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Fair Lending Risk Assessments, File Reviews & Best Practices. Presented by Eleanor (Ellie) J. Fox. June 2013. Fair Lending Risk Assessment (FLRA). The general components of a FLRA include off-site and on-site analysis: Off-site analysis of HMDA Data

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fair lending risk assessments file reviews best practices

Fair Lending Risk Assessments, File Reviews & Best Practices

Presented by

Eleanor (Ellie) J. Fox

June 2013

fair lending risk assessment flra
Fair Lending Risk Assessment (FLRA)
  • The general components of a FLRA include off-site and on-site analysis:
  • Off-site analysis of HMDA Data
    • FIS EGRC Solutions spreads data utilizing Centrax mapping software
    • Analysis reveals statistical evidence of potential discrimination
  • On-site analysis; review of documentation
    • Checking most recent compliance examination and audit reports for fair lending issues
    • Reviewing general and specific loan policies for clear and consistent underwriting standards and guidelines
    • Reviewing marketing materials including website and social media for use of diverse cultures and images
flra interviews
FLRA Interviews
  • On-site Analysis: Interview Management
    • Each FLRA reveals the appropriate person to interview but generally, it is helpful to start with the person responsible for HMDA accuracy and completion
      • If there have been multiple issues with HMDA accuracy and completion, then the off-site analysis may be compromised
      • If there has been significant turnover in this area, then additional training may be needed to avert future issues
      • Every effort should be made to interview someone who actually speaks to the applicant. This could be an originator who takes an application or follows up on ‘e’ applications.
flra interviews1
FLRA Interviews …
  • From a list of over 200 potential questions, choose 7 – 10 that apply to the institution and interviewee
  • Incorporate questions that arose as a result of documentation review
  • The goal is to ensure that the person being interviewed understands the policy and procedures and applies them appropriately
  • Determine whether the interviewee encourages applications, even when initial information makes it unlikely to be approved (e.g., applicant shares they just finished bankruptcy).
underwriting risks
Underwriting Risks
  • Higher denial rates for minority populations vs. white populations
  • Shorter or longer days to decide for one group vs. another
  • Loan origination compensation based on dollars of loans vs. numbers of loans
  • Lack of a second review for denials
  • Lack of exception tracking
  • Lack of annual exception analysis
collection servicing risks
Collection / Servicing Risks
  • General loan policies silent on fair lending and Servicemembers Civil Relief Act (SCRA) even when financial institution has a separate fair lending or SCRA Policy
  • Minimal explanation of concessions and modifications
  • Failure to reference Fair Debt Collection Practices
  • Failure to reference Credit Counseling
  • Failure to document state collection or servicing requirements
  • Inadequate consumer complaint tracking
  • Inconsistent and/or inaccurate reference to prohibited bases
  • Incomplete complaint process
redlining marketing risk
Redlining & Marketing Risk
  • Redlining Risk - The percentage of applications from minority census tracts with greater than 80% minority population is low compared to the number of minority majority census tracts in the assessment area (AA).
    • Example: Receiving 1% of all applications from “minority-majority” census tracts when those census tracts comprise 12% of the assessment area population. Implies an attempt to carve out these geographies.
  • Marketing Risk – The percentage of applications from minority populations is low compared to the population within the entire AA.
    • Example: Receiving 1% of applications from Hispanic applicants when the Hispanic population makes us 8% of the entire AA.
observations recommendations
Observations / Recommendations
  • Most institutions:
    • Reference all federal, but not state prohibited bases. We recommend creating an appendix detailing federal prohibited bases (by law/regulation) and then state specific prohibited bases for all states in which the institution lends.
    • Omit reference to SCRA in servicing or collection policies. We recommend including a reference to SCRA or at least to a separate, standalone SCRA Policy
    • Omit fair lending guidelines or code of conduct guidelines in their compensation agreements with originators. With the new MLO rules taking effect in January 2014, now is a good time to update these agreements.
    • Collect underwriting exception date on individual loans, but don’t create any aggregate reports. We recommend documenting exceptions made for consumer, residential and commercial loans.
observations recommendations continued
Observations / Recommendations (continued)
  • Most institutions:
