+1-786-628-7980
Sign Up/Sign In 
SAN DIEGO, Calif June 29, 2020 – Point Predictive Inc., the San Diego-based company that provides machine learning solutions to lenders, announced today that the U.S. Patent Office has granted the company a patent for the Ai technology that powers DealerTrace – their dealer risk scoring technology. The patent covers the core underlying technology and data model providing monthly risk assessments on over 70,000 car dealerships nationwide.
“Point Predictive continues to advance auto lending fintech with Ai,” indicates Tim Grace, CEO of Point Predictive. “Our patented approach to identifying both high-risk and low-risk dealers is transforming the way that lenders manage their relationships with car dealers. Before this technology became available, lenders would often have a lag of three to six months before discovering which dealerships are performing as expected and which are not; this lag results from relying on loan default information as the foundation of current dealer monitoring processes. Our dealer scoring is a big advancement in this process and is informed by real-time application data from our nationwide fraud consortium that helps determine whether or not a dealership’s applications are likely to result in unacceptable levels of fraud or early payment default due to material misrepresentation. Conversely, we can also use this technology to help lenders understand which dealers have low-risk profiles so they can enhance their relationships with those dealers by clearing stipulations automatically or offering incentives to encourage more loans from those dealers. Dealership owners can also use this information to proactively monitor practices occurring within individual dealers. They can take timely action within the dealerships to avoid possible lender actions or eventual loan pushbacks.”
U.S. Patent number 10,692,141 – Multi-Layer Machine Learning Classifier with Correlative Score – recognizes Point Predictive’s unique approach to identifying car dealership risk by profiling their application submissions to each lender, scoring each application they submit for risk, and then clustering those applications across the fraud consortium to identify a final dealer risk score. The score, which is provided in the company’s DealerTrace solution, helps lenders identify risky dealerships and avoid losses up to 120 days sooner than using a performance-based scorecard approach.
DealerTrace leverages the underlying pattern-recognition technology of the fraud and early payment default detection analytics of Auto Fraud Manager to create dealer-centric risk assessments based on lender-reported application and outcome data. Fuzzy-matching techniques are used to recognize the same dealer – perhaps operating under different names or with slightly different demographic characteristics – across multiple participating lenders. This allows DealerTrace to form a cross-lender consortium-level view of each dealer’s risk characteristics that is beyond what any individual lender could do on its own. It also enables participating lenders to benchmark their book of loans with a dealer against the consortium’s view of that dealer – this is especially useful to detect instances of “adverse selection” where a dealer may be routing its riskier loans to certain lenders.
For auto lenders and dealers that are interested in more information about DealerTrace, please contact info@pointpredictive.com.
About Point Predictive Inc.
Point Predictive helps automotive, mortgage, retail and personal loan finance companies to identify the consumer applications with truthful and reliable information without the intense interrogation and verification of data caused by lower tech solutions currently in use. Highly regarded as the most trusted fraud and misrepresentation analytic solution providers, Point Predictive has transformed that trust to enable lenders to fund more loans to more consumers simply. Point Predictive uses big data powerfully orchestrated from millions of examples of true and falsified loan applications, billions of derived proprietary data elements, and scientifically selected 3rd party data sources to build powerful machine learning models with the added natural intelligence of human experience. Located in San Diego, California, more information about Point Predictive can be found at www.pointpredictive.com.
