Emphasis on Predictive Analysis can Enable the Indian Insurer to Gain an Edge in a Fast Changing Economy

Insurance is a form of risk management used to hedge against a contingent, uncertain loss. Traditionally insurers used Mathematical and Statistical concepts related to Actuarial Science to assess risk, and thus, sold policies. Actuarial Science focused, in turn on the analysis of mortality, the production of life tables and the application of compound interest. Prior to the 90s, PSU insurers enjoyed an arena devoid of competition and thus could sustain themselves, marketing policies based on traditional theories of Actuarial Science alone. Post 90's the Indian Insurance Sector opened its doors to private participants. These players, aggressive to gain their market share, used multiple media channels to touch their customers profitably. Meanwhile the average Indian customer metamorphosed into an intensely aware person with an increasing financial power, as Customer Relationship Management took center-stage. Also mortality statistics are undergoing change, considering the constantly enfolding lifestyle of the global citizen. The earlier product-centric insurers now had to be customer-centric and design products tailor-made for the regular Indian customer.

In such a changed scenario, saved customer-data became relevant and predictive analysis of such data took an edge over traditional Actuarial Science in guiding the Indian Insurer in designing their products. This paper, shall analyze through available secondary data, how predictive analytics of customer data can impact target marketing and benefit design in the Insurance Sector as competition grows relentlessly.