Big Picture
Compliance with fair lending laws and regulations is a key priority for financial institutions, and data analytics is an invaluable asset to monitor and measure the effectiveness of a fair lending program. The Equal Credit Opportunity Act (“ECOA”) and the Fair Housing Act (“FHA”) prohibits discrimination on protected classes that are enumerated under both federal laws. Additionally, the Home Mortgage Disclosure Act (“HMDA”) implemented by Regulation C, requires certain financial institutions to maintain, report, and publicly disclose important information about mortgage lending.[1] HMDA data helps to illustrate how “lenders are serving the housing needs of their communities,” which helps public officials make key policy decisions, and could also reveal potential discriminatory lending patterns that would violate the ECOA or the FHA.[2] Therefore, financial institutions should be vigilant to ensure that they accurately report data and appropriately administer policies, procedures, and practices to mitigate the risk of unfair treatment or discrimination.
[1] https://www.consumerfinance.gov/data-research/hmda/
[2] See Id.
Client Scenario
A law firm representing a banking client retained Asurity Advisors to perform a fair lending review of the client’s application and origination data (i.e., HMDA-reportable transactions). This fair lending review required building and executing underwriting and pricing regression models and performing fallout disparity analysis.
Asurity Solution
Asurity Advisors, led by industry experts, has a broad domain of knowledge and skills to methodically conduct statistical analytics for the assessment of regulatory compliance requirements and the evaluation of fair lending risks. To that end, Asurity Advisors performed statistical analysis of credit outcomes, including underwriting decisions, pricing decisions, and application fallout. Underwriting decisions were assessed using logistic regression, while pricing decisions were evaluated using least squares regression. Two-factor proportion tests, also known as Chi square tests of homogeneity, were used to test for differences in fallout rates on a prohibited basis.
For any prohibited basis group where statistically significant differences in outcomes were discovered, Asurity Advisors selected files for comparative file reviews to investigate the results of statistical testing and provided training to the bank on best practices in conducting comparative file reviews. A comprehensive report was drafted to summarize the results of the fair lending analyses.