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19 October 2021Insurance

TigerRisk partners with Pinpoint Predictive to improve risk selection

Reinsurance broking and risk/capital management firm  TigerRisk Partners has partnered with Pinpoint Predictive, an analytics platform that uses proprietary data and deep learning algorithms to help property and casualty insurers make better decisions.

Pinpoint’s AI has modeled the behavioral propensities of the adult population of the US. Its automated platform produces risk scores for individuals as well as explainable analytics revealing the factors that drive specific human behaviours.

These new capabilities allow insurance companies to significantly boost key predictions at the time of quote, including claims frequency, SIU referral, litigation propensity, cancellation, and home-inspection outcomes.

The platform helps optimise front-end processes across marketing and distribution channels, including aggregators, agency book rolls, MGAs, brokers, and direct.

Bill O’Keefe (pictured),  TigerRisk’s head of strategy, further explained: “Pinpoint is a personality-focused data enrichment platform that provides new predictive power to carriers and MGAs, leveraging the latest in behavioral economics and artificial intelligence, all in a privacy-safe fashion. Factoring individuality into predictions can save $100s of millions per year. This partnership demonstrates TigerRisk’s commitment to supporting cutting-edge technology companies as well as our desire to bring value-added opportunities to our clients.”

Scott Ham, chief executive officer of Pinpoint, said: “We are thrilled to be partnering with TigerRisk to offer their clients our unique and impactful platform. Personalizing predictive analytics with Pinpoint provides a tremendous opportunity to treat people as true individuals with future potential.”

Avi Tuschman, founder and CIO of Pinpoint, added: “This partnership will allow Pinpoint to expand its reach and bring individualized intelligence to leading P&C carriers, enhancing their risk selection by making better forward-facing predictions.”

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