Warwick Analytics is in the market for auto finance partners, following its participation in BMW Financial Services U.K.’s Innovation Lab, Auto Finance News has learned.
The predictive analytics provider operates in various industries, including auto, but in the past it has mostly worked with manufacturers. Warwick has a partnership with Jaguar Land Rover, among others.
But now, Warwick is starting to get into the auto finance business, after testing use-cases of its predictive analytics with BMW Financial.
Warwick is one of five startups that participated in BMW’s 10-week Innovation Lab, which concluded in December 2016. So far, three startups have secured commercial contracts with BMW, including Cazana, Divido, and Wrisk.
While Warwick has not secured a commercial contract with BMW Financial Services U.K. yet, the company hopes “to continue the work we’ve done for them in the future,” Warwick’s Chief Executive Dan Somers told Auto Finance News.
Warwick Analytics specializes in digitally analyzing big data for its clients. The company hopes the relationships formed at BMW will help the team understand the auto finance industry and form new partnerships moving forward, Somers said. Warwick’s analytics can be used in the auto finance space to help lenders and captives improve customer service, provide market insights, help detect fraud, and more.
“With the work we have done with BMW and other car companies — we want to bring that source of customer-journey dynamic insights to the automotive world,” Somers said. “And then there is a dual benefit: The customer gets a better experience and the supplier gets a better opportunity to increase [consumer] loyalty, upsell, and [increase] cross-sell opportunities — and to improve its product, or service along the way.”
Additionally, Warwick is also uniquely positioned to provide analytics and data as autonomous vehicles come to market, such as predictive maintenance analytics, Somers said.
“This is a really exciting time for us, because the more autonomous devices become — not just automotive, but all devices — and the more data there is, the more possibilities for things to go wrong,” Somer said. “So we can help on the predictive maintenance side.”
