Predictive analytics in insurance uses historical and real-time data to forecast future events, assess risks, and make data-driven decisions.
We collect and integrate relevant data, applying AI and machine learning algorithms to analyze historical patterns, and creating predictive models to inform underwriting decisions, pricing strategies, and fraud detection.
It's about making fewer mistakes and saving money. It helps to charge the right amount for insurance, catch fraud, and handle claims.
Progressive (United States) uses predictive analytics to set car insurance rates. They analyze driving habits, like how fast you brake or how much you drive, to determine if you're a safe driver.
AXA (Global) uses predictive analytics for fraud detection. They look at claims data and use algorithms to spot unusual patterns that might indicate fraudulent claims, helping them save money.
Progressive, a U.S.-based insurer, implemented it by leveraging telematics data from policyholders' vehicles to assess driving behavior, allowing them to offer personalized auto insurance rates.
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