Meet growing needs for innovative insurance solutions while increasing operational health and improving compliance.
Manage complex risks using data-driven insights, advanced approaches, and deep industry experience.
Navigate today’s most pressing health industry challenges with a leading global expert by your side.
Deliver on the promises of the past and create smart solutions for the future.
This is a place where your ideas and insights make an impact. Where an independent, entrepreneurial spirit is an advantage. And where diversity of thought and experience makes us who we are.
Data-driven insight. Deep expertise. Transformative innovation. Since 1947, Milliman has delivered intelligent solutions to improve health and financial security.
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.
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.
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:
Over each 12-month period, the random sample must include the full scope of:
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.
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.
Our team is dedicated to analysing mortgage and credit risk, specialising in statistical, actuarial, and econometric risk-assessment techniques.
Our mortgage insurance and lender loan loss reserving framework combine our independence and depth of industry expertise.
We combine actuarial and modelling expertise with capital markets structure analysis to deliver meaningful financial feasibility studies.
We specialise in building customised and cost-effective solutions to measure and manage the risks associated with originating credit risk.
Jonathan Glowacki is a principal and consulting actuary in the Milwaukee office of Milliman. He has been with the firm since 2009. Jonathan leads a team of data scientists and developers to provide powerful information and analysis to ...
Ask the tough questions. We’re ready for them.