Yesterday, an interagency statement was issued to remind creditors of the ability under the Equal Credit Opportunity Act (ECOA) and Regulation B to establish special purpose credit programs (SPCP) to meet the credit needs of specified classes of persons.
At the heart of SPCP success is the ability of lending institutions to channel data to inform their SPCP program management, from determining need and writing a written plan to setting up a measurement framework that measures and reports progress of the SPCP rollout. The use and application of data is still a barrier for many lenders when it comes to SPCP. Lenders can use our framework for Determining Need to organize their analysis and explore the feasibility of SPCP in their markets. We have identified 5 areas/questions that lenders can start exploring immediately, analyzing the data, and documenting the results (see the graphic below). By performing this analysis, lenders will learn a lot, and they will also generate more questions about SPCP, driving additional rounds of analysis.
This framework helps guide the analytical project and can be applied to all the markets where lenders operate. Combined with the fast and powerful analytics in HMDAVision, this is not only quick but also a repeatable analysis for multiple markets/locations, producing consistent market analysis reports that are also easily collected and shared.
Often, lenders may come to the conclusion that there is no need for SPCP because their existing products and programs are serving the credit needs of their communities - or could be expanded to do so. Either way, such an analytical exercise will be highly beneficial to lenders, helping them understand even better the local dynamics in their markets, assessment areas (AA), or reasonably expected market areas (REMAs), serving as a triage tool that can quickly identify fair lending red flags, if any, and inform plans of action to resolve them.
Working with the industry data, whether it is for analyzing your markets and lending patterns to determine need for SPCP, or even choosing the data for your automated valuation models (AVM), which is another hot topic on the regulators' radar, requires that lenders are fluent in the available industry data, its use cases, its characteristics, its limitations, and its potential for bias. We will be writing more in future posts about data for AVMs and the risk of algorithm bias, and would love to hear your thoughts on these topics.
In the meantime, schedule 15 minutes with us to explore how data can be used to support the evaluation and design of SPCP.