SOURCE: PointPredictive Inc.

PointPredictive Inc.

October 25, 2016 07:00 ET

PointPredictive Finds Fraud Follows Similar Risk Patterns in Auto Lending and in Mortgage Lending

New White Paper Available: Industry experts and data scientists find that patterns of early payment default on auto loans are similar to what the mortgage industry experienced before the mortgage crisis

SAN DIEGO, CA--(Marketwired - October 25, 2016) - PointPredictive, Inc. a leading provider of machine learning fraud solutions, today announced the results of a new study that detected high levels of fraud in early payment auto loan defaults. The study found that by scoring auto loan applications with models built to detect fraud, lenders could detect 50 percent or more of their early payment default (EPD) prior to funding than if they relied on traditional credit scores alone.

"Our analysis and experience suggest that many auto loans that default within the first six months have fraudulent misrepresentation on the loan application," indicates Tim Grace, CEO at PointPredictive. "When we ran fraud pattern recognition models on the application information provided on EPD loans, we found strong evidence of fraud. This is the same type of behavior mortgage lenders discovered prior to the mortgage crisis when it was determined that up to 70 percent of mortgage EPD was fraud related. The study confirms that using credit scores alone cannot detect fraud or risk of default."

The study encompassed data from millions of auto loan applications submitted by dealers all over the US across all vehicle types. PointPredictive auto fraud models analyzed each loan application and gave it a fraud score. While built to detect fraud, scientists were surprised to find that it did extraordinarily well in the detection of early payment default, a term lenders use to indicate when loans default within the first six months.

The PointPredictive analysis proved that fraud scoring could:

  • Detect 14 times more fraud for lenders than current solutions while flagging less than five percent of the total applications.
  • Prevent 50 percent or more of a lender's early payment default losses by identifying those applications that had misrepresentations that would lead to loss.
  • Identify risky auto dealers that submit multiple fraud loans up to three months sooner and reduce losses due by 70 percent due to early detection of bad players.

In 2007, a study by BasePoint Analytics found that between 30 and 70 percent of mortgage loans that defaulted within the first six months contained serious misrepresentations on the original application. These misrepresentations on borrowers' income, employment, collateral or even intent to occupy had a material impact on the performance of the loan but were often considered "hidden fraud" since they were never detected in the application process.

Auto lending fraud, like mortgage fraud, occurs when information on an auto loan application is intentionally misrepresented either by the borrower, a sophisticated fraud ring, or an unscrupulous dealer. When information is manipulated and the lender does not know about it, they may underwrite the application assuming the information is valid. Intentional fraud presents a problem for auto lenders since loans that have misrepresentation are more likely to result in EPD.

To counter auto loan fraud and better detect EPD, PointPredictive Auto Fraud Manager uses pattern recognition, a technique that scientists have perfected to detect fraud based on historical data mining. The solution works by analyzing historical patterns of fraud, EPD and risky dealer activity and then scores each application as it comes in from a dealer. Lenders are automatically alerted when an individual application has a significant number of anomalies or fraud patterns related to the income, employment, collateral, borrower or dealer. The lender can review the application and take action before it is approved. Over time, if a particular dealer submits many applications with similar fraud patterns, the solution will alert the lender to that as well so they can take the appropriate action.

The full results of the study have been published in the PointPredictive whitepaper, "You Can't Fight Fraud with Credit Risk Tools," available at no charge by emailing info@pointpredictive.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, CA, more information about PointPredictive can be found at www.pointpredictive.com

Contact Information

  • Media Contact:
    Gina Ray
    Ray Public Relations
    949-370-0941
    gina@raypr.com