
 +
result in delayed data availability, leading to slower
 +
decision-making. Real-time analytics improves the customer
 +
service, reduce fraud risk etc.</font></p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">The key
 +
challenges that should be address are</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in"><font color="#000000"><b>Low
 +
latency: </b></font><font color="#000000">Data needs to be
 +
streamed in near real-time without impacting the performance of
 +
the source transaction system.</font></p>
 +
<p class="msonormal" style="margin-bottom: 0.2in"><font color="#000000"><b>Data
 +
consistency:</b></font><font color="#000000"> The data arriving at
 +
the ODS remains consistent with the source system, especially
 +
during high transaction volumes.</font></p>
 +
<p class="msonormal" style="margin-bottom: 0.2in"><font color="#000000"><b>Scalability:</b></font><font color="#000000">
 +
The ingestion framework must scale to handle increasing
 +
transaction volumes during peak hours, like flash sales or
 +
promotions etc.</font></p>
 +
<p class="msonormal"><font color="#000000"><b>High Availability:
 +
</b></font><font color="#000000">The framework should tolerate
 +
failures and be resilient with high-availability.&nbsp; </font>
 +
</p>
 +
</td>
 +
<td width="320" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" style="margin-bottom: 0.2in">
 +
Project Inputs:<br/>
 +
Project sponsors will share sufficient
 +
context so students can understand how/where this model brings
 +
value to users.<br/>
 +
<br/>
 +
Project Deliverables:
 +
</p>
 +
<p class="msonormal" style="margin-left: 0.24in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; A low latency real-time
 +
ingestion framework using CDC and should support CRUD operations
 +
to be consistent with the source database.</p>
 +
<p class="msonormal" style="margin-left: 0.24in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Analytics dashboard that
 +
provides insights as</p>
 +
<p class="msonormal" style="margin-left: 0.69in; margin-bottom: 0.2in; background: transparent">
 +
•&nbsp;&nbsp;&nbsp;&nbsp; Customer activity and behaviour</p>
 +
<p class="msonormal" style="margin-left: 0.69in; margin-bottom: 0.2in; background: transparent">
 +
•&nbsp;&nbsp;&nbsp;&nbsp; Pending or failed payments</p>
 +
<p class="msonormal" style="margin-left: 0.69in; margin-bottom: 0.2in; background: transparent">
 +
•&nbsp;&nbsp;&nbsp;&nbsp; Total transaction volume per
 +
minute/hour</p>
 +
<p class="msonormal" style="background: transparent">•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
 +
Documentation with detailed setup instructions for configuring the
 +
ingestion with no-coding and just using configuration changes.</p>
 +
</td>
 +
<td width="151" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal">
 +
Project Coordinator: Lim Wei Ming<br/>
 +
Project Mentor:
 +
Radhakrishna Sarma</p>
 +
</td>
 +
</tr>
 +
<tr valign="top">
 +
<td width="73" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: 1.00pt solid #000000; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0.08in; padding-right: 0.08in"><p class="msonormal" align="center" style="margin-bottom: 0.2in">
 +
Project #2</p>
 +
<p class="msonormal" align="center">FY2024/25 <br/>
 +
Term 2</p>
 +
</td>
 +
<td width="78" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal">
 +
OCBC - Front Office Relationship Managers</p>
 +
</td>
 +
<td width="322" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" style="margin-bottom: 0.2in">
 +
<b>Front Office Dashboard / Client meeting prep support</b></p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">The goal of this
 +
project is to leverage GenAI Technologies to develop a dashboard
 +
and client meeting preparation support system. The system will
 +
gather relevant information such as to-do lists, insights that
 +
clients would appreciate, follow-ups from previous meetings,
 +
outstanding document deficiencies, and areas requiring client
 +
feedback. All of this information will be consolidated into a
 +
meeting preparation pack, making it easier for professionals to
 +
prepare for client meetings efficiently.
 +
</p>
 +
<p class="msonormal">Front office staff often struggle to gather
 +
and organize all the necessary information for client meetings.
 +
This leads to inefficiencies and potential oversights. Therefore,
 +
there is a need for a system that can streamline the process of
 +
gathering, organizing, and presenting important information to
 +
professionals before client meetings.
 +
</p>
 +
</td>
 +
<td width="320" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" style="margin-bottom: 0.2in">
 +
Project Inputs:</p>
 +
<p class="msonormal" style="margin-left: 0.24in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Project sponsors will
 +
share sufficient context so students can understand how/where this
 +
UI brings value to users.</p>
 +
<p class="msonormal" style="margin-left: 0.24in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Components required for
 +
effective client meeting preparation, including to-do lists,
 +
insights, follow-ups, document deficiencies, reviews, and client
 +
feedback.</p>
 +
<p class="msonormal" style="margin-left: 0.24in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Data or resources
 +
necessary for testing, such as sample client meeting data, client
 +
feedbacks, digital channel access data and relevant documents.</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">Project
 +
Deliverables:
 +
</p>
 +
<p class="msonormal" style="margin-left: 0.24in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Dashboard: Create a
 +
user-friendly dashboard that allows Front office to input and
 +
access information for client meeting preparation.</p>
 +
<p class="msonormal" style="margin-left: 0.24in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; AI Integration: Utilize
 +
GenAI Technologies to enhance the system's capabilities, such as
 +
natural language processing for analyzing meeting notes and
 +
predictive analytics for generating insights.</p>
 +
<p class="msonormal" style="margin-left: 0.24in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Data Analysis: Implement
 +
AI models to analyze data inputs and generate valuable insights,
 +
such as identifying patterns in client feedback or predicting
 +
potential document deficiencies.</p>
 +
<p class="msonormal">•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
 +
Meeting Preparation Pack: Consolidate all relevant information,
 +
including to-do lists, insights, follow-ups, document
 +
deficiencies, reviews, and areas requiring client feedback, into a
 +
comprehensive meeting preparation pack.</p>
 +
</td>
 +
<td width="151" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" style="margin-bottom: 0.2in">
 +
Project Coordinator: Bryan Lee Cheng Hui</p>
 +
<p class="msonormal">Project Mentor: Amila Silva</p>
 +
</td>
 +
</tr>
 +
<tr valign="top">
 +
<td width="73" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: 1.00pt solid #000000; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0.08in; padding-right: 0.08in"><p class="msonormal" align="center" style="margin-bottom: 0.2in">
 +
Project #3</p>
 +
<p class="msonormal" align="center">FY2024/25 <br/>
 +
Term 2</p>
 +
</td>
 +
<td width="78" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal">
 +
OCBC - Group Operations &amp; Technology</p>
 +
</td>
 +
<td width="322" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" style="margin-bottom: 0.2in">
 +
This project aims to explore the concept of Zero-Knowledge
 +
Rollups, an innovative technology that addresses two significant
 +
challenges in blockchain transactions: privacy and efficiency. In
 +
simpler terms, Zero-Knowledge Rollups are like a secret code that
 +
allows you to do more things securely and quickly without anyone
 +
else knowing the details.</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">In the world of
 +
digital currencies and blockchain, it's crucial to ensure that
 +
transactions are both private and efficient. Zero-Knowledge
 +
Rollups offer a promising solution by bundling many transactions
 +
together and proving they are valid without revealing specific
 +
details about each individual transaction.
 +
</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">This approach
 +
enables blockchain networks to handle a large number of
 +
transactions at once, making them faster and more scalable. This
 +
also prove that transactions are valid without exposing the
 +
specifics. As a practical demonstration, we are able to develop
 +
blockchain applications such as:</p>
 +
<p class="msonormal" style="margin-left: 0.3in; margin-bottom: 0.2in">
 +
1.&nbsp;&nbsp;&nbsp; Enhancing Privacy and Scalability in
 +
Blockchain Transactions using Zero-Knowledge Rollups</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">There is a need
 +
for an improved solution to address the privacy and scalability
 +
challenges facing blockchain transactions. Traditional blockchain
 +
systems, such as those used in cryptocurrencies, often struggle to
 +
handle a high volume of transactions while simultaneously ensuring
 +
the privacy of participants.</p>
 +
<p class="msonormal">Existing blockchain architectures suffer from
 +
limited scalability, resulting in congestion and increased
 +
transaction delay during peak usage periods. Moreover, transaction
 +
details are often visible to malicious actors, compromising user
 +
privacy and confidentiality.
 +
</p>
 +
</td>
 +
<td width="320" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" style="margin-bottom: 0.2in">
 +
Project Inputs:</p>
 +
<p class="msonormal" style="margin-left: 0.23in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Project sponsors will
 +
share sufficient context so students can understand its use cases,
 +
discussing the benefits and limitations of implementing zero
 +
knowledge rollups and how it can benefit end users.</p>
 +
<p class="msonormal" style="margin-left: 0.23in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; The project details,
 +
explanation of the zero knowledge rollups and other useful details
 +
will be shared.</p>
 +
<p class="msonormal" style="margin-left: 0.02in; margin-bottom: 0.2in">
 +
Project Deliverables:
 +
</p>
 +
<p class="msonormal" style="margin-left: 0.23in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Students will dive into
 +
the technical aspects of Zero-Knowledge proofs, learn about the
 +
challenges of implementing Rollup solutions, and examine
 +
real-world examples where this technology has been used
 +
successfully
 +
</p>
 +
<p class="msonormal" style="margin-left: 0.23in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Investigate where zero
 +
knowledge rollups can be applied in banking environment. Students
 +
will study relevant academic resources, examine existing
 +
Zero-Knowledge Rollup implementations</p>
 +
<p class="msonormal" style="margin-left: 0.23in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Create simulations or
 +
proof-of-concept prototypes to explore the practical aspects</p>
 +
<p class="msonormal">&nbsp;</p>
 +
</td>
 +
<td width="151" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" style="margin-bottom: 0.2in">
 +
Project Coordinator: Ravindra Kumar</p>
 +
<p class="msonormal">Project Mentor: Jorden Seet</p>
 +
</td>
 +
</tr>
 +
<tr valign="top">
 +
<td width="73" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: 1.00pt solid #000000; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0.08in; padding-right: 0.08in"><p class="msonormal" align="center" style="margin-bottom: 0.2in">
 +
Project #4</p>
 +
<p class="msonormal" align="center" style="margin-bottom: 0.2in">FY2024/25
 +
<br/>
 +
Term 2</p>
 +
<p class="msonormal" align="center">Fulfills BA</p>
 +
</td>
 +
<td width="78" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal">
 +
Citi - Exchange Traded &amp; Cleared Derivatives</p>
 +
</td>
 +
<td width="322" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" style="margin-bottom: 0.2in">
 +
<b>Collateral Optimization for CCP Margin Calls</b></p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">Citi provides
 +
its clients with clearing services on several global Central
 +
Counterparty Clearing Houses (CCPs). Clients can post eligible
 +
currency (cash) &amp; financial instruments (bonds, treasury
 +
notes, securities, commodity warrants, etc.) as collateral to
 +
cover margin calls. Citi, as a clearing member, will then utilize
 +
some of these assets to cover the corresponding margin calls with
 +
the CCP.</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">Each CCP has
 +
