Key Drivers and Predictive Analytics for Insurers – AICPCU Whitepaper
Article Synopsis :
Predictive analytics has been used for some time in non-life insurance underwriting, but insurers have started acknowledging the business benefits as a result of its inclusion across digital touch points. Predictive analytics is expected to help insurers in reducing marketing costs, improving client conversion ratio, maintaining brand loyalty and dealing with the complexity of new distribution channels while remaining competitive.
In its white paper on predictive modelling, The American Institute Chartered Property Casualty Underwriters (AICPCU) summarises the predictive analytics process (Data Mining, Model Development and Model Validation) and its usage in the field of marketing, underwriting, claim settlements and fraud detection by insurers.
The white paper identifies the key drivers in the use of predictive analytics by insurers:
1. Technological advances
2. Data availability
3. Insurers’ desire for growth In slow-growth markets
4. Insurers’ search for competitive advantage
The white paper also puts forward an unbiased view on the advantages and disadvantages of predictive analytics for insurers.
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Digital Insurer's Comments
It is important to note that the precision and usability of predictive analytics depends heavily on the quality of data that is fed into the model. Extending analytics beyond underwriting to marketing, CRM and product designing will pose a serious challenge before insurers as data feeds have not in most cases been optimised for modelling.Unlike underwriting data, this data feed has never been intended for modelling, hence data cleansing effort and investment should precede analytics investment and its inclusion at various touch points.
The authors point out clearly how predictive analysis is an extension to the underwriters toolset to allow the correct pricing of risk. But they also correctly identify that this capability is leading to increasing commoditisation of products. Clearly insurer without predictive tools and an active approach to risk assessment will be at a significant competitive disadvantage.
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