Redlining is one of the hottest areas of consumer compliance, attracting the attention of regulators, community groups and financial institutions alike.
In particular, the media has covered Redlining extensively in 2018. Three investigations were opened as a result of the Center for Investigative Reporting's Reveal story and podcast.
This focus on Redlining has been a prominent trend since 2015. Over the past few years, redlining has been in headlines consistently, whether because of investigative reporting, enforcement actions, or regulatory guidance. (Regulators noted redlining as one of the top focal points in the 2016 and 2017 Interagency Fair Lending Hot Topics webinar.)
In this post, learn the 3 simple steps of understanding your Redlining risk.
Remember, data analysis is at the core of understanding your Redlining risk exposure. Start identifying Redlining risk by conducting statistical analysis of your HMDA loan data. It's where the regulators start, and where you should start, too. When conducting redlining analysis, you should:
Review your census tracts and MSA(s) (Metropolitan Statistical Area) to determine your footprint, or Market Area, and also review the location of your branches, loan production offices (LPOs) and ATMs within those census tract(s) and MSA(s). Analyze both Majority-Minority and Low- to Moderate-Income (LMI) tracts. Make sure your Market Area(s) doesn't exclude LMI or High-Minority census tract(s).
You should also know the demographic make-up of your Market Area.
In many of the government's redlining claims, their first focal point is whether the assessment area is fairly drawn, which can be reviewed by conducting this branch analysis. Their second focal point is whether the institution is meeting the credit needs of their community; this is also assessed with data analysis, as we'll cover in more depth below.
To determine where you’re lending within your MSA(s), geocode your lending activity. Once geocoded, review approval and denial rates by LMI or high minority tract.
Is your lending activity concentrated in specific areas of your MSA(s) - particularly in high- or low-minority areas? This may seem problematic to the regulators, indicating either redlining or reverse redlining.
If you find potential issues, you’ll want to dig deeper and compare your product mix to the mossible credit needs of a particular tract. If approval or denial rates within particular tracts raise questions, you may want to evaluate staffing as well as internal policies and practices to determine why those borrowers aren't applying for or getting those loans.
The regulators will pay close attention to how your institution is performing when compared to peer institutions. This means you need to analyze your loan data as compared to census and peer data. You can do this by comparing your HMDA loan application and origination data to peers.
Ensure that your peers are properly defined. Just because they are in your market does not mean their product mix and are similar to yours. Improperly defined peers can draw unnecessary attention.
As you review the data, consider the following:
After conducting this analysis, share your finding with senior management and determine next steps. If necessary, work on an action plan to manage risk and monitor for changing disparities. Also, make sure to keep track of all decisions and any related business reasons so that you’ll have plenty of information if they regulators start asking questions.
Ncontracts Viewpoint: Data analysis is essential for determining redlining risk, which should absolutely be a priority for financial institutions in 2016 and beyond. Luckily, the analysis is not difficult or expensive; it just needs to be done. To learn more about analyzing your data for Redlining risk, get this Click here!!
With analysis, some institutions will find peace of mind, while others will gain a valuable warning of potential risk. Either way, it’s a necessary part of any consumer compliance program - and Ncontracts makes it simple. Get a free demo of Nfairlending today!