With contributions by Olivia Hebner

Today’s post closes our three-part series on discrimination in mortgage lending and the analytical techniques that Summit uses to detect it. Part one discussed analytical techniques to detect redlining, the practice of denying loan applications to minority applicants based on the racial composition of neighborhoods. Part two examined loan pricing discrimination, the practice of charging higher interest rates to minority applicants due to their race.

In this installment, we talk about origination discrimination and predatory lending. 

With contributions by Natalie Patten

This is the second installment of our three-part series on discrimination in mortgage lending and the analytical techniques that Summit Consulting uses to detect it. Last week, we introduced redlining and showed examples of analyses we perform to identify potential redlining practices by a given lender. This week, we will explore how we identify and measure pricing discrimination.

This week, Summit released a new white paper on using analytics to combat discrimination in housing.

Over the past several weeks, we explored fair lending regulations and mortgage finance practices here on the Summit Blog. Today, we round out the blog series by acknowledging potential borrower concerns about the Consumer Financial Protection Bureau’s (CFPB’s) amendment to Regulation C. Read on to explore these revised reporting requirements. We will also discuss how home buyers might benefit (and maybe even save money) from the coming data windfall.

How often do you think about the local sanitation department's efforts to purify your water? Unless you are a department employee, you probably just assume they do a good job. So it stands to reason that unless you are mortgage lender, you do not give much thought to the amended Home Mortgage Disclosure Act (HMDA) data CFPB will collect. Yet if CFPB does not collect enough of the necessary mortgage data or mishandles the data it does collect, homeowners (and potential homeowners) have reason for concern.

How does expansion of Home Mortgage Disclosure Act (HMDA) data change the ways in which we can use that data? So far in our HDMA blog series, we have explored the new 2015 HMDA rule, the history of HMDA and fair lending, and how HMDA data helps combat redlining. This week, we will discuss how the expansion of HMDA from aggregate-level to loan-level data significantly changed the ways in which HMDA could be used by community leaders, industry experts, and regulators.

Last week, we discussed the history of Home Mortgage Disclosure Act (HMDA) and fair lending in the United States. The week before, we reviewed what's new in the updated HMDA rule. This week, we'll explore redlining and racial disparity in mortgage lending.

Redlining describes a situation where mortgage services are denied or limited for two specific reasons:^[1][2]

1. The racial and/or ethnic composition of an area’s residents
2. The age of an area’s properties

Last week, we reviewed what's new in the updated Home Mortgage Disclosure Act (HMDA) rule. This week, we'll explore the history of HMDA and fair lending.

The history of HMDA is best understood in a broader context of fair housing. Despite positive changes brought about by the Fair Housing Act of 1968, congressional hearings just a few years later revealed a continued lack of credit in urban communities, which in turn contributed to declining housing conditions. (To learn more about the current status of fair housing, click here to read our our blog post about the 2015 Supreme Court decision on the Fair Housing Act and disparate impact.)

Over the course of three years, Congress enacted a series of fair housing efforts:

On October 15, 2015, the Consumer Financial Protection Bureau (CFPB) issued the final rule on the Home Mortgage Disclosure Act (HMDA) updates, as required by the Dodd-Frank Act.

A Bit of Background on HMDA:  Enacted in 1975, HMDA is a Federal law that requires certain financial institutions to report information about mortgage applications and originations. The reported HMDA data contain certain key information on borrowers, properties and underwriting decisions. The initial intention of HMDA legislation was to provide information on how well financial institutions are serving housing credit needs. HMDA has served an important role in studies on housing needs and mortgage lending practices, as well as possible discriminatory lending patterns. These data have been used by Federal agencies, advocacy groups, lending institutions, and academia. Every year, the Board of Governors of the Federal Reserve System publishes a study on the newly released HMDA data to provide an overview of the most current mortgage market trends (2013 HMDA study and 2014 HMDA study).

On June 25th, the Supreme Court issued its decision in Texas Department of Housing and Community Affairs v. The Inclusive Communities Project, Inc. and affirmed several decades of legal precedent by holding that the Fair Housing Act (FHA) allows claims based on disparate impact. This decision upholds the U.S. Department of Housing and Urban Development (HUD) view that liability exists under the FHA not just for policies that are intentionally discriminatory, but also for policies which unintentionally lead to discriminatory outcomes. It also confirms that using statistical methods to test for discriminatory outcomes can be an important component of future claims brought forward under the FHA.