Predictive Modeling for Fraud
Fraudulent claims are costly, but it is too expensive and inefficient to investigate every claim. Even if possible, investigating innocent customers could prove to be a very poor experience for the insured, leading some to leave the business. Using predictive modeling, you can automatically build extremely accurate predictive models to identify and prioritize likely fraudulent activity. In this session, Rajiv will go over types of problems that are good candidates for building predictive models. He will also walk through how predictive models are built and used for various types of fraud detection. Megan will share her experiences in building a predictive model for identifying fraud.
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