Tricolor's Machine Learning Tech Is Reducing Its Reconditioning Costs | Auto Finance News | Auto Finance News

Tricolor’s Machine Learning Tech Is Reducing Its Reconditioning Costs

Tricolor Chief Executive Daniel Chu presents at the Auto Finance Innovation Summit (photograph by Nicole Casperson)

SAN DIEGO — The machine-learning technology deployed by Tricolor Auto Acceptance has cut its vehicle reconditioning costs, Chief Executive Daniel Chu said during the Auto Finance Innovation Summit here on Wednesday.

Tricolor provides the reconditioning centers that service its chain of retail dealerships with technology that determines the most cost-effective source of car parts. The lender leverages its partnership with AutoZone Auto Parts to test the machine learning capabilities.

“We’re testing technology that can source parts for our body shop — recyclers versus factory parts versus AutoZone versus other vendors and suppliers,” he added. “Through machine learning, we’ve already achieved some cost efficiencies with [reconditioning] processes.” 

Of the $1,800 Tricolor spends reconditioning every vehicle it purchases before selling, the parts component is about half the cost. “We think we can make a meaningful dent in that,” he said.

Tricolor has leveraged machine learning technology within its call center, underwriting model, and risk-scoring capabilities.

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