Regression and Statistical Analysis for Fair Lending

Financial institutions face increasing pressure from regulatory agencies in regard to fair lending. As regulators have launched renewed efforts with new strategies for detecting potential fair lending violations, a large number of institutions have found themselves having to react to a new level of scrutiny. This renewed focus by the regulatory and enforcement agencies employs innovative, statistical techniques and has imposed considerable time and resource demands on institutions in order to counter allegations of potential disparate treatment. Indications are that initiatives to scrutinize banks in this regard will continue and likely intensify.

A reactive posture will prove to be costly and extremely risky strategy for financial institutions. This approach is costly due to the time and resource demands of preparing, analyzing, and defending bank practices “ex post” and risky because banks may not know what their lending practices may suggest when subjected to sophisticated, econometric analyses. Conversely, a proactive approach will reduce risk and greatly enhance the likelihood of a positive outcome when faced with a fair lending review.

In order to be successful, banks must have at their disposal the intellectual resources to evaluate their lending practices consistent with this new standard. This involves knowledge of empirical and scientific methods as well as the experience to interpret analytical results and accurately evaluate risk. Institutions today must be able to have confidence in their robustness of their fair lending analytics. Premier has the experience, knowledge, resources, and track record to bring such confidence. We have a proven approach to reduce risk and effectively navigate the current environment.