SAN DIEGO, CA--(Marketwired - January 17, 2017) - PointPredictive, Inc. announced today the launch of a new mortgage fraud score that provides an enhanced, real-time assessment of misrepresentation risk allowing lenders to reduce the number of applications currently selected for detailed fraud reviews by investigators.
This score should be requested in parallel with, and used in combination with, credit scores to ensure that the lender's underwriting policies are informed by the likelihood of misrepresentation early in the loan process. PointPredictive research confirms that in the absence of a fraud and misrepresentation score, credit scores alone cannot accurately predict repayment of all loans.
Most mortgage lenders have processes that are bogged down by reviewing inaccurate and unnecessary fraud alerts after much of the credit underwriting has been completed. This slows down the lending approval process and ultimately does not deliver the consumer experience or the loss mitigation lenders want. The service launched today helps to solve that problem by reducing fraud-related false positives by at least 40 percent while providing enhanced real-time targeting of misrepresentation risk that would lead to future financial losses due to default and repurchase.
"When we started PointPredictive, our vision was to leverage new predictive modeling techniques to help industries evolve," says Joe Jackson, Head of Partner Relations. "Mortgage lending is one of our key markets because while there is so much data available during the lending process, it is not used optimally to identify fraud risk instantly so it can be resolved."
This new cloud-based, predictive scoring service relies on information readily available at the time of the application and can score more than 3,000 applications per second. The mortgage lender receives real-time notification of any potential misrepresentation along with an indication of what types of information will need to be validated with the borrower.
These features allow lenders to insert this service directly in their time-sensitive processing flows, streamlining most loans for faster approval while only flagging the most risky loans for costly and slower fraud prevention efforts.
"Most mortgage applications do not have a high risk of default or repurchase due to applicant misrepresentation and their processing path can be streamlined. Our new model provides an objective and statistically sound way to help lenders do that," says Tim Grace, CEO of PointPredictive. "We use sophisticated machine learning models that provide lenders a 'Go / No-Go' decision about misrepresentation review in milliseconds. With the launch of programs by many leading lenders designed to simplify and expedite the customer's application processing experience, this new scoring service is now critical for the mortgage industry."
PointPredictive is offering a proof of concept evaluations to lenders to demonstrate the new model's effectiveness. As part of the proof of concept, a lender can score historical applications (with known outcomes) to understand the model's accuracy in identifying fraud risks that led to a financial loss. Given the speed of the scoring service, we can review one to two years of a lender's full application volumes very quickly. PointPredictive will also provide participating lenders with a detailed analysis of the statistical soundness of the model including review rates, detection rates and false positive rates of the model.
If you would like more information about this new predictive service or the proof of concept program, please contact email@example.com.
About PointPredictive, Inc.
PointPredictive, Inc. is a leading provider of fraud solutions to banks, lenders and finance companies. It solves the billion dollar fraud problems of auto lending, mortgage lending and retail fraud with the latest technology platforms, smarter science and business experience by leveraging big data with analytic models. Located in San Diego, Calif., more information about PointPredictive can be found at www.pointpredictive.com.