9/14/07

Edward Kramer Executive Vice President, Regulatory Programs, Wolters Kluwer Financial Services

Class action fair lending lawsuits in the automobile financing area have resulted in creditor scrutiny at all levels. This article will provide an overview of the fair lending laws and how creditors can help avoid violating such laws when funding auto finance transactions.

Overview

Recent class action lawsuits have brought fair lending issues to the forefront of automobile financing. These cases have cited disparities in pricing and dealer markup for minority borrowers – disparities not based on creditworthiness. These lawsuits can be extremely expensive to the creditor – in 2005, the cost of these lawsuits exceeded 30 million in contributions to consumer education, attorneys' fees, litigation expenses, and payouts to class representatives.

Creditors are now being scrutinized on fair lending issues – scrutinized not only by examiners, but also by community groups. The risk is really two-fold:  regulatory risk and reputational risk. No creditor wants to be written up by an examiner for fair lending issues. No creditor wants to have its name splashed in the media with allegations of unfair lending. A creditor needs to understand fair lending laws and take steps to ensure that it is not violating those laws.

Federal Law Prohibits Discrimination

The federal Equal Credit Opportunity Act (ECOA) prohibits discrimination in any aspect of a credit transaction based on race or color, religion, national origin, sex, marital status, age, receipt of income from any public assistance program, or the exercise, in good faith, of any right under the Consumer Credit Protection Act. These categories are typically called the "protected classes." The federal law requires that similarly qualified applicants be treated the same, regardless of whether the applicant is a member of a protected class. The ECOA is implemented through Regulation B.
 
In the area of auto financing, ECOA claims typically involve allegations that the applicant (or the car buyer) was treated differently due to the applicant's (or car buyer's) race, ethnicity, age, or gender. For example, the allegation might be that minority applicants were more likely to be denied credit than non-minority applicants with similar creditworthiness. Or, more typically, the allegations might be that minority applicants were charged higher prices for transactions than non-minority applicants with similar creditworthiness.

There may be additional fair lending laws under state law; in this article we are just touching on the federal ECOA law.

The Auto Finance Fair Lending Examination

Creditors who fund auto finance transactions through the dealer are subject to examination by banking authorities. An auto finance fair lending exam typically will have two aspects to it, the transaction testing and the pricing testing.

• Transaction testing. Examiners will review transactions in order to identify any patterns of discrimination in the credit-granting decision. This test will compare the approved and declined applications.
  
  
• Pricing testing. Examiners will also perform a pricing test. The test will be designed to verify that borrowers were priced appropriately based on credit risk. The pricing test will also look for any trends that might indicate that charges were increased upon a prohibited basis.

The examiner will be looking for evidence that members of the protected classes were treated differently with regard to credit granting and credit pricing. This usually occurs with dealer "mark-ups."

Mitigating Fair Lending Risk

So what's a creditor to do? A creditor needs to make fair lending risk mitigation a priority in its organization.

A traditional approach. A creditor could interview the individuals involved in the sale and underwriting processes. This could help identify any overt discrimination. A creditor could also review a sampling of closed transactions in order to do a comparative file review. This is probably the most common approach, but it is time consuming. Such a review will help identify whether members of a protected class were treated differently than non-members of the protected class.

A modern approach. To really stay on top of fair lending issues – to catch the problems before they become a part of the portfolio – a creditor really needs to use robust technology in its fair lending practices. This is done by integrating a fair lending system into the creditor's existing automated processes. The creditor can determine in real time whether an applicant was denied who should have been approved. Or help prevent an applicant from being overcharged. Technology can bring uniformity and consistency to fair lending risk mitigation. Technology – in the form of fair lending analytics software – can save money by automating labor intensive tasks, and, most importantly, prevent disparate treatment before it happens.

Fair Lending Analytics Software

The advantage of fair lending analytics software is that it can test in real time; this will help prevent fair lending problems from entering the creditor's portfolio. Fair lending analytics software can test at the time of transaction in the following manner:

• Whether that transaction is following the creditor's established credit policy.
• Whether that transaction is following the creditor's pricing policy.

The fair lending analytics software will help measure whether protected class members are being treated differently. The software can perform this function in a fraction of the time and cost involved in doing such a comparison in the traditional approach.

Collecting the Data

Under ECOA, the creditor is required to collect what is called "government monitoring information" (data about race, ethnicity, and gender) only for certain loans that are secured by a home. ECOA prohibits the collection of the government monitoring information for transactions beyond those certain home loans. Because auto finance transaction data does not include government monitoring information for race, ethnicity, and gender, the examiner may rely on "surrogate coding" for inferring data on race, ethnicity, and gender.

• A surrogate race code may be assigned based on census tract demographics. For example, a resident of a census tract with a population that is 80 percent or more minority population may be coded as a minority record. 
  
  
• A surrogate ethnicity may be assigned based on the list of Hispanic surnames. A list of Hispanic surnames is available through the census bureau.
  
  
• A surrogate gender may be assigned based on first name. 

By using surrogate coding, fair lending analytical software can help measure whether protected class members are being treated differently.

Conclusion

Examiners and community groups are expected to watch the behavior of creditors closely, especially in the area of auto finance. Make sure that your organization has made fair lending a priority. By implementing fair lending analytical software, your organization can avoid difficult examinations, costly litigation, and damage to your reputation. 

The best fair lending automation solutions perform the full range of risk assessment, matched pair testing, regression analysis, and reporting without the need for costly consultants and statisticians. Find out how Fair Lending Wiz®, from Wolters Kluwer Financial Services | PCi, can provide best-in-class fair lending analytics.

In addition, be sure to view the Wolters Kluwer Financial Services’ Motor Vehicle Product List for a full array of documents to help you address regulatory requirements with the financing of a motor vehicle.