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Credit Underwriting and Default Management in Today’s Private Student Loan Environment

Credit Underwriting and Default Management in Today’s Private Student Loan Environment. Contact Info: Michial Thompson Managing Director, Credit Risk Management First Marblehead 617-638-2135 mthompson@fmd.com. How to Avoid Student Loan Defaults.

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Credit Underwriting and Default Management in Today’s Private Student Loan Environment

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  1. Credit Underwriting and Default Management in Today’s Private Student Loan Environment

    Contact Info: Michial Thompson Managing Director, Credit Risk Management First Marblehead 617-638-2135 mthompson@fmd.com
  2. How to Avoid Student Loan Defaults To determine how to prevent defaults, let’s look at what the main drivers of default are: Credit Policy: Lenders make loans they expect to be paid back Collection Agency Management: Ensure maximum performance when DQ loans are placed for collections Data & Analytics: Performance projections, reporting and collections placement streams driven by data analytics Student Loan Idiosyncrasies: Deferment, youth, cosigners 2
  3. PSL Credit, Data and Analytics 3
  4. Credit Policy
  5. Credit Policy Appropriate Assessment of Risk at Time of Application Beyond just FICO More granular credit bureau attributes Evaluate both student and cosigner Over-borrowing/loan amounts School types/programs Ability to repay 5
  6. Credit Policy: Skeletons in the Closet All of these are cosigned loans with cosigner FICO > 750. The bars show what happens to defaults when we further segment these by student FICO. The student (skeleton in the closet) weighs heavily on the performance of the loan. Overall cosigned loans with cosigner FICO > 750 default at a higher rate than non-cosigned loans with student FICO > 750. Cosigner vs. CWS Student FICO on Cosigned (>750) Loans 6
  7. Credit Policy: Lend to Quality Schools Dropouts are twice as likely to default as graduates School, school type, and program of study are strong predictors of graduation rates Clearly graduates are more likely to get a higher paying job that will allow them to pay back the loan 7
  8. Credit Policy: Lend to Quality Schools 8
  9. Credit Policy: Control Over-Borrowing School certification greatly reduces over-borrowing compared to DTC Loan amount requested should be considered in credit decision Capacity metrics (such as DTI) further assess ability to repay and prevent excessive loan amounts 9
  10. FMC Private Student Loan Scorecard: Updated Score Further Separates Risk 10
  11. Agency Management
  12. Aggressive Agency Management Approach Define Strategy Define the agency type (experience, client base, management, etc) Performance drives future volume placements Incentive plan must be meaningful to agency to align performance Develop Network Optimizing number of agencies per segment to foster competition Continuous refresh of agencies based on results Robust bullpen for quick change-out for performance or client need Goals and volume forecasts clearly communicated Monitoring in place for outcomes; activity monitoring progressing Mutual transparency into operations Deep dives on root causes of performance gaps Volume shift algorithms for Recovery agencies Agencies now know they are being watched Manage 12
  13. Data & Analytics
  14. Data and Analytics NOT one-size-fits-all Collectability scorecard Origination, monthly performance, refreshed credit bureau data Probability of a delinquent loan curing Strategies driven by data When to place a file vs. leaving it with servicer Which collection agency to place with How long to leave loan at a given collection agency Which strategies (FB, MGRS, etc) available per customer Test-and-learn approach 14
  15. Data and Analytics Agency level Daily, weekly, monthly Performance by batch, by risk segment, by placement stream/strategy Transparent view of competition Agent level Daily, weekly, monthly Keep track of what happens to top performers 15
  16. Data and Analytics Data Dialer data Daily details of every call Skip-tracing Refreshed credit bureau data Phone, cell phone data USPS (and others) data to track relocations 16
  17. Data and Analytics: Example Agent level reporting Prevent best performer migration Plans for lower performers Resulted in 3 better supervisors transferred in They know we are watching 17
  18. Data and Analytics: Example Test-and-Learn Mailing Strategy Test Timing of communications strategy Borrower vs. Cosigner Delivery / Channel options Agency integration / talking points No Cosigner With Cosigner 18
  19. Student Loan Idiosyncrasies
  20. Student Loan Idiosyncrasies Deferment does not build a habit of making payments Credit policy should encourage cash-flowing loans Early Awareness Program Reach out to both student and cosigner before repayment Email, phone, mail package Most loans need a cosigner—utilize this early and often Contact cosigner at any sign of trouble Include cosigner in all communications Require cosigner participation in FB or similar decisions 20
  21. Student Loan Idiosyncrasies: Example Deferment 21
  22. Results: A Case Study
  23. Case Study: FMD reduced delinquencies and defaults for one major bank’s PSL portfolio by 50% After taking over, delinquencies immediately improved. Within 6 months, annualized monthly charge-off rates were cut in half. 23
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