Underwriting solution helped a leading insurance client improve campaign strategy
Client is a leading insurance services provider based out of US, primarily dealing with term life insurance and retirement market.
- Underwriting in insurance is about deciding how much of the risk should be covered by the financial institutions like insurance companies, based on certain factors.
- Our client initially had a black box solution to perform the Underwriting process, which gave no clarity on the scoring process. The reinstatement process which determines the quality of medical report was not clear. This had an impact on the policy consideration decision making.
- The scoring process is a black box methodology, which makes it difficult to understand the process.
- Data acquisition is manual and time consuming
- Real time data are not taken into consideration
- Lack of means to follow insured’s life development.
Ameex developed a solution which extracted and stored data in a structured manner and built the model to generate the score. Our solution gives a rationale for the score, which helps the client in better assessing the risk of default of a policy holder. This also gives the flexibility to run wellness campaigns targeting appropriate groups of customers.
- Factor Mapping was done to identify the possible variables leading to insurance claim.
- Hypothesis matrix was created and signed off, forming the basis for our modeling and subsequent analysis
- Data was extracted from the client’s environment and stored in a relational format
- Feature engineering and Data cleaning was done before feeding into the model
- The output of the model was displayed on the front end
Features: This application includes
- Option to enter the SSN Number (mocked-up for the purpose of this demo) and view the patient details.
- View the results of EDA and the relationship of all the significant factors with respect to the possibility of claim.
- A white box solution which gives the score and the significant factors behind the same.
- Client can better assess the risk of default of a policy holder, designing targeted campaigns resulting in trimming of marketing costs
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