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Private sector Tata AIA Life Insurance, which has been betting on technology in a big way, is now using data analytics and tie-ups with credit bureaus to give insurance coverage without the need for medical check-ups.
“In the last few years, we have invested a lot in analytics and data-driven underwriting. What we are able to do today is identify a consumer based on his application and provide him insurance coverage up to a very large sum without even asking him to go for medical tests,” said Yusuf Pachmariwala, Senior Vice-President and Head of Operations, Tata AIA Life Insurance Company. Depending on the age of the customer and the channel used, the insurer is able to issue policies of up to ₹2 crore to ₹3 crore without medical check-ups, he said.
Predicts behaviour
The analytical models help predict the behaviour of the customer and on occasion also get a doctor to speak to the customer, he further said
Additionally, the insurer has also tied up with credit bureaus such as Transunion Cibil and Experian and underwrites policies based on some of the data it gets from them.
According to Pachmariwala, the use of analytics and data has also helped the insurer in its claim-settlement process.
“Because of all these robust models being implemented, we have been able to identify a lot of risk even before it actually comes to us, rather than at the underwriting stage,” he said, adding that it wants to use these analytical models at the underwriting stage for proper underwriting so that it does not have to decline any claims.
The insurer has a claim settlement ratio of 97.99 per cent between April 2018 and January this year.
Elaborating on further innovations by the company, Pachmariwala said it is now focussing on launching Artificial Intelligence chatbots, which can, sort of, automate and respond to the customer.
Similarly, the insurer is also working on call centres, where it can deploy bots to respond to consumers.
“We have been focussing on innovation for four to five years,” he said.
He added that the insurer is now also looking at how analytics can be used in the post-issuance phase to predict the requirements of the customer and proactively service them.
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