April 20, 2012 New Delhi

1. Presentation to National Housing Bank Risk Scoring and Risk Based Pricing of Home Loans ICRA Management Consulting Services Limited April 20, 2012 New Delhi

2. Risk based pricing enables better risk management Risk Identification A rating model or scorecard will discriminate good and bad borrowers Identify risks in the property (collateral) Risk Measurement Estimate credit losses through models Compute credit risk premium from risk grading Risk Mitigation Manage anticipated credit losses by provisioning and risk based pricing Maintain capital to absorb adverse losses

3. Credit losses can be divided into expected loss and unexpected loss Losses Unexpected Loss Expected loss Year Frequency Credit Loss Expected Loss Average loss in the course of business Managed by pricing and provisions Unexpected Loss Peak losses in excess of expected loss Managed with capital cushion

4. Expected loss is the average loss anticipated in the course of business • Forecast of average level of credit losses a firm reasonably expects to experience in a year • One of the cost components of doing business • Managed by pricing and provisioning • For e.g. • On an average, out of 100 AA borrowers, two of them default at the end of a normal business year • On an average 10% is the loss in the realisation of the asset • Rating model or scorecard will help estimate expected loss scientifically Expected Loss = Probability of Default * Loss Given Default

5. Unexpected loss is a peak loss that exceeds expected loss • Peak losses do not occur every year but can potentially be very large • Capital acts a cushion to absorb unexpected losses • Losses can exceed expected losses due to reasons like • Economic slowdown, higher interest rates leading to more defaults • Correction in property prices leading to negative equity Capital required = Exposure * Risk Weight Risk weight is based on loan amount and LTV

6. Risk based pricing Risk-based pricing The cross-subsidy 1 Good credits overpriced Subsidy 2 Typical Pricing Interest Rate 2 Bad risks under-priced 1 Risk Low High • Good accounts subsidize poor credit risk accounts • Risk based pricing can mitigate problem of adverse selection

7. Risk Adjusted Return on Capital Employed Capital Required (regulatory) / Employed (economic)

8. Cost heads considered in pricing… as % of exposure Cost of Funds Cost of borrowing Direct and Indirect Costs • Loan origination and servicing cost • + • Other overheads Provisions • Maximum of • Existing provisions apportioned • Expected loss computed as • PD * LGD * Exposure • Hurdle rate based on RoE • * • Regulatory capital Opportunity Cost of Regulatory Capital

9. Risk based pricing – an example 12.00% 0.90% 0.10% 10.90% 0.50% 1.00% 10.00% 8.50% 8.00% 6.00% 4.00% 2.00% 0.00% Cost of funds Overhead Credit risk Cost of Processing Lending rate cost premium capital fee

10. Credit risk premium depends on the rating of the borrower Assumptions *LGD is assumed as 10% as per Basel guidelines Processing fee is amortised over 10 years

11. Benefits of a rating model Decision to lend – reduce adverse selection problem In case of lending for a poor credit worthy borrower, what additional collateral to be sought Measure risk and price loans in a scientific manner Achieve consistency across the organisation Perform analysis of portfolio using risk scores, drivers of risk in the rating model

12. Explanatory Variables in the Home Loan Model Age Family structure Joint/Nuclear Quality of Borrower Skill level Years of Banking Qualitative Others Years of Experience Cost of Living No. of dependents Residence type Marital Status Loan to Value Fixed Obligation / Income Quantitative EMI/NW Loan Amount Income

13. Quantitative IndicatorsFixed Obligation to Income Ratio (FOIR) FOIR 35.0% 1.8% 29.5% 28.6% 1.6% 1.6% 30.0% 24.5% 1.4% 25.0% 1.2% 20.0% 1.0% 0.8% 15.0% 0.7% 9.0% 0.6% 8.5% 10.0% 0.5% 0.5% 0.5% 0.4% 5.0% 0.2% 0.0% 0.0% Less than 25% 25% - 40% 40% - 60% 60% - 80% Greater than 80% Relative Frequency Default Rate Higher the FOIR, lower is the capacity of the applicant to absorb the negative shock in net income. Hence, higher the FOIR, lower is the ability of the applicant to meet unforeseen expenses. From the data it is observed that if FOIR exceeds 60%-80%, default increases The optimum range for lending in terms of most favorable default experience is the 40%-60%

14. Quantitative IndicatorsLoan to Value Ratio (LTV) LTV 47.5% 50.0% 1.8% 45.0% 1.6% 1.6% 40.0% 1.4% 35.0% 1.2% 27.5% 30.0% 1.0% 25.0% 0.8% 17.5% 20.0% 0.6% 0.6% 15.0% 0.4% 0.4% 10.0% 5.5% 2.0% 0.2% 0.2% 5.0% 0.0% 0.0% 0.0% Less than 25% 25% - 40% 40% - 60% 60% - 80% Greater than 80% Relative Frequency Default Rate Lower the LTV, greater is the applicants contribution towards the asset i.e. loss in event of default increases for the applicant. The optimum range in terms of most favorable default experience is the 60-70% Default rates increase sharply when LTV is greater than 80%

15. Quantitative IndicatorsAge of the Borrower 40.0% 1.8% 35.7% 34.1% 1.6% 35.0% 1.5% 1.4% 30.0% 1.4% 1.2% 25.0% 19.0% 1.0% 0.9% 20.0% 0.9% 0.8% 0.8% 0.7% 15.0% 0.6% 10.0% 6.4% 0.4% 3.6% 5.0% 0.2% 0.8% 0.4% 0.0% 0.0% 0.0% Less than 25 - 30 30 - 40 40 - 50 50 - 60 60 - 70 Greater 25 than 70 Relative Frequency Default Rate The lower age bracket and the higher age brackets appear more prone to default The 40 -50 years age bracket seems to be the safest

16. Other important factors which should be considered for appraisal Credit Track Record Past credit record depicts the attitude of the person in honouring his credit obligation. “Wilful default” are one of the causes for a number of defaults. Nature of Asset In Housing Segment, assets gradually appreciate with time unlike many other assets [Cars, white goods, etc.]. The chance of negative equity will be lesser and Loan to Value ratio will improve over the period of time. Collateral Security Additional collateral security lowers the net exposure of the bank. It increases the applicants contribution in the asset thus effectively reducing loan to value ratio If the Collateral Security is high, in case of default by the applicant, the Loss Given Default will be lower

17. Rating models – Does it really work ? • 6967 out of 9092 customers correctly classified -77% accuracy (73% accuracy within first 3 grades – refer blue color last column)

18. Balance business flexibility with asset quality improvement Cumulative NPAs Risk Grade 10 9 8 7 6 5 4 3 2 1 Cumulative Lending The objective is to strike a balance between business objectives (so that not too many cases are rejected) and potential NPA reduction.

19. Formation of pools – cost effective way of managing risks

20. Risk based pricing of mortgage loans – USA • Interest rates are determined based on a number of factors like • Loan Type, Loan Amount • Property Type, Property Use, Property Location • Credit Score and History – one of the most important factors • Debt to Income Ratio • Appraised Value/Purchase Price • Loan to Value/Purchase Price • Documentation Type Example: FICO score >=760 score can fetch 0.375% rebateFICO score 680-719 will have no fee/rebateFICO score 660-679 will incur 0.25% cost Illustration source: http://www.thetruthaboutmortgage.com/mortgage-dictionary/risk-based-pricing-loan/

21. Risk based pricing system in various countries

22. Discussions