Predictive Modeling for Life Insurance – Deloitte Report
Article Synopsis :
Predictive modeling is being used to align marketing, distribution channels, products and services with customer requirements/preferences in order to improve hit ratio, customer engagement and retention by insurers. Key to realizing the business benefits of predictive modeling in the insurance sector is its successful implementation.
In the report titled “Predictive Modeling for Life Insurance”, the Deloitte team describes how predictive modeling techniques can be used to improve decision making processes in the areas of underwriting and marketing, resulting in more profitable and efficient operations. The report also illustrates the general processes that can be used to implement predictive modeling in life insurance underwriting and marketing. The modeling process involves following steps as per the report:
1. Collection and organization of Data
2. Variable Generation
3. Exploratory Data Analysis
4. Variable Transformation
5. Partitioning Model Set for Model Build
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Digital Insurer's CommentsLife Insurers need to reconsider reservations against deployment of predictive modeling such as competing internal priorities, lack of IT infrastructure and complexity concerns. Business benefits surely outweigh the implementation concerns as driving forces like data availability, technological advancement, and availability of skilled workforce have made the job easier – although establishing predictive modeling capabilities is not a trivial exercise.
P&C insurers have already shown the value of predictive modeling and Life Insures should follow suit in order to gain competitive advantage.
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