Identifying Enforcement And Class Action

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Identifying Enforcement And Class Action Risk
Factors In Mortgage Servicing Brian P.
Brooks OMelveny Myers LLP 1625 Eye Street,
N.W. Washington, D.C. 20006 [phone] (202)
383-5414 (fax) bbrooks_at_omm.com
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Overview

• The hypothesis behind regulatory proceedings and
  class actions Subprime servicers are supposedly
  driven by financial incentives to manage loans
  into delinquency.
• The compliance dilemma for servicers Managing to
  measurable standards vs. managing to adjectives
• Compliance initiatives to reduce enforcement and
  class action risk Three key metrics

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Testing the Incentive Hypothesis Are Delinquent
Loans More Profitable Than Performing Loans?

• Analyzing loan-related cash flows

• For a given loan pool, what is the average net
  income (usually expressed in bps)?
• What is the average net income for 31-89 day
  delinquent loans?
• What is the average net income for 90 day
  delinquent loans? All delinquent loans?
• Comparing all delinquency-related revenues (late
  fees, inspection fees, BPO fees, etc.) with all
  delinquency-related costs (REO, lost servicing
  fee income, etc.)?

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• Testing The Payment Posting Hypothesis
• Are Timely Payments Posted Late?
• Analyzing payment posting issues
• Posting vs. crediting
• What percentage of borrower payments are posted
  on the date of receipt? Within 24 hours? Within
  48 hours? Etc.
• For payments posted after the date of receipt,
  are payments credited effective as of the date
  of receipt? Are any interim delinquency-related
  charges reversed? Is the reversal process
  automated or manual?
• To what extent are late postings attributable to
  servicing processes (e.g., data entry error) vs.
  borrower conduct (e.g., absence of loan number
  absence of property address incorrect/insufficien
  t payment amount)? To what extent are the causes
  of late posting documented?

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Testing The Excessive Delinquency
HypothesisAre Delinquencies Explained By
Servicing PracticesOr Credit Quality?

• Comparing delinquency rates to predictive
  delinquency models
• FICO scores, if available and sufficiently recent
• Predictive models based on pre-boarding
  delinquency profiles
• Comparing delinquency rates to industry averages
• Loan Performance data
• AFSA data

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Risk Management Strategies

• Dont wait for the crisis. Ongoing monitoring of
  cash flows, payment posting/crediting
  effectiveness, and credit quality-adjusted
  delinquency rates can identify issues before they
  mature into enforcement actions or litigation.
• Many processes that relate to risk factors
  involve human error. Consider whether automated
  solutions are available and practicable.
• To avoid allegations that servicers have a
  financial incentive to charge delinquency-related
  fees, consider extent to which expected servicing
  costs (including delinquency-related costs) can
  be priced into the initial servicing-rights
  transaction.