specific requirements regarding the types of collateral it
 +
accepts, applying different haircuts and collateral fees based on
 +
asset class. Additionally, transaction costs are incurred when
 +
depositing, substituting or withdrawing collateral. Optimizing the
 +
allocation of available collateral across different CCPs can
 +
minimize costs and increase efficiency.</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">This project
 +
aims to develop an algorithm that optimizes the allocation of
 +
available collateral to various CCPs based on eligibility,
 +
collateral costs, haircuts, and transaction costs, taking into
 +
account frequent changes in available collateral due to client
 +
activity.</p>
 +
<p class="msonormal">Citi’s clearing services require optimal
 +
collateral allocation to different CCPs in order to minimize costs
 +
and comply with eligibility requirements. The current process
 +
involves multiple variables such as collateral eligibility,
 +
haircut rates, collateral fees, and transaction costs. The
 +
objective of this project is to build a solution that optimizes
 +
collateral allocation for margin calls at each CCP while
 +
minimizing associated costs and fees.</p>
 +
</td>
 +
<td width="320" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" style="margin-bottom: 0.2in">
 +
Project Inputs:</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">Students will be
 +
provided with:</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">1. A file
 +
containing a list of available collateral.</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">2. A file that
 +
lists the margin calls required at each CCP.</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">3. A file
 +
containing static data regarding eligible</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">associated
 +
haircut rates, fees, and transaction costs at different CCPs.</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">All required
 +
data is in public domain. No Citi proprietary data is required nor
 +
will be shared for this project.
 +
</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">Project
 +
Deliverables:</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">1. Optimization
 +
Algorithm: A solution to optimize the allocation of available
 +
collateral across multiple CCPs based on eligibility, costs, and
 +
transaction considerations.</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">2. User
 +
Interface: A basic user interface to input data and visualize the
 +
optimized collateral allocation across CCPs.</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">3. Collateral
 +
Movement Report: A user report that lists the optimal collateral
 +
allocation and the related asset movements.</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">4.
 +
Documentation: Detailed documentation explaining the methodology,
 +
logic behind the optimization algorithm, and any assumptions made.</p>
 +
<p class="msonormal">5. Presentation: A final presentation
 +
demonstrating the optimization tool, its functionality, and
 +
potential real-world applications for Citi's operations.</p>
 +
</td>
 +
<td width="151" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" style="margin-bottom: 0.2in">
 +
Project Coordinator: TBA</p>
 +
<p class="msonormal">Project Mentor: Nirav Parikh</p>
 +
</td>
 +
</tr>
 +
<tr valign="top">
 +
<td width="73" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: 1.00pt solid #000000; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0.08in; padding-right: 0.08in"><p class="msonormal" align="center" style="margin-bottom: 0.2in">
 +
Project #5</p>
 +
<p class="msonormal" align="center">FY2024/25 <br/>
 +
Term 2</p>
 +
</td>
 +
<td width="78" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal">
 +
Citi - Markets &amp; Trading</p>
 +
</td>
 +
<td width="322" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" style="margin-bottom: 0.2in">
 +
<b>Synthetic Market Generator for Algorithmic Trading</b></p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">One of the key
 +
challenges in training trading algorithms is the limited
 +
availability of real-world historical data specific to certain
 +
securities. This scarcity of data can lead to overfitting and
 +
suboptimal performance in machine learning models. Moreover, it is
 +
difficult to find data that accurately reflects specific market
 +
conditions, including varying volumes, trends, and volatility
 +
levels.</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">This project
 +
aims to address these challenges by developing a synthetic market
 +
simulator capable of generating market data tailored to specific
 +
securities and market conditions. The simulator will be
 +
parameterized to model various patterns, volatility levels, and
 +
market trends, providing a flexible tool for creating synthetic
 +
datasets. These datasets can then be used for training and testing
 +
algorithmic trading strategies, avoiding the pitfalls of limited
 +
real-world data.</p>
 +
<p class="msonormal">Current trading models face the challenge of
 +
limited historical data for specific securities and market
 +
conditions. This project seeks to build a synthetic market data
 +
simulator that allows traders and researchers to generate
 +
customized market data based on chosen parameters such as
 +
volatility, trend strength, and volume. This will provide a larger
 +
and more diverse dataset to train trading algorithms, leading to
 +
better generalization and performance in various market
 +
environments.</p>
 +
</td>
 +
<td width="320" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" style="margin-bottom: 0.2in">
 +
Project Inputs:</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">Students will be
 +
provided with:</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">1. A
 +
representative set of market data for a given security (historical
 +
OHLCV data).</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">2. Parameters to
 +
tune the synthetic data generation, including market patterns,
 +
volatility, trends, and volume.</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">All required
 +
data is in public domain. No Citi proprietary data is required nor
 +
will be shared for this project.  
 +
</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">Project
 +
Deliverables:</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">1. Synthetic
 +
Data Generator: A working model that simulates and outputs
 +
synthetic market data based on input parameters.</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">2.
 +
Parameterization: A set of controls to modify the synthetic data
 +
generation, including trend types, volatility levels, and other
 +
key market conditions.</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">3. Transaction
 +
Output: The output will be a file containing the generated market
 +
data, with fields such as Open, High, Low, Close, and Volume
 +
(OHLCV).</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">4.
 +
Documentation: Detailed documentation explaining how the synthetic
 +
data is generated, how to use the parameterization tools, and how
 +
the simulator can be applied in algorithm training.</p>
 +
<p class="msonormal">5. Presentation: A demonstration of the
 +
synthetic market simulator, including use cases for improving
 +
trading algorithm performance.</p>
 +
</td>
 +
<td width="151" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" style="margin-bottom: 0.2in">
 +
Project Coordinator: TBA</p>
 +
<p class="msonormal">Project Mentor: Nirav Parikh</p>
 +
</td>
 +
</tr>
 +
<tr valign="top">
 +
<td width="73" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: 1.00pt solid #000000; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0.08in; padding-right: 0.08in"><p class="msonormal" align="center" style="margin-bottom: 0.2in">
 +
Project #6</p>
 +
<p class="msonormal" align="center">FY2024/25 <br/>
 +
Term 2</p>
 +
</td>
 +
<td width="78" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal">
 +
Citi - &nbsp;Investment Banking</p>
 +
</td>
 +
<td width="322" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" style="margin-bottom: 0.2in">
 +
<b>Deal Review Committee Using LLM Agents</b></p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">In investment
 +
banking, evaluating deals for new clients involves multiple
 +
dimensions of analysis. Banks must assess the market potential,
 +
competitive positioning, and risk profile of a client’s
 +
business, while estimating revenue and cost projections.
 +
Additionally, ensuring compliance with regulatory standards and
 +
aligning deals with the bank’s strategic objectives are crucial
 +
aspects of decision-making.</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">This project
 +
proposes the development of a framework utilizing Large Language
 +
Model (LLM) agents to simulate a virtual committee of financial
 +
experts. Each LLM agent will be specialized in specific areas such
 +
as risk assessment (credit, market, operational, regulatory,
 +
reputational), revenue estimation, compliance, and strategic
 +
alignment. By simulating the expertise of real-world financial
 +
analysts and risk managers, this system will provide a
 +
comprehensive review of deal proposals for new clients.</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">The goal is to
 +
enhance decision-making, mitigate risks, ensure regulatory
 +
compliance, and foster profitable client relationships, helping
 +
banks balance opportunity with risk for long-term sustainability
 +
and growth.</p>
 +
<p class="msonormal">Investment banks face challenges in
 +
evaluating deal proposals due to the need for multi-faceted
 +
analysis across revenue potential, risk assessment, regulatory
 +
compliance, and strategic fit. This project aims to develop a
 +
framework leveraging LLM agents to provide a holistic and
 +
expert-driven approach to deal review, improving both the
 +
efficiency and accuracy of decision- making processes.</p>
 +
</td>
 +
<td width="320" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" style="margin-bottom: 0.2in">
 +
Project Inputs:</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">Students will be
 +
provided with:</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">1. Training data
 +
from previous deal reviews, including analysis from financial
 +
analysts and risk managers.</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">2. Access to
 +
relevant market data, risk factors, and financial models.</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">3. Strategic
 +
guidelines and risk appetite documentation for new deals.</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">Note: Anonymized
 +
Citi internal data (no client data) will be required for this
 +
project subject to approvals and potential NDA agreements.</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">Project
 +
Deliverables:</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">1. LLM-Based
 +
Expert Agents: A framework of specialized LLM agents trained to
 +
simulate expert perspectives in areas such as revenue estimation,
 +
risk analysis, compliance, and strategic alignment.</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">2. Virtual
 +
Committee Decision Process: A mechanism for synthesizing the
 +
insights from different agents to form a comprehensive
 +
recommendation on deal approval and conditions.</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">3. Decision
 +
Support System: A tool that provides deal recommendations,
 +
approval conditions, and risk mitigation strategies based on the
 +
committee’s output.</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">4.
 +
Documentation: Comprehensive documentation outlining the design,
 +
methodology, and decision-making process of the virtual committee
 +
of LLM agents.</p>
 +
<p class="msonormal">5. Presentation: A final presentation
 +
showcasing the framework, its decision-making process, and its
 +
potential impact on the bank's deal review process.</p>
 +
</td>
 +
<td width="151" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" style="margin-bottom: 0.2in">
 +
Project Coordinator: TBA</p>
 +
<p class="msonormal">Project Mentor: Nirav Parikh</p>
 +
</td>
 +
</tr>
 +
<tr valign="top">
 +
<td width="73" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: 1.00pt solid #000000; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0.08in; padding-right: 0.08in"><p class="msonormal" align="center" style="margin-bottom: 0.2in">
 +
Project #7</p>
 +
<p class="msonormal" align="center">FY2024/25<br/>
 +
Term 2</p>
 +
<p class="msonormal" align="center">Fulfills BA</p>
  
