credit underwriting and default management in today s private student loan environment
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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 [email protected] How to Avoid Student Loan Defaults.

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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

[email protected]

slide2

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

slide5

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

slide6

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

slide7

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

slide9

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

slide12

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

slide14

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

slide15

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

slide16

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

slide17

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

slide18

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

slide20

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

slide23

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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