Improving lending practices helps consumers, economy

Researchers use SAS to forecast effects of lending practices

The not-for-profit Center for Responsible Lending plays a key role in researching the impact of lending practices on consumers. Its research on payday and subprime lending has helped regulators understand how these practices affect both consumers and the economy, including a 2006 prediction that the subprime mortgage market was headed for a meltdown. SAS is the analytics engine that supports the Center's research.

Our goal is to help level the playing field so that scrupulous lenders can stand out and win on merit. SAS helps us do that.

Keith Ernst
Director of Research


The Center routinely conducts research that combs through 30 million to 50 million Home Mortgage Disclosure Act records to spot patterns and trends. Before using SAS, it took hours to run a program. Research that required multiple calculations often took days to process. One mistake would set a researcher back a full day. Because the Center was involved in a state-by-state review of the impact of lending laws, it needed a better statistical solution.

Results with SAS®

  • Calculations that took hours now take minutes. SAS allows the Center to create "what if" scenarios that help it do a better job of understanding how regulations might affect the mortgage marketplace.
  • By looking at the performance of subprime loans across local markets, the Center predicted the subprime mortgage meltdown two years before it happened. Its analysis showed that one in five subprime mortgages in real estate hot spots like Southern California and Las Vegas was likely to default before the market bubble burst.
  • The Center was able to expose the flaw in the argument that prepayment penalties benefit consumers because those loans have a lower interest rate. By analyzing data available at the national level and using regression models, the Center discovered that the mortgage rate "break" was diverted, most likely to third parties like mortgage brokers. New regulations greatly restrict prepayment penalties.
  • The Center was able to show that state laws enacted to prevent predatory mortgage lending work as intended to reduce abusive loan terms without impeding credit flow. It also analyzed payday lending in California and discovered that such lenders are nearly eight times as concentrated in neighborhoods with the largest share of African-Americans and Latinos.
  • Using SAS, the Center has automated the updating of statistics on mortgage conditions. This makes the organization a go-to resource for policymakers, researchers and journalists seeking information about the state of the housing market.

Making a name for itself

The quality of its research has earned the Center a major role in testifying before Congress and the Federal Reserve. "Our input during the policymaking processes will help shape financial regulation going forward,'' says Keith Ernst, Director of Research for the Center.


Produce fast, accurate forecasts about the impact lending laws have on consumers across the 50 US states


SAS® Forecasting


  • Reduces program run time from 12 hours to minutes.
  • Fosters complex analysis that led regulators to restrict prepayment penalties on mortgages and other predatory lending practices.

The results illustrated in this article are specific to the particular situations, business models, data input, and computing environments described herein. Each SAS customer’s experience is unique based on business and technical variables and all statements must be considered non-typical. Actual savings, results, and performance characteristics will vary depending on individual customer configurations and conditions. SAS does not guarantee or represent that every customer will achieve similar results. The only warranties for SAS products and services are those that are set forth in the express warranty statements in the written agreement for such products and services. Nothing herein should be construed as constituting an additional warranty. Customers have shared their successes with SAS as part of an agreed-upon contractual exchange or project success summarization following a successful implementation of SAS software. Brand and product names are trademarks of their respective companies.

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