KAR Auction Services said Tuesday it has launched a Data Science Solutions Group that aims to help customers improve business decisions through analytics and predictive modeling.

KAR DataSci will be led by Dr. Huey Antley, who was most recently vice president of marketing analytics for KAR’s Automotive Finance Corp. subsidiary. Antley will report to KAR chief operating officer Don Gottwald.

“KAR will commit the resources necessary to develop products specific to the auto remarketing industry that enable our customers to make better business decisions,” Gottwald said in a news release. “The KAR Data Science Solutions group is actively applying data science and predictive modeling to our business, leveraging the rich data assets collected over many years to optimize decisions in vehicle remarketing.”

‘Billions of data points’

The group will take “billions of data points” gleaned through KAR’s operations across the wholesale spectrum, and then generate and apply predictive algorithms to aid in customers’ decision-making, the company said. If you think about KAR's operations, that includes everything from whole-car auctions and floor plan financing to transportation and inspections, plus much more in-between. 

“In essence, we are bringing science to our customers to lower their operating costs, enable them to turn vehicles faster with less risk and ultimately help them be more successful,” Antley said in news release . “I am excited to lead this talented team in applying advanced mathematical and computing science to data to meet our customers’ needs and deliver real business solutions.”

In an interview ahead of Tuesday’s launch, Auto Remarketing asked Gottwald for a few examples where KAR DataSci — which will focus on the wholesale side — will come into play.

“First off, better matching supply and demand would be one issue,” he said. “If you think of the problems that a company like KAR Auction Services and our affiliated organizations (aim to solve) … at the end of the day, we help solve the problem of improving the efficiency for our customers, improving transparency and reducing risk.

“So, to the extent we can better match supply and demand — the sellers and the buyers — we can make the process more efficient, more transparent,” Gottwald said.

Another area is “pricing optimization across channels,” he added.

For instance, getting the right inventory to the right channel (be it in-lane, online or to a service like TradeRev) at the right price.

Gathering data points

As far as how bits of information are collected, KAR has a set of transactional data through its operations that span “the entire remarketing spectrum,” Gottwald said.

“We actually have the data. It’s now going beyond the historical ways of looking at data, applying — I hate to overuse the term, but — big data tools and predictive analytics tools to those data sets to find new insights and help our customers better optimize across a host of fronts,” he said.

“At the end of the day, we have the data we need right now,” Gottwald went on to say. “The difference will be in how we use it, how we present that, how we share that with our customers.”