Project sponsor will share further context on the various pain points and priorities around onboarding and training new hires. Specific use case and target audience personas will be defined and shared with the students too.
+
</td>
|width="20%"|<!-- Project Stakeholders -->  
+
<td width="78" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal">
Project Coordinator: Dossii, Shailej P <br>
+
Revolut - Digital Investing</p>
shailej.p.dossii@citi.com <br> <br>
+
</td>
Project Mentor: Go Cheng Yan <br>
+
<td width="322" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" style="margin-bottom: 0.2in">
email cg14129@citi.com
+
<b>Bespoke Robo Advisory Platform for Retail Users</b></p>
|-
+
<p class="msonormal" style="margin-bottom: 0.2in">Create a digital
|width="2%"|<!-- Item--> X
+
investment platform that allows users to invest into through
|width="10%"|<!-- Sponsor--> Citibank
+
Revolut’s Robo-advisory solution coupled with the Users own
|width="30%"|<!-- Project Description --> '''Data APIs using Low Code''' - Lots of our data sourcing is driven from embedding SQL or Logic in Stored procedures. This makes the application logic heavily dependent on data which sometimes is not even owned by the given service. Accessing data in an easy way within a distributed platform is a big challenge. A low-code development platform (LCDP) provides a development environment used to create application software through a graphical user interface. A low-coded platform may produce entirely operational applications, or require additional coding for specific situations
+
inputs relating to Risk Appetite, preferred asset class mix,
https://en.wikipedia.org/wiki/Low-code_development_platform
+
single name stocks and investment amount.
The objective is to develop Data APIs using Low code technology automation. This is an agile way of software development. It will deliver easy access of our data (reference / product / transactional) to our Web, Mobile UI and reposting modules.
+
</p>
|width="30%"|<!-- Project Deliverables --> Students are expected to deliver:
+
<p class="msonormal" style="margin-bottom: 0.2in">The ask is to
* POC for Low Code products.  
+
create a web app that:</p>
* Design new APIs based of selection made by project sponsor.  
+
<p class="msonormal" style="margin-left: 0.3in; margin-bottom: 0.2in">
* Working APIs for data from current sources.
+
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Allows users to include
 +
more inputs before letting Robo advisory take over the investment
 +
of users funds.
 +
</p>
 +
<p class="msonormal" style="margin-left: 0.3in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; List of investment
 +
instruments and asset classes available
 +
</p>
 +
<p class="msonormal" style="margin-left: 0.3in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Visualize the performance
 +
data using charts, tables etc. in a simple, uncluttered fashion.
 +
</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">Robo-advisory is
 +
a useful solution / tool for beginning and intermediate investors
 +
who wise to utilize ”Robos” to optimize users funds and invest
 +
accordingly based on black box algorithms built by the Robo
 +
Advisory company.</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">The Problem is
 +
that users have little or no say in which specific asset class,
 +
industries, or single name stocks should the investor have a
 +
preference in whilst offering the investor expertise of the Robo
 +
Advisory perform dynamic asset re-allocation as and when the need
 +
to do arises.
 +
</p>
 +
<p class="msonormal">So the idea is to create a platform which is
 +
a hybrid of a Robo-Advisor and a full manual trading platform</p>
 +
</td>
 +
<td width="320" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" style="margin-bottom: 0.2in">
 +
Project Inputs:</p>
 +
<p class="msonormal" style="margin-left: 0.27in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Project sponsors will
 +
share sufficient context so students can understand how/where this
 +
platform brings value to users.</p>
 +
<p class="msonormal" style="margin-left: 0.27in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; The mock raw data files,
 +
explanation of this data structure and other useful details will
 +
be available.</p>
 +
<p class="msonormal" style="margin-left: 0.02in; margin-bottom: 0.2in">
 +
Project Deliverables:
 +
</p>
 +
<p class="msonormal" style="margin-left: 0.27in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Working App that provides
 +
intuitive UI/UX.
 +
</p>
 +
<p class="msonormal" style="margin-left: 0.27in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; This App should be a
 +
standalone application that can be easily incorporated in a larger
 +
application. Freedom to use visualization &amp; analysis tools,
 +
technology of the team’s choice.</p>
 +
<p class="msonormal">&nbsp;</p>
 +
</td>
 +
<td width="151" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" style="margin-bottom: 0.2in">
 +
Project Coordinator: [ TBA ]
 +
</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">&nbsp;</p>
 +
<p class="msonormal">Project Mentor: Abhinav Suryavanshi</p>
 +
</td>
 +
</tr>
 +
<tr valign="top">
 +
<td width="73" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: 1.00pt solid #000000; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0.08in; padding-right: 0.08in"><p class="msonormal" align="center" style="margin-bottom: 0.2in">
 +
Project #8 FY2024/25 <br/>
 +
Term 2</p>
 +
<p class="msonormal" align="center">Fulfills BA</p>
 +
</td>
 +
<td width="78" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal">
 +
Singapura Finance -Regulatory Compliance</p>
 +
</td>
 +
<td width="322" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" style="margin-bottom: 0.2in">
 +
<b>Customer Profiling Application</b></p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">Customers are
 +
on-boarded to the bank’s system after performing checks and
 +
validation for know your customer and anti-money laundering
 +
(KYC/AML) compliance.</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">The solution
 +
should extract information about existing customers, run checks
 +
and document results. It will score each customer based on given
 +
parameters. The parameters may change over time, so flexibility to
 +
adjust the parameter will be required.</p>
 +
<p class="msonormal">The current approach to handling AML scoring
 +
and documenting of customer profile is manually done by staff. It
 +
is not consistent and prone to oversight and missing filed
 +
information.</p>
 +
</td>
 +
<td width="320" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" style="margin-bottom: 0.2in">
 +
Project Inputs:</p>
 +
<p class="msonormal" style="margin-left: 0.27in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Project sponsors will
 +
share context so students can understand how/where this
 +
digitalization can add value to the organization.</p>
 +
<p class="msonormal" style="margin-left: 0.27in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; The mock up data and
 +
parameter for scoring will be shared with explanation on the
 +
digital filing requirements.</p>
 +
<p class="msonormal" style="margin-left: 0.27in; margin-bottom: 0.2in">
 +
<font color="#000000">•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
 +
</font><font color="#000000"><span lang="en-SG">Potential to use
 +
ML Tools to profile customer</span></font></p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">Project
 +
Deliverables:
 +
</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">A solution or
 +
program which can accomplish the following:</p>
 +
<p class="msonormal" style="margin-left: 0.27in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Take in a customer
 +
information from the banking system</p>
 +
<p class="msonormal" style="margin-left: 0.27in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Profile the customer
 +
information using available search/information engine/service
 +
provider. Obtain the results</p>
 +
<p class="msonormal" style="margin-left: 0.27in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Provide data visualization
 +
of the results obtained</p>
 +
<p class="msonormal" style="margin-left: 0.27in; margin-bottom: 0.2in">
 +
<font color="#000000">•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
 +
</font><font color="#000000"><span lang="en-SG">Score each
 +
customer&nbsp; profile</span></font></p>
 +
<p class="msonormal" style="margin-left: 0.27in; margin-bottom: 0.2in">
 +
<font color="#000000">•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
 +
</font><font color="#000000"><span lang="en-SG">Store the results
 +
for historical review or audit review requirement.</span></font></p>
 +
<p class="msonormal" style="margin-left: 0.27in; margin-bottom: 0.2in">
 +
<font color="#000000">•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
 +
</font><font color="#000000"><span lang="en-SG">Allow
 +
customization of the scoring</span></font></p>
 +
<p class="msonormal" style="margin-left: 0.27in; margin-bottom: 0.2in">
 +
<font color="#000000">•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; </font><font color="#000000"><span lang="en-SG">Easy
 +
search and identification of customer profile documents collated.</span></font></p>
 +
<p class="msonormal"><font color="#000000">•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
 +
</font><font color="#000000"><span lang="en-SG">Allow for
 +
triggering of review on customer information based on score</span></font></p>
 +
</td>
 +
<td width="151" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" style="margin-bottom: 0.2in">
 +
Project Coordinator: (TBA)</p>
 +
<p class="msonormal">Project Mentor: Winny Ho</p>
 +
</td>
 +
</tr>
 +
<tr valign="top">
 +
<td width="73" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: 1.00pt solid #000000; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0.08in; padding-right: 0.08in"><p class="msonormal" align="center" style="margin-bottom: 0.2in">
 +
Project #9</p>
 +
<p class="msonormal" align="center" style="margin-bottom: 0.2in">FY2024/25
 +
<br/>
 +
Term 2</p>
 +
<p class="msonormal" align="center">Fulfills BA</p>
 +
</td>
 +
<td width="78" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" style="margin-bottom: 0.2in">
 +
Singapura Finance - Risk Management</p>
 +
<p class="msonormal">&nbsp;</p>
 +
</td>
 +
<td width="322" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" style="margin-bottom: 0.2in">
 +
<b>Consumer Loans Credit Scoring</b></p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">The bank
 +
implemented an online straight through loan application (Mortgage)
 +
using government provided information, with customers consent.
 +
</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">The system does
 +
not identify nor prioritize customer profile, hence good/great
 +
customers are left together with the majority.</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">Solution will
 +
use information obtained by the government data source and
 +
generate a credit score each application. An application may have
 +
more than one submission (Multiple owners).</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">The solution
 +
should provide automated recommendation for improved loan rates
 +
for of better scoring customers. It should also document and
 +
recommend follow-up for lower scoring applications.</p>
 +
<p class="msonormal">&nbsp;</p>
 +
</td>
 +
<td width="320" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" style="margin-bottom: 0.2in">
 +
Project Inputs:</p>
 +
<p class="msonormal" style="margin-left: 0.25in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Project sponsors will
 +
share context so students can understand how/where this
 +
digitalization can add value to the organization.</p>
 +
<p class="msonormal" style="margin-left: 0.25in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; The mock up data and
 +
parameter for scoring will be shared with explanation on the
 +
digital filing requirements.</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">Project
 +
Deliverables:
 +
</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">An app that
 +
provides the following:</p>
 +
<p class="msonormal" style="margin-left: 0.25in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Take in a customer
 +
information submitted via online forms/government data.</p>
 +
<p class="msonormal" style="margin-left: 0.25in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Profile the customer
 +
information</p>
 +
<p class="msonormal" style="margin-left: 0.25in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Analyze the results
 +
obtained and score each application</p>
 +
<p class="msonormal" style="margin-left: 0.25in; margin-bottom: 0.2in">
 +
<font color="#000000">•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
 +
</font><font color="#000000"><span lang="en-SG">Allow
 +
customization of the scoring using various data points available.</span></font></p>
 +
<p class="msonormal" style="margin-left: 0.27in; margin-bottom: 0.2in">
 +
<font color="#000000">•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</font>Provide
 +
data visualization of the results obtained</p>
 +
<p class="msonormal"><font color="#000000">•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
 +
</font><font color="#000000"><span lang="en-SG">Results will be
 +
sent to back-room for processing or automated escalated actions.</span></font></p>
 +
</td>
 +
<td width="151" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" style="margin-bottom: 0.2in">
 +
Project Coordinator: (TBA)</p>
 +
