IS484 IS Project Experience (FinTech)
Course Description:
- This is an SMU-X course designed in collaboration with CitiVentures Innovation Lab. Citibank will supply a minimum of 5 projects ideas to select from.
- Students will form teams of 5 or 6, and select one of the Citibank 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 Citibank sponsor and an SMU faculty supervisor.
- Citibank 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 Citibank sponsor.
- Citibank will specify the technologies to be used, including; development tools/languages, OS, database, 3rd party libraries, target deployment environment e.g. cloud environment.
Project Timeline:
- Week 1 - Attend orientation session, where teams will be formed (if you have not already formed a team), and projects are selected from a set of predefined projects provided by CitiVentures.
- Week 8 - Midterm presentation and demo
- Week 15 - Final presentation and demo
Project deliverable:
- Student project teams will be expected to develop a working software application prototype, to be delivered to Citibank at the end of the course.
- A formal, in-person midterm and final presentation will be facilitated by Citibank.
Citibank Projects
- Projects to be selected/assigned to project teams during Week 1 orientation session.
| Item | Project Description | Project Deliverables | Project Sponsor |
|---|---|---|---|
| 1 | Microservices Architecture in Banking - In recent years, there is much written about microservices architecture. Even so, there is very little written about how microservices are used in the banking industry. A study is needed to understand microservices implementation in banking. Faculty Advisor: Prof Alan Megargel |
Research Question 1: How do banks decide on the boundary context and granularity of microservices? Research Question 2: What kind of tool sets do banks use for building, testing, and deploying microservices? |
Research Method: Data collection through surveys and interviews of bank staff, and existing case studies. Analysis of qualitative and quantitative data collected. Results and Conclusions. Integrated Report: Write up an integrated report covering all 3 research questions. |
| 2 | Data Replication Across Microservice Instances - In a microservices architecture, as the demand (# of invocations) for a microservice increases, management tools elastically create replicated instances of the microservice. A study is needed to understand mechanisms for replicating the data underlying multiple instances of a microservice. Faculty Advisor: Prof Alan Megargel |
Research Question 1: Can an in-memory-data-grid be used instead of a relational database, underlying replicated instances of a microservice? What is the feasibility of each, in a banking context? Research Question 2: What are the performance characteristics (eg; response time, replication time) of an in-memory-data-grid as compare to a relational database, as invoked across microservice instances? |
Research Method: Develop a microservice (banking context) which requires transaction management. Configure a microservice management tool to replicate instances of the microservice. Load test instances of the microservice across heavy loads, to generate data, for; a) in-memory-data-grid, and b) relational database. Analysis of the data generated from load testing. Results and Conclusions. Integrated Report: Write up an integrated report covering all 3 research questions. Relate each question within a banking context. |
| 3 | Maintaining Data Privacy Across Connected Blockchains - With an increasing number of commercial private blockchains being used on different platforms there is a problem on how to connect the blockchains and maintain data privacy. Faculty Advisor: Prof Paul Griffen |
Research Question 1: How can current homogeneous blockchain interoperability platforms such as PolkaDot maintain data privacy be expanded for heterogeneous blockchain interoperability? Research Question 2: What are the key features for designing a heterogeneous blockchain interoperability platform? |
Research Method: Review current homogeneous blockchain interoperability platforms such as PolkaDot. Interview industry partners (OneConnect) for the key features necessary for a heterogeneous blockchain interoperability platform. Analyze the gaps in the homogeneous blockchain interoperability platforms for the business needs for heterogeneous blockchain interoperability platform and propose a data exchange protocol. Results and Conclusions. Integrated Report: Write up an integrated report covering all 3 research questions. |
| 4 | Comparing Decentralized Exchange (DEX) Protocols - With an increasing complexity in crypto-token exchanges as well as continuing security issues in centralised exchanges, there is a need to robustly compare decentralised exchange (DEX) protocols. Continuing on from a previous IS470 project (final report available on request) comparing 0x and Khyber, these and other DEX protocols can be investigated according to the DEX comparison framework in collaboration with the industry partner ICHX. Faculty Advisor: Prof Paul Griffen |
Research Question 1: Which DEX protocol is the best fit for the business requirements of ICHX and why? Research Question 2: What are the shortcoming of the DEX protocols? |
Research Method: Interview and review the business requirements of ICHX. Analysis the pros and cons of the DEX protocols against the business requirements using the comparison framework. Results and Conclusions. Integrated Report: Write up an integrated report covering all 3 research questions. |
| 5 | Quantum Computers for Consensus Algorithms - Blockchain consensus mechanism has limitation in speed, security and range. Quantum computers are now available that can be used to show potential improvements for blockchain consensus. This project is to continue work from an IS470 (final report available on request) and further explore the proof-of-concept developed on the IBM Q quantum computers using Qskit. In particular the apparent sensitivity of the quantum algorithm to non-consensus could be highly useful and can be characterised further. Faculty Advisor: Prof Paul Griffen |
Research Question 1: What is the form of the behaviour of the sensitivity of the quantum algorithm to non-consensus? Research Question 2: Is there a full implementation of a quantum AND gate in any available quantum computer? |
Research Method: Execute the quantum code with varying non-coherence levels. Analysis the quantum algorithm data to characterise the sensitivity to non-coherence. Review industry needs for consensus sensitivity. Results and Conclusions. Integrated Report: Write up an integrated report covering all 3 research questions. |
