How HMDA data and increased transparency can affect fair lending.
HMDA submission season is just around the corner and your institution’s data will be under close scrutiny by more than regulators. Litigators, advocates and the general public can view the data and possibly use it to identify institutions at fair lending risk. But since HMDA data alone is not enough, this can lead to misinterpretation, unwarranted accusations and loss of reputation. To help mitigate these issues, maintaining HMDA data integrity is essential.
The Home Mortgage Disclosure Act (HMDA) was created to enhance the monitoring of lending patterns and to ensure financing needs are met across a diverse field of potential borrowers. Submitting loan origination and application data on borrower demographics and loan features enables enforcement agencies to identify financial institutions who excel at fair lending and those that require further investigation. In order to accommodate that goal, new data points were added in hopes to further keep biases in check and reduce barriers to homeownership for protected classes.
The new data delivers a deeper understanding of institutional borrowing practices. Regulatory agencies can now apply comprehensive data screening, data monitoring and statistical modeling routines across all lenders subject to HMDA reporting requirements. In addition, many of the new HMDA data fields, like age, credit score and debt-to-loan ratio, can be used for more effective identification of institutions with elevated potentials of fair lending risks.
With the release of the new data, 2020 is the first time members of the public will have greater access to some of the key determinants of underwriting and pricing decisions. Be assured, litigators and advocacy groups will be taking a close look for any sign of unfair practices. Since disparities are estimated after a broader range of pricing and underwriting factors are applied, litigators can present more credible fair lending cases that on the surface appear to be true than with previous HMDA data sets. Furthermore, journalists will also have access to the data, possibly increasing marketing and reputational risks.
Peer analysis also benefits from the new data. Because it is accumulated from all covered financial institutions, it is particularly helpful for defining local and national benchmarks. Peer comparisons can be expanded beyond penetration rates in minority census tracts to include APR, total loan costs, product features and so on. A clearer picture is presented, allowing regulators to more accurately compare benchmarks and identify institutions with elevated fair lending risks.
With more public access to HMDA data, regulators advise caution when interpreting this data, especially if it leads to accusations or conclusions of discrimination. According to a FFIEC Press Release, “HMDA data alone cannot be used to determine whether a lender is complying with fair lending laws. The data do not include some legitimate credit risk considerations for loan approval and loan pricing decisions. Therefore, when regulators conduct fair lending examinations, they analyze additional information before reaching a determination about an institution’s compliance with fair lending laws.”
In today’s world, businesses rise and fall on the whims of public perception. An unsubstantiated claim of discriminatory lending practices based on misinterpreted data could have far-reaching consequences. What can financial institutions do to protect themselves? Understand your data, especially when underwriting and pricing decisions can create and identify disparities. Realize how your data can be interpreted by public regulators, advocacy groups, journalists and litigators. And then be prepared to tell your story and/or present the corrective and preventive actions taken.
The only way to minimize or eliminate risk is to consistently monitor and analyze your own data for pricing, underwriting and redlining risk. Keeping data clean and relevant is essential for accurate interpretation. In addition, separate assessments should be conducted to identify possible anomalies generated by the expanded data fields. This can be an intensive undertaking. Automated compliance software for HMDA reporting will help ensure data accuracy. At the same time, it will help identify fair lending risk points in the application and origination process. When combined with analysis and interpretation, you should be able to identify any additional risk factors.
Marquis can provide a turnkey solution when combining industry-leading tools like CenTrax NEXT compliance software with the experienced and intuitive skills of the Marquis Compliance Professional Services experts. These services can make a great difference in your HMDA reporting process by regularly monitoring and cleaning your data and then helping you understand the HMDA Integrity Analysis. With cleaner data and a deeper understanding of how it can be interpreted, your institution will be better able to respond when your HMDA data is used by regulators and the public to evaluate fair lending risks.