<p class="msonormal">Project Mentor: Cindy Ng</p>
 +
</td>
 +
</tr>
 +
<tr valign="top">
 +
<td width="73" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: 1.00pt solid #000000; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0.08in; padding-right: 0.08in"><p class="msonormal" align="center" style="margin-bottom: 0.2in">
 +
Project #10</p>
 +
<p class="msonormal" align="center">FY2024/25 <br/>
 +
Term 2</p>
 +
</td>
 +
<td width="78" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal">
 +
Tiger Fund - Fund Management</p>
 +
</td>
 +
<td width="322" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" style="margin-bottom: 0.2in">
 +
<b>Using Artificial Intelligence for Effective Stock Screening</b></p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">This project
 +
focuses on using artificial intelligence (AI) to develop an
 +
effective stock screening tool that assists investors in
 +
identifying potential buying or selling opportunities in the U.S.
 +
stock market.
 +
</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">With the vast
 +
amount of data generated daily, AI can automate the screening
 +
process by quickly analyzing stock trends, sector performance, and
 +
user-defined parameters to detect valuable market opportunities.
 +
</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">The system will
 +
leverage machine learning algorithms and technical indicators to
 +
filter stocks based on investor preferences, such as
 +
undervaluation, technical patterns, or strong market trends.
 +
</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">The goal is to
 +
streamline stock selection and improve decision-making efficiency
 +
for portfolio managers.</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">Investors face a
 +
challenge in sorting through the immense quantity of stock market
 +
data to identify opportunities for profitable trading. The manual
 +
stock screening process is time-consuming and prone to human
 +
error, especially when considering various technical indicators
 +
and market conditions.
 +
</p>
 +
<p class="msonormal">This project aims to address these issues by
 +
developing an AI-powered stock screening system capable of
 +
efficiently analyzing stock data, detecting strong market trends,
 +
and automating the identification of potential buying or selling
 +
opportunities based on predefined criteria.</p>
 +
</td>
 +
<td width="320" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" style="margin-bottom: 0.2in">
 +
&nbsp;Project Inputs:</p>
 +
<p class="msonormal" style="margin-left: 0.25in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Project sponsors will
 +
share sufficient context so students can understand how/where this
 +
project brings value to users.</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">Project
 +
Deliverables:
 +
</p>
 +
<p class="msonormal" style="margin-left: 0.25in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; AI-Powered Stock Screener
 +
Application: A functional application that can analyze large
 +
datasets and apply user-defined parameters to screen stocks.</p>
 +
<p class="msonormal" style="margin-left: 0.25in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Backtesting: To engage in
 +
backtesting of the model in order to ensure the reliability of the
 +
system</p>
 +
<p class="msonormal" style="margin-left: 0.25in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Market Trend Detection
 +
Module: A feature that detects strong market trends or significant
 +
changes in sector performance.</p>
 +
<p class="msonormal" style="margin-left: 0.25in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Sector Analysis Tool: A
 +
tool to conduct in-depth analysis of sectors to identify potential
 +
opportunities for buying recommendations.</p>
 +
<p class="msonormal" style="margin-left: 0.25in; margin-bottom: 0.2in">
 +
<font color="#000000">•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
 +
</font><font color="#000000"><span lang="en-SG">Sentiment Analysis
 +
Engine: </span></font><font color="#000000">A system that scrapes
 +
and analyzes sentiment data from news articles, social media, and
 +
financial reports, and integrates it into the model.</font></p>
 +
<p class="msonormal">•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; User
 +
Interface for Stock Screening: An interactive interface where
 +
users can input their screening criteria and view stock
 +
recommendations in real-time.</p>
 +
</td>
 +
<td width="151" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" style="margin-bottom: 0.2in">
 +
Project Coordinator: [TBA]</p>
 +
<p class="msonormal">Project Mentor: [TBA]</p>
 +
</td>
 +
</tr>
 +
<tr valign="top">
 +
<td width="73" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: 1.00pt solid #000000; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0.08in; padding-right: 0.08in"><p class="msonormal" align="center" style="margin-bottom: 0.2in">
 +
Project #11</p>
 +
<p class="msonormal" align="center" style="margin-bottom: 0.2in">FY2024/25
 +
<br/>
 +
Term 2</p>
 +
<p class="msonormal" align="center">Fulfills BA</p>
 +
</td>
 +
<td width="78" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal">
 +
Tiger Fund - Fund Management</p>
 +
</td>
 +
<td width="322" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" style="margin-bottom: 0.2in">
 +
<b>Using Artificial Intelligence to Time the Market</b></p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">The project aims
 +
to build a machine learning-based system that assists portfolio
 +
managers with accurate market timing by predicting the prices of
 +
major Exchange-Traded Funds (ETFs) such as SPY (S&amp;P 500 ETF)
 +
and TLT (Treasury Bond ETF).
 +
</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">The core
 +
component of this system will be an AI model, potentially using a
 +
Long Short-Term Memory (LSTM) neural network, which will predict
 +
future prices based on a blend of economic, fundamental,
 +
sentiment, and technical data.</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">The model will
 +
be designed to continuously learn and adapt to evolving financial
 +
environments, making real-time predictions.
 +
</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">The data inputs
 +
will be aggregated from reliable financial sources like FRED,
 +
World Bank, Yahoo Finance, and sentiment analysis from news
 +
outlets, social media, and financial reports to develop a
 +
comprehensive model.
 +
</p>
 +
<p class="msonormal">Accurate market timing is one of the most
 +
challenging tasks for portfolio managers. Market prices fluctuate
 +
based on a wide range of factors, including economic indicators,
 +
fundamental analysis, market sentiment, and technical trends.
 +
Traditional financial models often fail to capture the complexity
 +
and rapid changes in market dynamics. This project seeks to bridge
 +
the gap by leveraging machine learning to forecast ETF prices more
 +
accurately and continuously adapt to changing market conditions.</p>
 +
</td>
 +
<td width="320" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" style="margin-bottom: 0.2in">
 +
Project Inputs:</p>
 +
<p class="msonormal" style="margin-left: 0.25in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Project sponsors will
 +
share sufficient context so students can understand how/where this
 +
project brings value to users.</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">Project
 +
Deliverables:
 +
</p>
 +
<p class="msonormal" style="margin-left: 0.25in; margin-bottom: 0.2in">
 +
<font color="#000000">•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; </font><font color="#000000"><span lang="en-SG">AI
 +
Prediction Model: </span></font><font color="#000000">A machine
 +
learning model trained to predict the prices of SPY and TLT based
 +
on technical, economic, fundamental, and sentiment data. An AI
 +
system capable of retraining itself as new data becomes available,
 +
allowing for adaptation to market changes.</font></p>
 +
<p class="msonormal" style="margin-left: 0.25in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Backtesting: To engage in
 +
backtesting of the model in order to ensure the reliability of the
 +
system</p>
 +
<p class="msonormal" style="margin-left: 0.25in; margin-bottom: 0.2in">
 +
<font color="#000000">•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
 +
</font><font color="#000000"><span lang="en-SG">Sentiment Analysis
 +
Engine: </span></font><font color="#000000">A system that scrapes
 +
and analyzes sentiment data from news articles, social media, and
 +
financial reports, and integrates it into the model.</font></p>
 +
<p class="msonormal" style="margin-left: 0.25in; margin-bottom: 0.2in">
 +
<font color="#000000">•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; </font><font color="#000000"><span lang="en-SG">Risk
 +
Appetite Indicator: </span></font><font color="#000000">A
 +
composite indicator driven by sentiment analysis, measuring market
 +
risk aversion or appetite to inform predictions.</font></p>
 +
<p class="msonormal" style="margin-left: 0.25in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Data Pipeline: Web
 +
scraping and integration pipeline to pull continuous data from
 +
FRED, World Bank, Yahoo Finance, and other relevant sources.</p>
 +
<p class="msonormal"><font color="#000000">•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
 +
</font><font color="#000000"><span lang="en-SG">Dashboard
 +
Interface: </span></font><font color="#000000">A user-friendly
 +
dashboard to display model predictions, risk appetite indicators,
 +
and relevant metrics.</font></p>
 +
</td>
 +
<td width="151" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" style="margin-bottom: 0.2in">
 +
Project Coordinator: [TBA]</p>
 +
<p class="msonormal">Project Mentor: [TBA]</p>
 +
</td>
 +
</tr>
 +
<tr valign="top">
 +
<td width="73" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: 1.00pt solid #000000; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0.08in; padding-right: 0.08in"><p class="msonormal" align="center" style="margin-bottom: 0.2in">
 +
Project #12</p>
 +
<p class="msonormal" align="center" style="margin-bottom: 0.2in">FY2024/25
 +
<br/>
 +
Term 2</p>
 +
<p class="msonormal" align="center">Fulfills BA</p>
 +
</td>
 +
<td width="78" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal">
 +
UBS - &nbsp;Equities</p>
 +
</td>
 +
<td width="322" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" style="margin-bottom: 0.2in">
 +
<b>News Screener For Relevant Investment Opportunities</b></p>
 +
<p class="msonormal" style="margin-bottom: 0.17in">Bankers and
 +
Investment counselors (ICs) develop deep relationships with
 +
clients and provide them with relevant investment and
 +
opportunities advices based on client’s needs.
 +
</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">The ask is to
 +
create a tool that:<br/>
 +
Scans publicly available social media and
 +
news sources for news about relevant sector’s or region’s
 +
current and ongoing events and their co-related relevant companies
 +
or entities.</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">Summarize these
 +
views to a digestible format for Client Advisor, Ensure each data
 +
point has a source link, that would enable the Client Advisor to
 +
verify that the subject is indeed relevant to preferences of their
 +
client.</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">Freedom to use
 +
visualization &amp; analysis tools, generative AI, APIs and
 +
technology of the team’s choice. However the solution should be
 +
hosted in an Azure Cloud.</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">Example: Tools
 +
scans news from the ‘Financial Times’ for relevant sector
 +
‘Real Estate’ and region ‘China’, Based on the news
 +
coverage, it identifies the current market trend and effected
 +
companies and instruments relevant to those companies and provides
 +
a relevant view to client advisors.</p>
 +
<p class="msonormal">Given current volatile world and lots of
 +
information being generated every moment, analysts require smart
 +
intelligent tools to sort through all those and provide clients
 +
with relevant investment advices on timely manner. The tool is to
 +
automated way to scan news, provide digest about the news in
 +
categories like sector, region and entity. Also to provide
 +
relevant&nbsp; sentiment of the news.</p>
 +
</td>
 +
<td width="320" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" style="margin-bottom: 0.2in">
 +
Project Inputs:</p>
 +
<p class="msonormal" style="margin-left: 0.25in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Project sponsors will
 +
provide 5 entity names, and suggested data sources on which the
 +
output should be created</p>
 +
<p class="msonormal" style="margin-left: 0.25in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Project Sponsors will
 +
review at regular intervals the outputs to refine requirements and
 +
usability of output.</p>
 +
<p class="msonormal" style="margin-left: 0.25in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; We will provide support on
 +
how to perform identity matching for the entities.</p>
 +
<p class="msonormal" style="margin-left: 0.25in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Team can use AI tools to
 +
discover digest of news (e.g. news is about ‘Real Estate’
 +
sector.)</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">Project
 +
Deliverables:
 +
</p>
 +
<p class="msonormal" style="margin-left: 0.25in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Working dashboard that
 +
provides a real view of relevant sectors and entities.
 +
</p>
 +
