Big50-2017 Startup Spotlight: PointPredictive

PointPredictive

What they do: Provide Pattern Recognition Fraud Models that “instantly scan application risk for a mortgage lenders, auto lenders and retail merchants.” 

Problem they solve: Online or off, fraud is a MASSIVE problem in our economy. Auto loan fraud is a $6 billion a year problem. Mortgage Fraud is estimated at $20 billion annually, while retail fraud siphons off $32 billion a year from businesses.

How they solve it: PointPredictive’s goal is to “eliminate fraud through machine learning.” The startup’s software reduces fraud through Pattern Recognition Fraud Models that help lenders target the biggest risks. PointPredictive builds these models using millions of historic transactions, applications, and examples of fraud.

Big50-2017 Group 3 vote winner @PointPredict fights fraud w/ machine learning http://wp.me/p330ZZ-hO #Big50 #startups Click To Tweet

“Our pattern recognition models can reduce fraud losses by 50% or more,” said Frank McKenna, PointPredictive’s Chief Fraud Strategist. For instance, to combat auto loan fraud, lenders can use PointPredictive to scan for hundreds of fraud risks before funding a loan.

Headquarters: Del Mar, CA

CEO: Tim Grace. Before PointPredictive, Grace served as CEO of BasePointAnalytics, and, prior to that, General Manager for Fiserv Risk Product Lines.

Year Founded: 2015

Funding: Self-funded.

Competitors include: Riskified, Signifyd, Feedzai, and Trustev are the most direct competitors, but this is a very crowded space. Others they could compete against include Fraud.net, ThreatMetrix, and Socure.

Why they’re in the Big 50-2017:  As fraud metastasizes across both online and offline channels, cyber-security and fraud prevention will remain hot. PointPredictive is positioned in a ridiculously competitive space, but we believe that it will remain a sector with room for many competitors for the foreseeable future.

PointPredictive also won the group 2 voting round, which cemented their spot in the Big50-2017 lineup.