The Dangers Of Predictive Analytics In Life And Health Insurance
June 13, 2019 Leave a comment
Currently the health and life insurance products we buy are static in the sense that right at the beginning of the policy term the insurance company makes an assessment of the morbidity or mortality risk of the person and then agrees to insure them at agreed-upon rates.
Now imagine a scenario of continuous health monitoring and a dynamic premium that reduces when people engage in what is deemed healthy behaviour. A scenario where the insurer provides various “incentives” like discounts on gym memberships , wearables like fitbit and preventive healthcare check-ups etc.
The first time I came across such an idea,2 lines of thought came to my mind simultaneously: Read more of this post
Predictive analytics involves the analysis of large data sets ie big data ,to make inferences by identifying meaningful relationships between different variables and using these relationships to forecast what might happen in the future with an acceptable level of reliability.Predictive Analytics includes what-if scenarios and risk assessments.
The mortality risk is not the same across different sections of the population.So one of the ways in which life insurance companies have traditionally competed is by restricting their offerings to people who have lower risks of dying early and thus keeping premiums lower and/or bonuses higher.The classic example is the Postal Life Insurance plans of the past that were offered exclusively to government servants vs similar plans of the LIC that were open to all. In more recent times,insurance companies target the more educated, affluent, urban ,financially successful professional/managerial class with better living standards and access to world-class healthcare.
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