November 2016 - End of the Road?

TheMReport — News and strategies for the evolving mortgage marketplace.

Issue link:

Contents of this Issue


Page 21 of 67

20 | TH E M R EP O RT FEATURE conducting business in majori- ty-minority or low-to-moderate income neighborhoods within its footprint, is high on the reg- ulatory agenda. A case this year in Memphis involved sending undercover "testers" to bank branches, resulting in a joint complaint by the CFPB, and the DOJ that settled for over $10 million in penalties, plus the opening of a new branch, and other remediation. • Multiple regulators are scruti - nizing the fairness of mortgage lending. For example, the CFPB refers matters to the DOJ, and then the two agencies bring joint actions against the defendant. • Regulatory tolerance during fair lending examinations appears to be lower than ever. For example, a single violation iden - tified in an exam sample may result in a full-blown investiga- tion. And, the "acceptable" de- nial disparity ratio benchmark, which is used to assess whether protected classes are more likely to be denied credit than non- protected classes, is shrinking. A Lot to Lose D iscrimination in the lending process in any form—overt or covert, intentional or un- intentional—is illegal. Prudent lenders elevate fair lending risk management to the top of their priority lists—and to the high- est levels of management and governance—to minimize regula- tory scrutiny, and the ramifica- tions of non-compliance with fair lending laws and regula- tions. Such consequences can be multi-faceted, with serious detrimental effects including: • Complaints and allegations of violations • Litigation and legal fees • Reputational damage through negative publicity • Regulatory scrutiny and targeted examinations • Civil money penalties, restitution, and fines • Administrative and enforcement actions • Loss of business opportunities The last impact (loss of busi- ness opportunities) includes the harm a fair lending allegation could do to a bank's Community Reinvestment Act (CRA) rating. A lowered rating can hinder cor - porate business strategies such as acquisitions and branch closings. In the current environment, the industry is seeing unprecedented double-rating downgrades in one exam cycle (e.g., from "outstand - ing" to "needs to improve"). From the top of this list to the bottom, the associated costs can be considerable. In a 2015 case settled with a New Jersey bank, remedia- tion included $25 million in direct loan subsidies, a $5.5 million penal- ty, $2.25 million in new community programs and outreach, two new branches to be opened in majority- Black-and-Hispanic neighborhoods, submitting to outside monitors, and developing a fair lending com - pliance and training plan, among other requirements. Additional costs, in terms of negative publicity and reputation damage, simply cannot be quantified. The $10 million Memphis case this year, as mentioned earlier, includes many provisions similar to the case in New Jersey, which the CFPB and DOJ proclaimed to be the largest ever. And the exten - sion of fair lending enforcement into other lending areas, such as auto loans, is evident in a $24 million settlement that the two agencies reached this year with a major automaker's finance arm. Send in the SaaS B est-in-class statistical analyt- ics programs afford lenders vigilance, intelligence, consis- tency, and data integrity—all crucial elements of effective fair lending risk management. Vigilance. Fair lending analytics technology can empower lenders to run more proactive tests on any loan portfolio—home, auto, stu - dent, credit cards, and so forth— employing a risk-based approach through the use of statistical methodologies. Software can be set up to help lenders keep a pulse on their lending patterns, proactively assessing risk rather than reactively waiting for scrutiny—both at the portfolio level and by individual markets or assessment areas. Intelligence. Software analytics inform lenders on potential areas of fair lending risk that warrant further investigation or corrective action plans. It helps visualize and analyze data on peer comparisons, market performance, geographic and demographic breakdowns, application versus origination activities, and more. SaaS software provides automatic updates of regulatory requirements and data sources by the vendor to lessen the burden on lenders (for exam - ple, the CFPB's recent release of over 14 million HMDA-reportable transactions collected from nearly 7,000 lenders in 2015). Consistency. Regularly scheduled reports can be produced based on standardized, repeatable meth - odologies. Fair lending analytics technology can reduce subjective interpretations in monitoring and analyzing lending patterns to detect emerging negative trends through the use of consistent, quantitative methodologies. Data integrity. Data fed into fair lending analytics must be accurate and complete, or the results produced will be unreliable and unacceptable for use in a fair lending examination. Automation can help to detect and easily cor - rect errors and gaps in the source data files that have to be used in fair lending reviews. The alterna- tive can be very expensive in terms of time spent scrubbing files or erroneous regulatory findings. To deliver on its promise, fair lending analytics technology must also be more accessible and user-friendly. With SaaS deliv - ery, it has become as convenient as opening a web browser. The SaaS design—also referred to as a "thin-client"—is comprised of software hosted on a vendor's pri - vate servers and accessed through a secure portal over the Internet. Traditionally, lenders have used general purpose statistical pack - ages or relied extensively on 5 Ways Fair Lending Analytics Can Provide Business Insights Understand your market- ing campaigns prior to launching. How does targeting a new segment in a new geographic area impact your lending portfolio? What are the demographics of the targeted population and communi- ties where outreach is to occur? Pre-launch analytics can help to identify and fix points of elevated fair lending risk before any firm ac- tion is taken. Assess new business op- portunities. Lenders can leverage publicly-available data to compare and contrast lending activity in merger and acquisition scenarios—of the entity to be acquired and the combined result of the consolidated entities. The same tools can also help evaluate branch strategies. Analyze competition. Comparisons to HMDA aggregate data and target peers in key markets will prepare lenders to answer questions such as: How do you determine who your peers are in each market? Where are com- petitors lending, and to whom? How do you benchmark against your peers in certain geographies? Identify root causes for operational issues. Data integrity reviews and segmented regression analyses can help pin- point specific operational factors— or even branches and personnel— that form the basis of compliance and general performance issues. Oversee third-party lending channels. Lenders can mini- mize risks inherent in third-party re- lationships by proactively managing the activities of mortgage brokers. Which brokers represent outliers in your portfolio of active brokers? Use analytics to document non- compliant pricing or underwriting practices, then educate the broker on what is acceptable. 01 02 03 04 05

Articles in this issue

Archives of this issue

view archives of TheMReport - November 2016 - End of the Road?