<p class="msonormal" style="margin-left: 0.25in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; View provides contextual
 +
correlated sentiment assessment of entities.</p>
 +
<p class="msonormal" style="margin-left: 0.25in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; View provides trigger
 +
notifications when significant activity threshold is breached
 +
(optional).</p>
 +
<p class="msonormal" style="margin-left: 0.25in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; View provides collected
 +
historical information and perform system end to end risk and
 +
returns on entities.</p>
 +
<p class="msonormal" style="margin-left: 0.25in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Ability to collect data
 +
from different sources.</p>
 +
<p class="msonormal">&nbsp;</p>
 +
</td>
 +
<td width="151" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" style="margin-bottom: 0.2in">
 +
Project Coordinator: Kumar, Ajith-A
 +
</p>
 +
<p class="msonormal">Project Mentor: Hossain, Mohammad-Jahangir
 +
</p>
 +
</td>
 +
</tr>
 +
<tr valign="top">
 +
<td width="73" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: 1.00pt solid #000000; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0.08in; padding-right: 0.08in"><p class="msonormal" align="center" style="margin-bottom: 0.2in">
 +
Project #13</p>
 +
<p class="msonormal" align="center">FY2024/25 <br/>
 +
Term 2</p>
 +
</td>
 +
<td width="78" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal">
 +
UBS - &nbsp;Mobile banking</p>
 +
</td>
 +
<td width="322" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" style="margin-bottom: 0.2in">
 +
<b>Modern web application and Native Mobile application for
 +
Portfolio viewing of a banking customer</b></p>
 +
<p class="msonormal" style="margin-bottom: 0.17in">There are
 +
already a quite a lot of Banking asset viewing and portfolio
 +
viewing apps in the market currently. Having a great user
 +
experience for such apps are key for success of any business. User
 +
experience is garnered from Customer experience strategy, research
 +
and design. Understanding user behavior and human computer
 +
interaction techniques are key in designing and implementing next
 +
gen user experience application is key.</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">In this project
 +
you will produce native iOS/Android mobile application and web
 +
application using latest technology which inculcates great
 +
customer experience design , user experience design and
 +
wireframes. There are already great deal of research materials on
 +
this subject, so need a both balanced academic view and already
 +
existing app view to come out with a great application to do
 +
portfolio viewing of a Banking clients assets. The backend may
 +
have mock data to begin with so not really expecting the app to
 +
work end to end. Key success criteria are to have a great visual
 +
and customer experience for these apps.</p>
 +
<p class="msonormal">This project aims to develop a banking
 +
portfolio viewing application which targets the upcoming
 +
generation of banking application consumers, ie. Gen Z and
 +
Millennials. Additionally, we will enhance the user experience of
 +
our application by implementing specific design considerations
 +
obtained through rigorous user research and analysis of
 +
human-computer interactions.</p>
 +
</td>
 +
<td width="320" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" style="margin-bottom: 0.2in">
 +
Project Inputs:</p>
 +
<p class="msonormal" style="margin-left: 0.25in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Technology services mentor
 +
will provide insights on deep knowledge on the subject
 +
</p>
 +
<p class="msonormal" style="margin-left: 0.25in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Help students to formulate
 +
the solution ideation
 +
</p>
 +
<p class="msonormal" style="margin-left: 0.25in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Provide the expertise
 +
where necessary for the group to produce a industry standard
 +
solution</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">Project
 +
Deliverables:
 +
</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">Must Have:</p>
 +
<p class="msonormal" style="margin-left: 0.25in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Working Mobile application
 +
for asset viewing targeted at Gen-Z age group</p>
 +
<p class="msonormal" style="margin-left: 0.25in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Design and develop a
 +
prototype which has a high customer experience design and HCI.</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">Nice To Have:</p>
 +
<p class="msonormal" style="margin-left: 0.25in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Fully working backend is
 +
not a requirement. Application can have a static data to power the
 +
application.
 +
</p>
 +
<p class="msonormal">&nbsp;</p>
 +
</td>
 +
<td width="151" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal">
 +
Project Coordinator: Kumar, Ajith-A Project Mentors: Sanghavi,
 +
Seema</p>
 +
</td>
 +
</tr>
 +
<tr valign="top">
 +
<td width="73" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: 1.00pt solid #000000; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0.08in; padding-right: 0.08in"><p class="msonormal" align="center" style="margin-bottom: 0.2in">
 +
Project #14</p>
 +
<p class="msonormal" align="center">FY2024/25 <br/>
 +
Term 2</p>
 +
</td>
 +
<td width="78" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal">
 +
UBS - &nbsp;Regulatory Compliance</p>
 +
</td>
 +
<td width="322" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" style="margin-bottom: 0.2in">
 +
<b>FinRegScanner</b></p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">Banks have to
 +
adhere to multiple market and exchange related financial
 +
regulations. The compliance function has to be vigilant in
 +
identifying the regulations that are published by various
 +
countries, regions and by industry bodies and implement them on
 +
time. If a bank is not regulatory compliant, that could lead to
 +
various repercussions from financial penalties, reputational
 +
impact to even posing a risk to the financial system as a whole.</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">Once a
 +
regulation is identified, few companies look out for vendor
 +
solutions and few companies build solutions in-house and this
 +
often requires a lot of coordination among various functions/teams
 +
to ensure that the regulation gets adhered to on time.</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">Hence, it would
 +
great if technology can help to assist and simplify the regulatory
 +
project management and implementation.</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">Right from
 +
identification of a financial regulation that the bank needs to
 +
adhere to, till the implementation, is very complex to manage,
 +
time intensive and costly affair.</p>
 +
<p class="msonormal">Build a solution that can act as an assistive
 +
tool to Compliance function of an organization to help detect,
 +
plan and manage regulatory impacts in a timely manner within the
 +
organization.</p>
 +
</td>
 +
<td width="320" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" style="margin-bottom: 0.2in">
 +
Project Inputs:</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
 +
Project Sponsors will provide information about regulatory data
 +
sources and will also give a brief overview of Financial
 +
Regulatory Landscape and relevant support wherever required</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
 +
Project Sponsors will review the output at regular intervals to
 +
provide feedback and to refine requirements</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">Project
 +
Deliverables:
 +
</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">Must Have:</p>
 +
<p class="msonormal" style="margin-left: 0.25in; margin-bottom: 0.2in">
 +
1)&nbsp;&nbsp;&nbsp; Identify upcoming regs and their regulatory
 +
deadline</p>
 +
<p class="msonormal" style="margin-left: 0.25in; margin-bottom: 0.2in">
 +
2)&nbsp;&nbsp;&nbsp; Summarize the requirements for each impacted
 +
business division and able to query the regulatory text and get
 +
answers</p>
 +
<p class="msonormal" style="margin-left: 0.25in; margin-bottom: 0.2in">
 +
3)&nbsp;&nbsp;&nbsp; Apply a chatbot feature to query the QnA</p>
 +
<p class="msonormal" style="margin-left: 0.25in; margin-bottom: 0.2in">
 +
4)&nbsp;&nbsp;&nbsp; Provide a dashboard to visualize the key
 +
features of the regulations.
 +
</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">Nice To Have:</p>
 +
<p class="msonormal" style="margin-left: 0.25in; margin-bottom: 0.2in">
 +
1)&nbsp;&nbsp;&nbsp; Build a machine learning model to classify
 +
the regulation, identify the potential impacts for each business
 +
division</p>
 +
<p class="msonormal" style="margin-left: 0.25in; margin-bottom: 0.2in">
 +
2)&nbsp;&nbsp;&nbsp; Provide a comparison with other regulations
 +
of similar nature</p>
 +
<p class="msonormal">&nbsp;</p>
 +
</td>
 +
<td width="151" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" style="margin-bottom: 0.2in">
 +
Project Coordinator: Kumar, Ajith-A
 +
</p>
 +
<p class="msonormal">Project Mentors: Kumar, Phanindra; Kumar,
 +
Ajith-A</p>
 +
</td>
 +
</tr>
 +
<tr valign="top">
 +
<td width="73" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: 1.00pt solid #000000; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0.08in; padding-right: 0.08in"><p class="msonormal" align="center" style="margin-bottom: 0.2in">
 +
Project #15</p>
 +
<p class="msonormal" align="center">FY2024/25 <br/>
 +
Term 2</p>
 +
</td>
 +
<td width="78" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal">
 +
UBS - &nbsp;Wealth Management</p>
 +
</td>
 +
<td width="322" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" style="margin-bottom: 0.2in">
 +
<b>Gamified Financial Literacy Application</b></p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">Financial
 +
Literacy is essential in wealth management as it enables
 +
individuals to make informed decisions about growing, protecting
 +
and preserving their assets.</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">The ask is to
 +
create a gamified financial literacy app that teaches essential
 +
money management skills through interactive challenges, quizzes,
 +
activities, simulations and make financial education engaging and
 +
fun for all ages. Users earn badges and unlock new levels as they
 +
progress through next stages in their learning paths consisting of
 +
topics ranging from time value of money, insurance, emergency
 +
fund, asset allocation, budgeting, saving, investing etc.</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">Financial
 +
Literacy is essential in wealth management as it enables
 +
individuals to make informed decisions about growing, protecting
 +
and preserving their assets.</p>
 +
<p class="msonormal">The ask is to create a gamified financial
 +
literacy app that teaches essential money management skills
 +
through interactive challenges, quizzes, activities, simulations
 +
and make financial education engaging and fun for all ages. Users
 +
earn badges and unlock new levels as they progress through next
 +
stages in their learning paths consisting of topics ranging from
 +
time value of money, insurance, emergency fund, asset allocation,
 +
budgeting, saving, investing etc.
 +
</p>
 +
</td>
 +
<td width="320" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" style="margin-bottom: 0.2in">
 +
Project Inputs:</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
 +
Project sponsors will share sufficient information regarding the
 +
various aspects of personal finance</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
 +
Mentors will guide the students on building learning paths and
 +
scenario simulations</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
 +
Mentors will review&nbsp;the progress at regular intervals to
 +
refine requirements and usability of the app.</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">Project
 +
Deliverables:
 +
</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">Must Have:</p>
 +
<p class="msonormal" style="margin-left: 0.25in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Fully functional
 +
responsive / mobile native application with at least 2-3 financial
 +
literacy learning paths.</p>
 +
<p class="msonormal" style="margin-left: 0.25in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Excellent user experience
 +
with security features implemented.</p>
 +
<p class="msonormal" style="margin-left: 0.25in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Real time analytics to
 +
track progress with personalized insights and badges</p>
 +
<p class="msonormal" style="margin-left: 0.25in; margin-bottom: 0.2in">
 +
•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Admin dashboard showing
 +
the learning progress, and the badges earned by all the users.</p>
 +
<p class="msonormal" style="margin-bottom: 0.2in">Nice To Have:</p>
 +
<p class="msonormal">•&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
 +
Integration with ChatGPT or other LLMs for personal finance
 +
scenario simulations</p>
 +
</td>
 +
<td width="151" style="border-top: none; border-bottom: 1.00pt solid #000000; border-left: none; border-right: 1.00pt solid #000000; padding-top: 0in; padding-bottom: 0.02in; padding-left: 0in; padding-right: 0.08in"><p class="msonormal" style="margin-bottom: 0.2in">
 +
Project Coordinator: Kumar, Ajith-A
 +
</p>
 +
<p class="msonormal">Project Mentors: Gopalan Ramakrishnan</p>
 +
</td>
 +
</tr>
 +
</table>
  
