Compliance is a growing and labor-intensive focus for several mortgage industry participants. Milliman’s analytics tools allow you to monitor and manage your exposure to compliance risk by proactively providing your team with actionable information. We assist clients with compliance-related analytics for both fair lending and quality control reviews.
Fair lending disparate impact
Recent actions by the Consumer Financial Protection Bureau (CFPB) and other agencies place a lot attention of fair lending and disparate impact. Many lenders have a difficult time finding enough resources to examine and process all of the available data to get a thorough understanding of their “footprint” and exposure for a fair lending claim.
Milliman developed a Fair Lending Algorithm to process loan-level application data collected from the Home Mortgage Disclosure Act (HMDA) datasets to produce results that identify potential areas where underwriting denial decisions indicate that disparate impact may have occurred for your institution.
Our results highlight geographic areas with the highest risk of a potential fair lending violation. These geographic areas often warrant further review, including looking at specific loan files or branches.
We work with lenders to understand, identify, and mitigate fair lending risk.
Freddie Mac and Fannie Mae (the GSEs) issued guidance beginning in September 2012 concerning changes in their respective representation and warranty framework. The changes, effective for loans acquired by the GSEs on or after January 1, 2013, require lenders to report defects on various samples of loans delivered to the GSEs. Milliman helps our clients design and implement statistically-based quality control sampling processes. We work with clients to design methodologies to leverage these reports to monitor and mitigate your risk of future repurchases.
Understanding the GSE Samples
The GSEs and the Federal Housing Administration (FHA), through self-assessments performed by mortgage sellers, use sampling to monitor the quality of loans purchased. Specifically, the GSEs and the FHA require sellers to perform self-assessments on defects for loans purchased by the GSEs or insured by the FHA. The GSEs define three types of required samples to monitor defect rates:
- Random sampling
- Discretionary sampling
- Targeted sampling
Random sampling. Random sampling is a type of sampling where the user sets the desired number of loans to be selected for review. One observation out of the entire population is randomly selected, usually using a random number generator, until the sample size is full. The purpose of random sampling is to develop a sample that is representative of the population; by randomly selecting a loan from the population, we expect, given a large enough sample size, any analysis on the sample is representative of the population.
Over each 12-month period, the random sample must include the full scope of:
- Product lines
- States of operation
- Branch offices
- Third party originators
- Loans with high risk characteristics
The GSEs require that at least 10% of the loans delivered to the GSEs are subject to random sampling.
For sellers with annual production in excess of 5,000 home mortgages per year, the seller may replace the 10% rule with a statistical sampling methodology that ensures a 95% confidence level with a 2% annual margin of error. Similarly, lenders who originate and/or underwrite more than 3,500 FHA loans also have the option of replacing the 10% rule with the 95%/2% statistical random sampling. Milliman can help your organization reduce the required sample size by developing a statistically-based methodology.
Discretionary sampling. Discretionary sampling is a non-random sampling process where a seller selects specific loans from their portfolio for review. Guidance from the GSEs state discretionary sampling should be used in the following instances:
- Review of loan production from a new employee, branch, or third party originator (TPO)
- Validation of the standards underlying new products
- Requests from the GSEs
Targeted sampling. Targeted sampling is a second type of non-random sampling process where an originator selects specific loans from their portfolio for review. Guidance from the GSEs and HUD state that loans that become 60 or more days delinquent in the first six months after the note date, defined as Early Payment Defaults (EPDs), must be reviewed under a targeted sampling framework.
Benefits of statistical sampling
Sellers with annual production of 5,000 loan or more to the GSE’s or 3,500 FHA-insured loans should be using statistical sampling to manage their defect risk. Statistical sampling provides an accurate representation of your defect rate while minimizing the required resources.
For example, a lender with annual production of 60,000 loans could reduce their annual QC costs by over $500,000 through the use of statistical sampling compared to a 10% sample.
In addition to statistical sampling, Milliman also helps clients manage their QC review data and leverage that data to improve the quality of their future business. The risk of a repurchase is a significant financial risk associated with loans sold to the GSEs or insured by the FHA. The best way to efficiently protect oneself from that risk is to identify the sources of repurchase risk prior to GSE or FHA involvement. Milliman helps mortgage companies leverage their self-assessment reports in order to minimize this risk through our Milliman Loan Quality Score tool.