Pinpoint Predictive Inc., the leading risk assessment platform for Property and Casualty insurers, is pleased to announce a strategic partnership with Trexis Insurance, a non-standard Personal Auto carrier serving drivers in fourteen states across the U.S.

Trexis provides competitive auto insurance solutions through a trusted network of independent agents, focusing on accessibility, fairness, and fast service for policyholders seeking flexible insurance options. With this collaboration, Trexis will leverage Pinpoint's Loss Predictions to instantly assess expected loss outcomes as soon as a quote is initiated — enabling Trexis to tailor Payment Plan offerings to each individual, right from the start.

"Pinpoint's prediction models have allowed us to reduce down payment requirements for many customers, which has helped increase our premium production," said Joel Witt, VP Actuarial Services at Trexis Insurance. "Our project timeline from initial contact with Pinpoint to live production was incredibly short – they have really made the entire process simple from project concept all the way to implementation."

Pinpoint's platform allows Trexis to quickly operationalize predictive insights without requiring heavy IT work or historical loss development — accelerating deployment and minimizing its resource lift. Delivered via API directly into Trexis' existing quoting workflows, Pinpoint's Loss Predictions enable Trexis to drive better outcomes earlier in the lifecycle and enhance customer experience by offering the most suitable billing options upfront.

"Pinpoint is proud to provide Trexis with the cutting-edge technology they need to continue innovating in the personal auto market," said Trevor Giroux, Head of Client Services at Pinpoint Predictive. "Our work together will help Trexis strengthen profitability while creating a better purchasing experience for drivers — a win for both customers and the business."

This collaboration marks another milestone in Pinpoint's growing adoption across P&C carriers nationally, demonstrating the measurable value and speed of deployment that predictive loss signals provide.