Project learnings:
+
=== Archived Past Projects and Groups ===
* Experience in designing / developing APIs.
+
AY2024/25 Term 1 <br>
* Learning an agile way of application development.
+
https://docs.google.com/spreadsheets/d/1IDAhC4JiK3RuKnIDQMG5UjJ6I1IiImo81Lu13wAuUxE/edit#gid=491663198 <br>
* Proof of connects with product(s) used of Low Code automation.
 
* Experience working on data complexity in a distributed system.
 
* Good idea about Capital Markets domain.
 
  
Project sponsors will share sufficient context so students can understand how current data flow works and what we expect from the APIs, and details about Low code products which can be used by Citi.
+
Past Project Descriptions<br>
|width="20%"|<!-- Project Stakeholders -->
+
https://docs.google.com/spreadsheets/d/1f7r2y1n6USWAYVTVyWkZkYxJt7HCoxlc-z3jAGzX7LQ/edit?gid=0#gid=0
Project Coordinator: Dossii, Shailej P <br>
 
shailej.p.dossii@citi.com <br> <br>
 
Project Mentor: Rohit Rohatgi <br>
 
email rohit.rohatgi@citi.com
 
|-
 
|}
 

Latest revision as of 11:40, 4 November 2024

Course Description:

  • This is an SMU-X course designed in collaboration with participating Banks, FinTechs, and other FIs, to serve as project sponsors. Collectively, industry sponsors will supply a minimum of 5 projects ideas to select from.
  • Students will form teams of 5 or 6, and select one the project ideas to work on. Project selections do not need to be unique, meaning multiple teams can select the same project idea.
  • Each student project team will be assigned to a sponsor/mentor and an SMU faculty supervisor.
  • Sponsors will provide project scope and management for student teams to have practical industry learning experiences.
  • Student teams will have weekly check in meetings, either virtually or physically, with their sponsor.
  • Sponsors will specify the technologies to be used, including; development tools/languages, OS, database, 3rd party libraries, target deployment environment e.g. cloud environment.
  • Student project teams will be expected to develop a working software application prototype, to be delivered to the sponsor at the end of the course.

Course Prerequisites:

1. Software Project Management (IS212) is a pre-requisite or a co-requisite.
2. Any two (2) track courses from the track that you are declaring for your project. One of these courses can be a co-requisite.

Project Timeline:

Activities Timeline Term 1/ Term 2 Action By
Project Sourcing and Registration Week -14 to Week -10 Form teams. Review the below set of predefined projects provided by Citibank, OCBC, NETS, UBS, and others. Fill up the Project Team Signup Sheet at the below link, listing your preferred projects. FT Track Coordinator will finalize the matching of teams to projects. Students
Project Matching Week -10 FT Track Coordinator will finalize the matching of teams to projects. FT Track Coordinator
Proposal Due before the start of Week -8 Submit your project proposals to your Track Coordinator(s). For mixed-track teams, both track coordinators need to review your proposal. Students
Decision on Proposal Week -4 Your Track Coordinator(s) will confirm that the project has sufficient scope to fulfill your respective track requirements for IS Project Experience. Track Coordinator, Students, (Optional: Sponsor)
Start of Project Week 1 Supervisor - Teams Student
Midterm Week 8 Presentation Students, Supervisor, Reviewer (Optional: Sponsor, Track Coordinator)
Finals Week 14 to Week 16 Presentation Students, Supervisor, Reviewer (Optional: Sponsor, Track Coordinator)

Project Team Signup Sheet:

AY2024/25 Term 2
https://docs.google.com/spreadsheets/d/1q-2qNkXGcjPxybU52s-1cazP5k4zhHTYRn7SKxz5Hjg/edit?gid=0#gid=0

Current Projects - FY2024/25 Term 2

ID, Term, and BA Status

Sponsor / Business Vertical

Project Description

Project Scope

Project Stakeholders

Project #1

FY2024/25
Term 2

Fulfills BA

OCBC - Consumer Banking

Fast Data Acquisition for Real-time Analytics
Core Banking processes a high volume of customer transactions including transfers, deposits and payments in an RDBMS (say PostgreSQL). There is a need to analyze the data real-time to detect any anomalies and generate operational reports. The application transaction database in optimized for high-availability and write performance, not analytics.

Therefore, there is a need for a real-time ingestion framework to stream transaction data from the source to the target operational data store (ODS), for real-time analytics.

Traditional batch ETL processes result in delayed data availability, leading to slower decision-making. Real-time analytics improves the customer

service, reduce fraud risk etc.

The key challenges that should be address are

Low latency: Data needs to be streamed in near real-time without impacting the performance of the source transaction system.

Data consistency: The data arriving at the ODS remains consistent with the source system, especially during high transaction volumes.

Scalability: The ingestion framework must scale to handle increasing transaction volumes during peak hours, like flash sales or promotions etc.

High Availability: The framework should tolerate failures and be resilient with high-availability. 

Project Inputs:
Project sponsors will share sufficient context so students can understand how/where this model brings value to users.

Project Deliverables:

•       A low latency real-time ingestion framework using CDC and should support CRUD operations to be consistent with the source database.

•       Analytics dashboard that provides insights as

•     Customer activity and behaviour

•     Pending or failed payments

•     Total transaction volume per minute/hour

•       Documentation with detailed setup instructions for configuring the ingestion with no-coding and just using configuration changes.

Project Coordinator: Lim Wei Ming
Project Mentor:

Radhakrishna Sarma

Project #2

FY2024/25
Term 2

OCBC - Front Office Relationship Managers

Front Office Dashboard / Client meeting prep support

The goal of this project is to leverage GenAI Technologies to develop a dashboard and client meeting preparation support system. The system will gather relevant information such as to-do lists, insights that clients would appreciate, follow-ups from previous meetings, outstanding document deficiencies, and areas requiring client feedback. All of this information will be consolidated into a meeting preparation pack, making it easier for professionals to prepare for client meetings efficiently.

Front office staff often struggle to gather and organize all the necessary information for client meetings. This leads to inefficiencies and potential oversights. Therefore, there is a need for a system that can streamline the process of gathering, organizing, and presenting important information to professionals before client meetings.

Project Inputs:

•       Project sponsors will share sufficient context so students can understand how/where this UI brings value to users.

•       Components required for effective client meeting preparation, including to-do lists, insights, follow-ups, document deficiencies, reviews, and client feedback.

•       Data or resources necessary for testing, such as sample client meeting data, client feedbacks, digital channel access data and relevant documents.

Project Deliverables:

•       Dashboard: Create a user-friendly dashboard that allows Front office to input and access information for client meeting preparation.

•       AI Integration: Utilize GenAI Technologies to enhance the system's capabilities, such as natural language processing for analyzing meeting notes and predictive analytics for generating insights.

•       Data Analysis: Implement AI models to analyze data inputs and generate valuable insights, such as identifying patterns in client feedback or predicting potential document deficiencies.

•       Meeting Preparation Pack: Consolidate all relevant information, including to-do lists, insights, follow-ups, document deficiencies, reviews, and areas requiring client feedback, into a comprehensive meeting preparation pack.

Project Coordinator: Bryan Lee Cheng Hui

Project Mentor: Amila Silva

Project #3

FY2024/25
Term 2

OCBC - Group Operations & Technology

This project aims to explore the concept of Zero-Knowledge Rollups, an innovative technology that addresses two significant challenges in blockchain transactions: privacy and efficiency. In simpler terms, Zero-Knowledge Rollups are like a secret code that allows you to do more things securely and quickly without anyone

else knowing the details.

In the world of digital currencies and blockchain, it's crucial to ensure that transactions are both private and efficient. Zero-Knowledge Rollups offer a promising solution by bundling many transactions together and proving they are valid without revealing specific details about each individual transaction.

This approach enables blockchain networks to handle a large number of transactions at once, making them faster and more scalable. This also prove that transactions are valid without exposing the specifics. As a practical demonstration, we are able to develop blockchain applications such as:

1.    Enhancing Privacy and Scalability in Blockchain Transactions using Zero-Knowledge Rollups

There is a need for an improved solution to address the privacy and scalability challenges facing blockchain transactions. Traditional blockchain systems, such as those used in cryptocurrencies, often struggle to handle a high volume of transactions while simultaneously ensuring the privacy of participants.

Existing blockchain architectures suffer from limited scalability, resulting in congestion and increased transaction delay during peak usage periods. Moreover, transaction details are often visible to malicious actors, compromising user privacy and confidentiality.

Project Inputs:

•       Project sponsors will share sufficient context so students can understand its use cases, discussing the benefits and limitations of implementing zero knowledge rollups and how it can benefit end users.

•       The project details, explanation of the zero knowledge rollups and other useful details will be shared.

Project Deliverables:

•       Students will dive into the technical aspects of Zero-Knowledge proofs, learn about the challenges of implementing Rollup solutions, and examine real-world examples where this technology has been used successfully

•       Investigate where zero knowledge rollups can be applied in banking environment. Students will study relevant academic resources, examine existing Zero-Knowledge Rollup implementations

•       Create simulations or proof-of-concept prototypes to explore the practical aspects

 

Project Coordinator: Ravindra Kumar

Project Mentor: Jorden Seet

Project #4

FY2024/25
Term 2

Fulfills BA

Citi - Exchange Traded & Cleared Derivatives

Collateral Optimization for CCP Margin Calls

Citi provides its clients with clearing services on several global Central Counterparty Clearing Houses (CCPs). Clients can post eligible currency (cash) & financial instruments (bonds, treasury notes, securities, commodity warrants, etc.) as collateral to cover margin calls. Citi, as a clearing member, will then utilize some of these assets to cover the corresponding margin calls with the CCP.

