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Difference between revisions of "IS480 Team wiki: 2013T1 Kungfu Panda X-Factor"

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===Teaching tool process flow===
 
===Teaching tool process flow===
 
[[Image:KP-TTProcessFlow.PNG|547x239px]]<br/><br/>
 
[[Image:KP-TTProcessFlow.PNG|547x239px]]<br/><br/>
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===Demographic Information for Generating Teaching Tool Loan Profiles===
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We retrieved our demographic information from various sources. When presented with alternative sources, we chose the source which was more reliable (e.g. from an authority such as the Government).
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<br/>
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The demographics are modeled after the Singapore population whenever possible.
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<br/>
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'''Income: '''
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* Median of $41760
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* Typically ranges between $12, 240 to $300,000 a year
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* Sources:  http://stats.mom.gov.sg/iMAS_PdfLibrary/mrsd-msib2013.pdf, http://www.mom.gov.sg/Publications/mrsd_singapore_workforce_2012.pdf
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'''Residence: '''
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* Home ownership rate of 90.1%
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* Source: http://stats.mom.gov.sg/iMAS_PdfLibrary/mrsd-msib2013.pdf
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''''Residence Stability:'''
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* Average of  6 years (according to US survey as there was limited SG information)
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* Source: http://www.creditsesame.com/blog/how-long-are-americans-staying-in-their-homes/
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'''Job Stability: '''
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* Median: 4.4 years (US survey)
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* Source: http://www.forbes.com/sites/jeannemeister/2012/08/14/job-hopping-is-the-new-normal-for-millennials-three-ways-to-prevent-a-human-resource-nightmare/
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'''No of Credit Cards'''
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* Median of 3.3 cards per individual
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* 75% of eligible cardholders have 2 or more cards
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* Source: http://sg.finance.yahoo.com/news/singapore-top-asia-credit-cards-105414790.html
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'''Credit and Banking History'''
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* 1.85% derogatory records on average
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* Source: http://www.btinvest.com.sg/system/assets/16730/Moody's%20-%20Banking%20System%20Outlook%20-%20Singapore%20071513.pdf
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'''Loan Quantum (HDB Flat)'''
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* Ranges from $320,000 to $820,000
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* Average 3 room HDB, $355,444
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* Average 4 room HDB, $490,352
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* Average 5 room HDB, $563,427
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* Source: http://www.hdb.gov.sg/fi10/fi10321p.nsf/w/BuyResaleFlatMedianResalePrices?OpenDocument
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'''Age'''
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* Source: http://www.singstat.gov.sg/statistics/browse_by_theme/population.html
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* Normalized for average loan takers
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**25 - 54 years (74.1%)
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**55-64 years (14.4%)
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** 65 years and > (11.5%)
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===Teaching tool Features (Input)===
 
===Teaching tool Features (Input)===
 
[[Image:KP-TTFeatures.PNG|492x201px]]<br/><br/>
 
[[Image:KP-TTFeatures.PNG|492x201px]]<br/><br/>

Revision as of 15:30, 24 November 2013

KP-NewHeader.PNG
Home About Us Project Overview Project Management User Testing Project Documents


SMU tBank Our Project Scope Our X-Factor Technologies

X-Factor Component

KP-XFactor.PNG




Credit Approval


The Credit scoring engine is a complex decision service that performs automatic credit evaluation and approval for mass consumer products such as Home Loans, Auto Loans, and Education Loans.
KP-CA.PNG

Credit scoring Process Flow

KP-CSProcessScore.PNG

Credit approval process diagram

KP-CAProcessDiagram.PNG


Credit Decision Engine Proof of Concept
POC for Credit Decision Engine

Market Research of Credit Engines

FICO Website: FICO Scoring Overview

FICO is a leading company in predictive analytics, specialising in scoring individual's credit-worthiness over a scale of 800 points. Our group used FICO's scoring model as our main reference when developing the rules for our Credit Engine.


Kp-fico overview.png

Examples

FICO's calculation based on Length of Credit History



FICO Types of Credit Used



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Mockup of Credit Approval Form

Credit Approval Form Mockup v2.png

Teaching Tool


The teaching tool allows users to perform modeling and simulations across varying customer profiles (credit capacity) in order to optimize the the rules of the scoring engine for a particular customer profile.


KP-TT.PNG

Teaching tool process flow

KP-TTProcessFlow.PNG

Demographic Information for Generating Teaching Tool Loan Profiles

We retrieved our demographic information from various sources. When presented with alternative sources, we chose the source which was more reliable (e.g. from an authority such as the Government).
The demographics are modeled after the Singapore population whenever possible.
Income:

Residence:

'Residence Stability:

Job Stability:

No of Credit Cards

Credit and Banking History

Loan Quantum (HDB Flat)

Age


Teaching tool Features (Input)

KP-TTFeatures.PNG

Teaching tool Features (Output)

KP-TTFeatures2.PNG

Teaching Tool Mock Up

Teaching Tool Data Generation

KP-TeachingToolMockup1-1.PNG

Teaching Tool Rule Customization

KP-TeachingToolMockup2-1.PNG

Teaching Tool Summary of Results (Output)

KP-TeachingToolMockup3-1.PNG KP-TeachingTool DisplayRessult2.png