Life insurers have been spending heavily on computers and software for generations, and they’re still hungry for more.
As hard as times may be, most of the 36 life insurers that participated in a recent Novarica survey said they’re planning to maintain their information technology (IT) budgets, and several said they’re on track to increase IT spending.
Srikant Venkatesh, a strategic client executive for banking, financial services and insurance at Tata Consultancy Services (TCS), helps meet that demand.
TCS is an arm of Tata Group, a Mumbai-based company that worked in the 1980s to introduce the idea that U.S. and European companies could farm some of their IT and back office support work out to companies in India.
TCS is now one of the biggest IT companies in the world, without about 446,000 employees and the equivalent of $21 billion in 2019 annual revenue.
One of the company’s major projects is an effort to help Aegon N.V. modernize the systems supporting administration of Transamerica’s U.S. insurance and annuity business lines.
Here are seven things Venkatesh said about how he sees life insurers’ and other insurers’ technology needs, drawn from a telephone interview conducted last week.
1.Banking tech and insurtech are different.
Insurance “is definitely behind the banking industry,” Venkatesh said.
That’s especially true when insurers are compared with smaller, more agile banking companies that have no legacy systems to worry about, he said.
2. Life insurers and other insurers are different.
Venkatesh said the state of life insurers’ systems is different partly because what life insurers do is different. In life insurance, he said, “all the companies are built on a promise that will be kept 70 years from now.”
3. Life insurers are made to buy insurtech companies.
Big life insurers have plenty of great tech people, and they have plenty of data, Venkatesh said.
“They’re data rich and information poor,” he said.
One reason life insurers tend to have such poor information is that they have a hard time getting data out of their old systems and cleaning up the data in such a way that it’s fit for analysis, he said.