Each CCP has specific requirements regarding the types of collateral it accepts, applying different haircuts and collateral fees based on asset class. Additionally, transaction costs are incurred when depositing, substituting or withdrawing collateral. Optimizing the allocation of available collateral across different CCPs can minimize costs and increase efficiency.

This project aims to develop an algorithm that optimizes the allocation of available collateral to various CCPs based on eligibility, collateral costs, haircuts, and transaction costs, taking into account frequent changes in available collateral due to client activity.

Citi’s clearing services require optimal collateral allocation to different CCPs in order to minimize costs and comply with eligibility requirements. The current process involves multiple variables such as collateral eligibility, haircut rates, collateral fees, and transaction costs. The objective of this project is to build a solution that optimizes collateral allocation for margin calls at each CCP while minimizing associated costs and fees.

Project Inputs:

Students will be provided with:

1. A file containing a list of available collateral.

2. A file that lists the margin calls required at each CCP.

3. A file containing static data regarding eligible

associated haircut rates, fees, and transaction costs at different CCPs.

All required data is in public domain. No Citi proprietary data is required nor will be shared for this project.

Project Deliverables:

1. Optimization Algorithm: A solution to optimize the allocation of available collateral across multiple CCPs based on eligibility, costs, and transaction considerations.

2. User Interface: A basic user interface to input data and visualize the optimized collateral allocation across CCPs.

3. Collateral Movement Report: A user report that lists the optimal collateral allocation and the related asset movements.

4. Documentation: Detailed documentation explaining the methodology, logic behind the optimization algorithm, and any assumptions made.

5. Presentation: A final presentation demonstrating the optimization tool, its functionality, and potential real-world applications for Citi's operations.

Project Coordinator: TBA

Project Mentor: Nirav Parikh

Project #5

FY2024/25
Term 2

Citi - Markets & Trading

Synthetic Market Generator for Algorithmic Trading

One of the key challenges in training trading algorithms is the limited availability of real-world historical data specific to certain securities. This scarcity of data can lead to overfitting and suboptimal performance in machine learning models. Moreover, it is difficult to find data that accurately reflects specific market conditions, including varying volumes, trends, and volatility levels.

This project aims to address these challenges by developing a synthetic market simulator capable of generating market data tailored to specific securities and market conditions. The simulator will be parameterized to model various patterns, volatility levels, and market trends, providing a flexible tool for creating synthetic datasets. These datasets can then be used for training and testing algorithmic trading strategies, avoiding the pitfalls of limited real-world data.

Current trading models face the challenge of limited historical data for specific securities and market conditions. This project seeks to build a synthetic market data simulator that allows traders and researchers to generate customized market data based on chosen parameters such as volatility, trend strength, and volume. This will provide a larger and more diverse dataset to train trading algorithms, leading to better generalization and performance in various market environments.

Project Inputs:

Students will be provided with:

1. A representative set of market data for a given security (historical OHLCV data).

2. Parameters to tune the synthetic data generation, including market patterns, volatility, trends, and volume.

All required data is in public domain. No Citi proprietary data is required nor will be shared for this project.

Project Deliverables:

1. Synthetic Data Generator: A working model that simulates and outputs synthetic market data based on input parameters.

2. Parameterization: A set of controls to modify the synthetic data generation, including trend types, volatility levels, and other key market conditions.

3. Transaction Output: The output will be a file containing the generated market data, with fields such as Open, High, Low, Close, and Volume (OHLCV).

4. Documentation: Detailed documentation explaining how the synthetic data is generated, how to use the parameterization tools, and how the simulator can be applied in algorithm training.

5. Presentation: A demonstration of the synthetic market simulator, including use cases for improving trading algorithm performance.

Project Coordinator: TBA

Project Mentor: Nirav Parikh

Project #6

FY2024/25
Term 2

Citi -  Investment Banking

Deal Review Committee Using LLM Agents

In investment banking, evaluating deals for new clients involves multiple dimensions of analysis. Banks must assess the market potential, competitive positioning, and risk profile of a client’s business, while estimating revenue and cost projections. Additionally, ensuring compliance with regulatory standards and aligning deals with the bank’s strategic objectives are crucial aspects of decision-making.

This project proposes the development of a framework utilizing Large Language Model (LLM) agents to simulate a virtual committee of financial experts. Each LLM agent will be specialized in specific areas such as risk assessment (credit, market, operational, regulatory, reputational), revenue estimation, compliance, and strategic alignment. By simulating the expertise of real-world financial analysts and risk managers, this system will provide a comprehensive review of deal proposals for new clients.

The goal is to enhance decision-making, mitigate risks, ensure regulatory compliance, and foster profitable client relationships, helping banks balance opportunity with risk for long-term sustainability and growth.

Investment banks face challenges in evaluating deal proposals due to the need for multi-faceted analysis across revenue potential, risk assessment, regulatory compliance, and strategic fit. This project aims to develop a framework leveraging LLM agents to provide a holistic and expert-driven approach to deal review, improving both the efficiency and accuracy of decision- making processes.

Project Inputs:

Students will be provided with:

1. Training data from previous deal reviews, including analysis from financial analysts and risk managers.

2. Access to relevant market data, risk factors, and financial models.

3. Strategic guidelines and risk appetite documentation for new deals.

Note: Anonymized Citi internal data (no client data) will be required for this project subject to approvals and potential NDA agreements.

Project Deliverables:

1. LLM-Based Expert Agents: A framework of specialized LLM agents trained to simulate expert perspectives in areas such as revenue estimation, risk analysis, compliance, and strategic alignment.

2. Virtual Committee Decision Process: A mechanism for synthesizing the insights from different agents to form a comprehensive recommendation on deal approval and conditions.

3. Decision Support System: A tool that provides deal recommendations, approval conditions, and risk mitigation strategies based on the committee’s output.

4. Documentation: Comprehensive documentation outlining the design, methodology, and decision-making process of the virtual committee of LLM agents.

5. Presentation: A final presentation showcasing the framework, its decision-making process, and its potential impact on the bank's deal review process.

Project Coordinator: TBA

Project Mentor: Nirav Parikh

Project #7

FY2024/25
Term 2

Fulfills BA

Revolut - Digital Investing

Bespoke Robo Advisory Platform for Retail Users

Create a digital investment platform that allows users to invest into through Revolut’s Robo-advisory solution coupled with the Users own inputs relating to Risk Appetite, preferred asset class mix, single name stocks and investment amount.

The ask is to create a web app that:

•       Allows users to include more inputs before letting Robo advisory take over the investment of users funds.

•       List of investment instruments and asset classes available

•       Visualize the performance data using charts, tables etc. in a simple, uncluttered fashion.

Robo-advisory is a useful solution / tool for beginning and intermediate investors who wise to utilize ”Robos” to optimize users funds and invest accordingly based on black box algorithms built by the Robo Advisory company.

The Problem is that users have little or no say in which specific asset class, industries, or single name stocks should the investor have a preference in whilst offering the investor expertise of the Robo Advisory perform dynamic asset re-allocation as and when the need to do arises.

So the idea is to create a platform which is a hybrid of a Robo-Advisor and a full manual trading platform

Project Inputs:

•       Project sponsors will share sufficient context so students can understand how/where this platform brings value to users.

•       The mock raw data files, explanation of this data structure and other useful details will be available.

Project Deliverables:

•       Working App that provides intuitive UI/UX.

•       This App should be a standalone application that can be easily incorporated in a larger application. Freedom to use visualization & analysis tools, technology of the team’s choice.

 

Project Coordinator: [ TBA ]

 

Project Mentor: Abhinav Suryavanshi

Project #8 FY2024/25

Term 2

Fulfills BA

Singapura Finance -Regulatory Compliance

Customer Profiling Application

Customers are on-boarded to the bank’s system after performing checks and validation for know your customer and anti-money laundering (KYC/AML) compliance.

The solution should extract information about existing customers, run checks and document results. It will score each customer based on given parameters. The parameters may change over time, so flexibility to adjust the parameter will be required.

The current approach to handling AML scoring and documenting of customer profile is manually done by staff. It is not consistent and prone to oversight and missing filed information.

Project Inputs:

•       Project sponsors will share context so students can understand how/where this digitalization can add value to the organization.

•       The mock up data and parameter for scoring will be shared with explanation on the digital filing requirements.

•       Potential to use ML Tools to profile customer

Project Deliverables:

A solution or program which can accomplish the following:

•       Take in a customer information from the banking system

•       Profile the customer information using available search/information engine/service provider. Obtain the results

•       Provide data visualization of the results obtained

•       Score each customer  profile

•       Store the results for historical review or audit review requirement.

•       Allow customization of the scoring

•       Easy search and identification of customer profile documents collated.

•       Allow for triggering of review on customer information based on score

Project Coordinator: (TBA)

Project Mentor: Winny Ho

Project #9

FY2024/25
Term 2

Fulfills BA

Singapura Finance - Risk Management

 

Consumer Loans Credit Scoring

The bank implemented an online straight through loan application (Mortgage) using government provided information, with customers consent.

The system does not identify nor prioritize customer profile, hence good/great customers are left together with the majority.

Solution will use information obtained by the government data source and generate a credit score each application. An application may have more than one submission (Multiple owners).

The solution should provide automated recommendation for improved loan rates for of better scoring customers. It should also document and recommend follow-up for lower scoring applications.

 

Project Inputs:

•       Project sponsors will share context so students can understand how/where this digitalization can add value to the organization.

•       The mock up data and parameter for scoring will be shared with explanation on the digital filing requirements.

Project Deliverables:

An app that provides the following:

•       Take in a customer information submitted via online forms/government data.

•       Profile the customer information

•       Analyze the results obtained and score each application

•       Allow customization of the scoring using various data points available.

•      Provide data visualization of the results obtained

•       Results will be sent to back-room for processing or automated escalated actions.

Project Coordinator: (TBA)

Project Mentor: Cindy Ng

Project #10

FY2024/25
Term 2

Tiger Fund - Fund Management

Using Artificial Intelligence for Effective Stock Screening

This project focuses on using artificial intelligence (AI) to develop an effective stock screening tool that assists investors in identifying potential buying or selling opportunities in the U.S. stock market.

With the vast amount of data generated daily, AI can automate the screening process by quickly analyzing stock trends, sector performance, and user-defined parameters to detect valuable market opportunities.

The system will leverage machine learning algorithms and technical indicators to filter stocks based on investor preferences, such as undervaluation, technical patterns, or strong market trends.

The goal is to streamline stock selection and improve decision-making efficiency for portfolio managers.

