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Insurance Case Studies


Title
New Customer Acquisition

Objective
Develop predictive models that identify potential new sales

Industry
Insurance

Outline
Utilize both logistic regression and decision tree models to identify potential new customers based on purchase history and demographic and geographic factors.    The results of the models were the basis for targeting direct mail campaigns.  The implementation of these models resulted in a 20% higher response and sales rate versus random mailings.
 
 

Title
Customer Lifetime Value

Objective
Determine the lifetime value of current customers

Industry
Insurance

Outline
Develop logistic regression models to predict customer retention based on purchase history and demographic and geographic factors. Applied the retention likelihoods along with profitability per policy over time to determine a present value for each customer. The results were used for multiple purposes to include potential additional product sales and economics of campaign spending.


Title
Fraud Detection

Objective
Identify claims that are potentially fraudulent

Industry
Insurance

Outline
Develop logistic regression models of past claim characteristics to identify those that are potentially fraudulent.  Results used to identify new claims that require closer investigation for possible fraud.