Redlining Risk is Limited to Mortgage Products Explore the Facts and Figures

Redlining risk is often associated with mortgage products, but the reality is more nuanced. According to the data, mortgage redlining risk is limited to specific products.

In 2019, 71% of mortgage redlining complaints were related to home purchase loans, while only 12% were related to home improvement loans. This disparity suggests that redlining risk is concentrated in the mortgage products that are most critical to homeownership.

The majority of mortgage redlining complaints come from a small number of lenders. In 2019, the top 5 lenders accounted for 44% of all mortgage redlining complaints. This concentration of risk among a few large lenders is a key takeaway from the data.

Discover more: Aveda Products

Redlining risk is a serious issue that can affect financial institutions in various ways. Comparative statistical analysis of loan data can pinpoint disparities and the loans causing the problem.

To identify fair lending risk, you may need to seek the help of a third-party provider when analyzing and interpreting data for redlining, marketing issues, underwriting, and price steering. This is especially true if you're dealing with a complex issue like redlining.

The CFPB and DOJ have recently been investigating independent mortgage companies, which have been responsible for a growing percentage of the overall market share in HMDA reportable loans. In 2022, mortgage companies accounted for 72.1 percent of all first-lien, residential mortgage originations, up from 63.9 percent in 2021.

Analyzing data is key to identifying fair lending risk. Comparative statistical analysis of loan data can pinpoint disparities and the loans causing the problem.

Comparative statistical analysis involves looking at loan data from different groups, such as different demographics or geographic areas. This can help you understand if disparities in lending are due to a legitimate business reason or not.

You may need to seek the help of a third-party provider when analyzing and interpreting data for redlining, marketing issues, underwriting, and price steering. This is because these areas can be complex and require specialized expertise.

Comparative statistical analysis can identify disparities in lending, but it's just the first step. You'll also need to understand the underlying reasons for these disparities and whether they're compliant with fair lending laws.

Worth a look: Portfolio Risk Analysis

Redlining investigations are expanding to target a wider range of financial institutions. Independent mortgage companies are now under scrutiny, accounting for 72.1 percent of all first-lien, residential mortgage originations in 2022.

In the past, banks were given a grace period to operate in a new market before regulators expected them to receive applications from minority-area residents at a level that matched their longer-established peers. This is no longer the case.

Regulators are now casting a wider net to capture small community banks in their redlining examinations and investigations, including ones with assets less than $1 billion.

No bank is too small or too large to become the subject of a redlining investigation.

See what others are reading: No Appraisal Mortgage Loans

Redlining risk is primarily limited to mortgage products, but understanding the geographies involved is crucial for assessing this risk. Mortgage lenders often use geographic information to determine creditworthiness.

Geographic Information Systems (GIS) are used to analyze data and identify high-risk neighborhoods. These systems help lenders pinpoint areas with high foreclosure rates, low credit scores, and other factors that may indicate a higher redlining risk.

High-risk neighborhoods are often characterized by low median incomes, high poverty rates, and limited access to education and job opportunities. These areas tend to have lower property values and higher crime rates.

Intriguing read: Refi Rates California

Understanding the specific geographies involved in redlining risk is essential for mitigating its effects. By analyzing geographic data, lenders can identify areas with higher redlining risk and develop targeted strategies to address these issues.

In some cases, geographic location can be a strong predictor of creditworthiness. For example, borrowers from neighborhoods with high median incomes and low crime rates may be viewed as lower risk.

To analyze redlining risk, it's essential to create a performance context document that describes the economic and demographic conditions in each market area. This document should include institution-specific capacities and limitations.

You may need to seek the help of a third-party provider when analyzing and interpreting data for redlining, marketing issues, underwriting, and price steering.

A performance context document should capture factors such as business-justified limitations or constraints on lending, product offerings, and lending activities of similarly situated lenders.

Some key factors to include in your performance context document are:

This document will help you understand the range of economic and demographic conditions in each market area and identify potential disparities in lending practices.