Predictive analytics can be applied to pricing car insurance to help insurance companies determine appropriate rates for individual policyholders. By analyzing large datasets of historical insurance claims and policyholder data, predictive models can be developed to estimate the likelihood of future claims based on various factors such as age, gender, driving history, location, credit score, and type of vehicle.  More recently, insurers have also been able to use the rich datasets from telematics sensors.  This session will provide an overview of how predictive analytics can be applied to pricing car insurance to help insurance companies make more informed pricing decisions and reduce risk, ultimately leading to improved profitability and customer satisfaction.