Insight into insurtech trends with Meera Krishnamurthy, Cognizant

Meera Krishnamurthy, Cognizant’s Senior Vice President and Strategic Business Unit leader for Insurance, North America.

Cognizant

Meera Krishnamurthy, Cognizant’s senior vice president and strategic business unit leader of insurance, has over two decades of digital insurance and financial service experience. She joined Cognizant in 2005 and has since held several roles in the company’s insurance unit. In her current role, Krishnamurthy participates in setting Cognizant’s insurance unit goals, prioritizes the unit’s investments, and maintains client relationships. Digital Insurance met with Krishnamurthy to discuss her thoughts and insights on digital trends in the insurance industry and insurtech space. 

The changing role of insurtechs
According to Krishnamurthy, insurers are acknowledging the staying power of insurtech and its valuable ability to disrupt the insurance industry. Insurtech companies are, however, typically founded to target a specific pain point for insurers – and Krishnamurthy believes that this may no longer be enough. 

Insurtechs are starting to recognize that their digital solutions may need to be “more intertwined with what the insurers are trying to solve, because a tech in itself cannot yield much to the industry,” Krishnamurthy says, adding that she continues to see more insurtechs hiring talent such as actuaries or data scientists to better integrate their solutions with service provided by insurance companies to solve this issue. 

She also sees insurance companies wanting a play in industry disruption. Krishnamurthy describes this as a “don’t-miss-out attitude,” and notes that many insurers have started to invest in and arm the insurtechs with potential for impact. For insurance companies, it is “important to be agile in nature and rapid in their thinking,” says Krishnamurthy. “I think it gives them the advantage.” 

She is also seeing the dawn of the “insurtech 2.0” – a term referring to the wave of insurtechs leveraging industry experience with digital transformation, to advance their underwriting capabilities. This new era of insurtech 2.0 may be what the industry needed, according to Krishnamurthy, as insurtechs are hiring more insurance experts and insurance companies are bringing in more external tech talent. 

“Insurtech 2.0 is a blessing… Some of [the insurtechs] have gone public too soon in my view – too soon, too quick. And I’m now realizing that for them to scale, they need these experts,” states Krishnamurthy. “Then you have the mid-market insurers and the large insurers. The mid-market insurers are a bit nimbler in using technology than the large ones, but they all fight for the same book.” 

As larger insurers are adapting to this insurtech 2.0 world, we will continue to see more consolidation and possibly see some industry-leading solutions as a result, she adds.

Digital trends 
In insurance, data is the bottom line – but how do insurers use data in a meaningful way? 

Krishnamurthy believes that AI and analytic capabilities are crucial to reading, interpreting, and utilizing data in underwriting risks and accelerating claims and underwriting processes. 

“Insurance is all about data… ‘AI’ and ‘analytics’ – you will hear these buzzwords,” explains Krishnamurthy. “Why? What is insurance measured on? One is loss ratio, two is investment returns, and three is expense ratio. If you put all of these together, data can influence all three.” 

We may see more insurers adopting the technology to better use this data, acquiring “the tech to ingest the data, take it in and put it in a form that people can consume. There are bits and pockets of [technology] investments, but moving more to that value chain – a claim value chain, an underwriting value chain, or even for a singular product or a monolith product. That’s where investments are being made now,” Krishnamurthy explains. 

Machine learning is one form of AI trends insurers are adopting to produce more intelligent, accelerated processes – especially in policy servicing. 

“It could be from issuance to quoting, to binding, to distribution, to claims. That’s where a lot of ML is being used today. If you have a nice IoT deployed and you want to read from that data and put it in and allow a machine to process and straight through, that’s ideal for anybody,” states Krishnamurthy. 

Challenges facing the industry
One issue that persists is that though there is an increase in disruptive innovations introduced to the industry, the act of integrating these new technologies into insurance services – and doing so rather quickly – continues to be a challenge for insurers. An insurance company may recognize the importance of a new technology, like catastrophe modeling as an example, but struggle with weaving the resulting data into the claims adjudication process. 

“That [challenge] is happening today as we speak, it’s still not there yet. There are leaps and bounds to get to where they want to be,” explains Krishnamurthy.

This difficulty is certainly exacerbated by the talent challenge and Great Resignation impacting the insurance industry. Attracting and retaining tech talent has become a major obstacle for many insurers, and acquiring top tech talent is essential for understanding and translating data in a meaningful way. 

“On one hand, there is technology. There is analytics. There is ML. You can use it, but who has the traditional knowledge and, at best, some bit of technology knowledge to bridge it? There is a dearth of data scientists in the insurance world today… You need somebody to translate the data to make meaningful decisions,” explains Krishnamurthy. “Insurers want to use technology to make meaningful decisions and be cost competitive and attractive to their clients…You need humans to take that and make the technology readable.”