7/27/2019 Gmid Associates- SME Loan Portfolio Review
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Case Study | Gmid Associates
www.thegmid.com
[email protected] | +91 020 4239596
Secured/ Unsecured SME Loan Portfolio: Asset
Valuation, Stress Testing and Lifetime Loss Forecast
Objective
Our client, one of Indias premier financial services conglomerates, had a growing and
profitable SME loan portfolio (both secured and unsecured). After three years o
cautious growth since inception- putting policies, procedures and best practices in
place; the management decided they had a solid platform to go for a steep growth
curve. With this context, they wanted an end to end review of portfolio credit quality
with the following objectives-
Credit quality review with respect to future default behavior and
recommendations for quality improvement.
Portfolio Stress Test Simulator to preempt the effect that macroeconomic stress
scenarios would have The stress scenarios were-
1. GDP Growth Slowdown,
2. Tougher Access to Finance.
Lifetime loss Prediction of the existing portfolio.
Methodology
Merged all the business datasets- application data (profile, demographics, financia
history of business and promoters etc.), transactional details (payment/ delinquency/
cheque bounce details), product information and other relevant information sources
(top-up/ cross-sell etc.) to compile a single view dataset so that each account had a
single unique record with all the information related to it.
CASE STUDY
7/27/2019 Gmid Associates- SME Loan Portfolio Review
2/2
Secured/ Unsecured SME Loan Portfolio: Asset Valuation, Stress Tesing and Loss forecasts
Case Study | Gmid Associates
www.thegmid.com| +91 0120 4239596
Conducted data mining analyses (clustering, segmentation, KDA etc.) to identify trends
and patterns in the loss making accounts, if any. Identified pockets of portfolio that
were significantly riskier than others.
Based on historical default data, developed a behavioral scorecard for default prediction
on active portfolio. Developed a survival model to predict lifetime at account levelCombined these two models for the lifetime loss forecast.
Basis various portfolio performance analyses, it was found that monthly portfolio
performance had a great correlation to account vintage and some macroeconomic
parameters. Devised a statistical relationship to correlate portfolio performance
(nonpayment behavior) with macroeconomic changes and built this into an easy to use
parameterized Macro enabled MS Excel tool. The tool was to be used by the CEOs
office and they wanted an easy to use and parameterized tool.
Shared a detailed report regarding portfolio leakages, distress trends and
recommendations, Life Time Loss Forecast results along with stress testing tool.
Impact
Management used the inputs to tighten leakages in credit policy, identify areas (i.e
regions/ industries) and parameter cut-offs which were the source of risky acquisitions
This helped the company to solidify the credit foundation and then go for aggressive
expansion while making sure portfolio quality doesnt go down.
The company was able to increase the monthly portfolio growth rates by 50% and at thesame time reduce the default rates (which were already pretty good) by over 10%.
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