Risk modeling
The project focused on analyzing loss drivers in automobile insurance and developing a risk modeling framework for AMI. To assess driver risks, we proposed integrating individualized behavioral data with claims and accident histories from internal databases. Our approach involved installing the Anaconda package, assessing the quality of internal data (customers, vehicles and driving history), performing a descriptive analysis of risk factors, and implementing a model risk based on claims and the history of the insured.
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