Investors face a challenge in sorting through the immense quantity of stock market data to identify opportunities for profitable trading. The manual stock screening process is time-consuming and prone to human error, especially when considering various technical indicators and market conditions.

This project aims to address these issues by developing an AI-powered stock screening system capable of efficiently analyzing stock data, detecting strong market trends, and automating the identification of potential buying or selling opportunities based on predefined criteria.

 Project Inputs:

•       Project sponsors will share sufficient context so students can understand how/where this project brings value to users.

Project Deliverables:

•       AI-Powered Stock Screener Application: A functional application that can analyze large datasets and apply user-defined parameters to screen stocks.

•       Backtesting: To engage in backtesting of the model in order to ensure the reliability of the system

•       Market Trend Detection Module: A feature that detects strong market trends or significant changes in sector performance.

•       Sector Analysis Tool: A tool to conduct in-depth analysis of sectors to identify potential opportunities for buying recommendations.

•       Sentiment Analysis Engine: A system that scrapes and analyzes sentiment data from news articles, social media, and financial reports, and integrates it into the model.

•       User Interface for Stock Screening: An interactive interface where users can input their screening criteria and view stock recommendations in real-time.

Project Coordinator: [TBA]

Project Mentor: [TBA]

Project #11

FY2024/25
Term 2

Fulfills BA

Tiger Fund - Fund Management

Using Artificial Intelligence to Time the Market

The project aims to build a machine learning-based system that assists portfolio managers with accurate market timing by predicting the prices of major Exchange-Traded Funds (ETFs) such as SPY (S&P 500 ETF) and TLT (Treasury Bond ETF).

The core component of this system will be an AI model, potentially using a Long Short-Term Memory (LSTM) neural network, which will predict future prices based on a blend of economic, fundamental, sentiment, and technical data.

The model will be designed to continuously learn and adapt to evolving financial environments, making real-time predictions.

The data inputs will be aggregated from reliable financial sources like FRED, World Bank, Yahoo Finance, and sentiment analysis from news outlets, social media, and financial reports to develop a comprehensive model.

Accurate market timing is one of the most challenging tasks for portfolio managers. Market prices fluctuate based on a wide range of factors, including economic indicators, fundamental analysis, market sentiment, and technical trends. Traditional financial models often fail to capture the complexity and rapid changes in market dynamics. This project seeks to bridge the gap by leveraging machine learning to forecast ETF prices more accurately and continuously adapt to changing market conditions.

Project Inputs:

•       Project sponsors will share sufficient context so students can understand how/where this project brings value to users.

Project Deliverables:

•       AI Prediction Model: A machine learning model trained to predict the prices of SPY and TLT based on technical, economic, fundamental, and sentiment data. An AI system capable of retraining itself as new data becomes available, allowing for adaptation to market changes.

•       Backtesting: To engage in backtesting of the model in order to ensure the reliability of the system

•       Sentiment Analysis Engine: A system that scrapes and analyzes sentiment data from news articles, social media, and financial reports, and integrates it into the model.

•       Risk Appetite Indicator: A composite indicator driven by sentiment analysis, measuring market risk aversion or appetite to inform predictions.

•       Data Pipeline: Web scraping and integration pipeline to pull continuous data from FRED, World Bank, Yahoo Finance, and other relevant sources.

•       Dashboard Interface: A user-friendly dashboard to display model predictions, risk appetite indicators, and relevant metrics.

Project Coordinator: [TBA]

Project Mentor: [TBA]

Project #12

FY2024/25
Term 2

Fulfills BA

UBS -  Equities

News Screener For Relevant Investment Opportunities

Bankers and Investment counselors (ICs) develop deep relationships with clients and provide them with relevant investment and opportunities advices based on client’s needs.

The ask is to create a tool that:
Scans publicly available social media and news sources for news about relevant sector’s or region’s current and ongoing events and their co-related relevant companies or entities.

Summarize these views to a digestible format for Client Advisor, Ensure each data point has a source link, that would enable the Client Advisor to verify that the subject is indeed relevant to preferences of their client.

Freedom to use visualization & analysis tools, generative AI, APIs and technology of the team’s choice. However the solution should be hosted in an Azure Cloud.

Example: Tools scans news from the ‘Financial Times’ for relevant sector ‘Real Estate’ and region ‘China’, Based on the news coverage, it identifies the current market trend and effected companies and instruments relevant to those companies and provides a relevant view to client advisors.

Given current volatile world and lots of information being generated every moment, analysts require smart intelligent tools to sort through all those and provide clients with relevant investment advices on timely manner. The tool is to automated way to scan news, provide digest about the news in categories like sector, region and entity. Also to provide relevant  sentiment of the news.

Project Inputs:

•       Project sponsors will provide 5 entity names, and suggested data sources on which the output should be created

•       Project Sponsors will review at regular intervals the outputs to refine requirements and usability of output.

•       We will provide support on how to perform identity matching for the entities.

•       Team can use AI tools to discover digest of news (e.g. news is about ‘Real Estate’ sector.)

Project Deliverables:

•       Working dashboard that provides a real view of relevant sectors and entities.

•       View provides contextual correlated sentiment assessment of entities.

•       View provides trigger notifications when significant activity threshold is breached (optional).

•       View provides collected historical information and perform system end to end risk and returns on entities.

•       Ability to collect data from different sources.

 

Project Coordinator: Kumar, Ajith-A

Project Mentor: Hossain, Mohammad-Jahangir

Project #13

FY2024/25
Term 2

UBS -  Mobile banking

Modern web application and Native Mobile application for

Portfolio viewing of a banking customer

There are already a quite a lot of Banking asset viewing and portfolio viewing apps in the market currently. Having a great user experience for such apps are key for success of any business. User experience is garnered from Customer experience strategy, research and design. Understanding user behavior and human computer interaction techniques are key in designing and implementing next gen user experience application is key.

In this project you will produce native iOS/Android mobile application and web application using latest technology which inculcates great customer experience design , user experience design and wireframes. There are already great deal of research materials on this subject, so need a both balanced academic view and already existing app view to come out with a great application to do portfolio viewing of a Banking clients assets. The backend may have mock data to begin with so not really expecting the app to work end to end. Key success criteria are to have a great visual and customer experience for these apps.

This project aims to develop a banking portfolio viewing application which targets the upcoming generation of banking application consumers, ie. Gen Z and Millennials. Additionally, we will enhance the user experience of our application by implementing specific design considerations obtained through rigorous user research and analysis of human-computer interactions.

Project Inputs:

•       Technology services mentor will provide insights on deep knowledge on the subject

•       Help students to formulate the solution ideation

•       Provide the expertise where necessary for the group to produce a industry standard solution

Project Deliverables:

Must Have:

•       Working Mobile application for asset viewing targeted at Gen-Z age group

•       Design and develop a prototype which has a high customer experience design and HCI.

Nice To Have:

•       Fully working backend is not a requirement. Application can have a static data to power the application.

 

Project Coordinator: Kumar, Ajith-A Project Mentors: Sanghavi,

Seema

Project #14

FY2024/25
Term 2

UBS -  Regulatory Compliance

FinRegScanner

Banks have to adhere to multiple market and exchange related financial regulations. The compliance function has to be vigilant in identifying the regulations that are published by various countries, regions and by industry bodies and implement them on time. If a bank is not regulatory compliant, that could lead to various repercussions from financial penalties, reputational impact to even posing a risk to the financial system as a whole.

Once a regulation is identified, few companies look out for vendor solutions and few companies build solutions in-house and this often requires a lot of coordination among various functions/teams to ensure that the regulation gets adhered to on time.

Hence, it would great if technology can help to assist and simplify the regulatory project management and implementation.

Right from identification of a financial regulation that the bank needs to adhere to, till the implementation, is very complex to manage, time intensive and costly affair.

Build a solution that can act as an assistive tool to Compliance function of an organization to help detect, plan and manage regulatory impacts in a timely manner within the organization.

Project Inputs:

•       Project Sponsors will provide information about regulatory data sources and will also give a brief overview of Financial Regulatory Landscape and relevant support wherever required

•       Project Sponsors will review the output at regular intervals to provide feedback and to refine requirements

Project Deliverables:

Must Have:

1)    Identify upcoming regs and their regulatory deadline

2)    Summarize the requirements for each impacted business division and able to query the regulatory text and get answers

3)    Apply a chatbot feature to query the QnA

4)    Provide a dashboard to visualize the key features of the regulations.

Nice To Have:

1)    Build a machine learning model to classify the regulation, identify the potential impacts for each business division

2)    Provide a comparison with other regulations of similar nature

 

Project Coordinator: Kumar, Ajith-A

Project Mentors: Kumar, Phanindra; Kumar, Ajith-A

Project #15

FY2024/25
Term 2

UBS -  Wealth Management

Gamified Financial Literacy Application

Financial Literacy is essential in wealth management as it enables individuals to make informed decisions about growing, protecting and preserving their assets.

The ask is to create a gamified financial literacy app that teaches essential money management skills through interactive challenges, quizzes, activities, simulations and make financial education engaging and fun for all ages. Users earn badges and unlock new levels as they progress through next stages in their learning paths consisting of topics ranging from time value of money, insurance, emergency fund, asset allocation, budgeting, saving, investing etc.

Financial Literacy is essential in wealth management as it enables individuals to make informed decisions about growing, protecting and preserving their assets.

The ask is to create a gamified financial literacy app that teaches essential money management skills through interactive challenges, quizzes, activities, simulations and make financial education engaging and fun for all ages. Users earn badges and unlock new levels as they progress through next stages in their learning paths consisting of topics ranging from time value of money, insurance, emergency fund, asset allocation, budgeting, saving, investing etc.

Project Inputs:

•       Project sponsors will share sufficient information regarding the various aspects of personal finance

•       Mentors will guide the students on building learning paths and scenario simulations

•       Mentors will review the progress at regular intervals to refine requirements and usability of the app.

Project Deliverables:

Must Have:

•       Fully functional responsive / mobile native application with at least 2-3 financial literacy learning paths.

•       Excellent user experience with security features implemented.

•       Real time analytics to track progress with personalized insights and badges

•       Admin dashboard showing the learning progress, and the badges earned by all the users.

Nice To Have:

•       Integration with ChatGPT or other LLMs for personal finance scenario simulations

Project Coordinator: Kumar, Ajith-A

Project Mentors: Gopalan Ramakrishnan

Archived Past Projects and Groups

AY2024/25 Term 1
https://docs.google.com/spreadsheets/d/1IDAhC4JiK3RuKnIDQMG5UjJ6I1IiImo81Lu13wAuUxE/edit#gid=491663198

Past Project Descriptions
https://docs.google.com/spreadsheets/d/1f7r2y1n6USWAYVTVyWkZkYxJt7HCoxlc-z3jAGzX7LQ/edit?gid=0#gid=0