    • Never escalate exceptions to the board level directly or by Loan Committee minutes – recommend escalating monthly and sharing semi-annual analysis
    • Omit any kind of analysis on the exception loans they do collect – recommend at least a semi-annual review of aggregate loan exceptions by type with subsequent annual sharing with the board
    • Limit training to lenders or only some lenders – recommend including all lenders and marketing at a minimum; much better to include all employees and of course the Board
comparative file review target group
Comparative File Review – Target Group
  • When a statistical risk develops from a FLRA, it is important to review the underlying files to ensure that there is no evidence of discriminatory activity
  • A comparative file review includes the target group (e.g., 15 denied black applicants)
    • Review these files in great detail, documenting the Housing, LTV and DTI ratios as well as anything of significance on the credit bureau reports
    • Ensure that an appropriate credit decision was made, based upon the facts and supporting information
    • Ensure that there was a more than cursory second review process
comparative file review control group
Comparative File Review – Control Group
  • A comparative file review includes a control group
    • Adhere to FFIEC guidance in determining the appropriate size for the control group (e.g., 100 approved White applicants)
  • Once the data is collected on both groups, we further analyze it to see if there are any anomalies
    • Were the Black applicants denied for exceeding policy ratios?
    • Were any White applicants approved even though they also exceeded policy ratios?
observations
Observations
  • Most Institutions:
    • Do not believe they act in a discriminatory manner
    • Do not analyze their HMDA data to identify potential risks
    • Do not conduct file reviews of these potential risks
    • Do not have a defense prepared when examiners raise same issue
      • Example – One Lender did not have discriminatory behavior but because they miscoded applications as withdrawn, rather than approved not accepted, the statistics indicated strong concern with ‘days to decide’
      • Example – Another Lender provided monthly exception reports; when they aggregated quarterly, they found exception rates over 25%. They increased their DTI ratio from 36% to 40% and eliminated exceptions.
watch out for fair lending red flags
Watch out for Fair Lending Red Flags
  • Red Flag #1: Disparate impact that may not be readily apparent
    • If disparate impact could exist or is suspected, conduct a “disparate impact analysis,” to ensure whether an adequate business justification exists and whether there is a less discriminatory alternative that could achieve the same results.
  • Red Flag #2: Lending policies that require a minimum loan amount
    • Although these guidelines are facially neutral, they have led to numerous fair lending complaints and settlements because of the perception that minimum loan amounts have a disparate impact on minority borrowers who are more likely to require lower loan amounts.
  • Red Flag #3: Credit overlays to underwriting guidelines
    • Credit overlays present a fairness risk in that similarly situated consumers are treated differently. Examples of credit overlays include:
      • Imposing higher minimum FICO scores for FHA loans
      • Requiring applicants on maternity leave to return to work before closing a loan
      • Requiring applicants on permanent disability to provide proof of the continuation of the disability from a doctor
fair lending red flags continued
Fair Lending Red Flags (continued)
  • Red Flag #4: Lack of periodic risk assessments to evaluate level of consumer compliance risk (including fair lending risk)
    • Federal regulators expect depository institutions of all sizes to conduct periodic risk assessments of its operations to evaluate compliance with applicable laws and regulations.
  • Red Flag #5: Use of discretion in consumer lending and loss mitigation
    • Policies and procedures often permit loan officers, underwriters or agents (e.g., auto dealers) to exercise discretion in pricing or credit decisions. Discretionary practices may also arise in areas such as account maintenance (e.g., fee waivers), collections, and loan modifications.
  • Red Flag #6: Failure to evaluate fairness risks and controls for non-HMDA loans
    • Although fair lending exams and enforcement actions have historically focused on mortgage lending, that no longer holds true. Recently, attention has been increasingly focused on non-HMDA lending (e.g., indirect auto lending, student lending, credit cards, and unsecured consumer lending).
    • In the absence of HMDA data to serve as the basis of a fair lending claim, the government has relied on “proxy” data (e.g., geocoding, surname) to conduct quantitative analyses.
thank you
Thank you!

Eleanor (Ellie) J. Fox

Assistant Director, New England Region

FIS Enterprise Governance, Risk & Compliance (EGRC) Solutions

978.778.8670

Eleanor.Fox@fisglobal.com