On December 6, the FDIC announced actions to promote a “more transparent, streamlined, and accountable deposit insurance application process” to encourage the establishment of new, or de novo, banks.
Your fair-lending regression results indicate a statistically significant disparity… now what? In our last blog post, we discussed the importance of a common-sense approach to statistical analysis. One common error in statistical analysis is to assume that a result is practically meaningful just because a result is statistically different from zero. This in not always the case. In fact, finding a statistically significant result may or may not be meaningful.
As fair lending analysis becomes increasingly technical, industry practitioners have had to familiarize themselves with the terminology of statistical analysis. Statistical significance is one of the most common and foundational concepts to successfully navigating these new waters. Moreover, it is a concept that, when misunderstood, may result in serious error.
One of the first questions before beginning any type of statistical analysis is what data are included and how should the sample or samples be formulated and segmented. In previous posts, we have addressed various nuances in regard to regression modeling and how the inappropriate application of regression and modeling techniques to real world issues (such as credit quality or fair lending) can have serious consequences.
The Federal Reserve Bank of New York released in February (2018) a study examining the role of technology-based residential mortgage lending. The report highlights the growth in volume of mortgage lending conducted exclusively over the internet along with other characteristics of this method of service delivery.
As is the case with most things in life, the regulatory environment goes through cycles. With respect to fair lending, examinations in the past few years have emphasized issues such as loan underwriting, redlining, and steering as opposed to pricing. Part of the explanation for this is cyclical, but also because examiners have perceived pricing risk as lower relative to other issues.
This, however, is very likely to change in the near term. Institutions may begin finding an increasing level of scrutiny in regard to loan pricing. There are a number of reasons for this and why this risk is likely to increase for lenders.
The term “Fintech” has come to mean essentially any application of technology for delivering financial services. More specifically, the term represents a rapidly growing space of alternative lending facilities that are outside of the traditional banking industry. This includes both consumer and, more recently, business lending.