This blog gives you a subject expert and a thought leader’s two cents about the new-age insurance needs and the prospects of AI in insurance.
Our previous blog brought to you the top trends and priorities for insurance businesses identified by Stuart Rose, subject expert and strategic advisor at Aite-Novarica. This week, we bring to you the outlook of Stuart and Maha Santaram, thought leader and Aspire Insurance practice head, on the industry’s unique needs for this age and prospects with AI.
Explaining how unique the insurance industry is, Stuart Rose, subject expert and strategic advisor at Aite-Novarica, pointed out that it is the only product that perhaps the manufacturers – the insurers – do not know how much it costs. “Insurers do not know with how much frequency it is going to be used or cost them.” So, it leads to a customer conundrum: How do you engage your customers when you don’t know what they might need? Some insurers seem to be tackling this unknown with digital solutions.
Explaining the need, Maha Santaram, the practice head of insurance at Aspire Systems, said, “Seamless experience across channels is the predominant expectation of customers not only in insurance but in all sectors today.
Need for digital channel solutions
Developing digital channel solutions like a mobile app is a good way to retain customers. It improves interactions and helps understand customer lifestyle better, reasoned Maha. And enabling self-service options across these digital channels has become imperative during the pandemic, she added.
Bringing up a use case, Maha explained that the claims lifecycle of a leading UK-based insurer had a number of issues that was negatively impacting their loss ratio. To improve customer experience and reduce operational costs, the customer decided to redevelop the entire claims platform, she added. This became imperative during the pandemic because they had to also provide their services remotely. “For example, analysis of the data with the insurer showed that additional mid-term adjustment to policies was the most-sought support by their customers, via call centres. It was not available as a self-service option,” said Maha.
Aspire’s team developed a comprehensive digital portal and addressed gaps in the system with specific modules, delivering improved claims turnaround time by 60%, 84% less claims processing time, electronic notification of loss (ENOL), real-time claims updates & complete transparency.
Read the full case study: Claims process revamp gets insurer 30% more cost savings and revenue.
Electronic notification of loss (ENOL) is the next evolution of first notification loss (FNOL), said Stuart.
Going a step further, telematics is enabling insurers to make effective decisions and is also enabling them to deliver risk prevention, said Maha. “A large insurance provider, working with fleet owners, gave fleet owners asset protection and tracked drivers. They then used telematics to score drivers and use it with crash alerts, theft alerts and create an overall driver profile,” she said, presenting it as a real-life example of using telematics.
“But all this data can be of limited value if you do not have the right technology and tool to analyze the data. Insurers need AI & analytics to do that, AI is the game-changer now,” said Stuart.
AI: Are insurers keen about it?
These following charts show the AI deployment levels among large and mid-sized insurers, as observed in a survey by Aite-Novarica.
Explaining the gap in the deployment levels of various AI methodologies, Stuart said large insurers are more mature in terms of AI implementation because they have more resources available.
Addressing the need to encourage better interest in the new-age tech, Maha said, “AI does not replace underwriters or adjustors but simply adds value by taking repetitive tasks off their hands, and offering next-level data insights.” “We’ve worked on triaging systems where AI tools read emails, analyzed their pulse, sorted them in order of priority, and raised an automated request for processing with the relevant team,” Maha added. Without AI, manual triaging is very time and resource-consuming, she explained.
“An example of using voice recognition is the addition of voice bot on an insurer’s self-service portal to raise claim and address all customer service requests,” said Maha as another use case of AI in insurance technology solutions .
AI in insurance underwriting
AI is meant to augment the decision process. “For simple risks, an AI engine can help skip the really boring manual data entry work and checking of documents. With complex risk cases, AI tools such as telematics and geo-imaging can be used to analyze data to arrive at a decision,” said Stuart. AI can also help build a risk portfolio for a business and help position pricing accordingly, he added.
Read the full case study: A leading insurer went from that to achieving ~97% underwriting automation in just four months.
“The automation in underwriting ensured that almost all applications of this insurer were evaluated in a day,” said Maha, talking about the wide array of business benefits this use case delivered.
AI in insurance claims
AI has the greatest potential to influence customer experience through claims, Stuart said.
“The obvious use of AI in claims is in detecting claims fraud. AI has the ability to not just look at individual claims but to use all claims data in real-time and use machine learning to identify fraud,” explained Stuart. Claims automation is another sought-after use of AI in claims, he added, referring to no-touch or touchless claims.
Another big use is in subrogation. The sheer volume of data available to an insurer makes it a challenge for them to subrogate. “AI can help dig up such missed subrogation opportunities,” Stuart said. Litigation propensity and injury management are other applications of AI in claims, the advisor pointed out.
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Excerpts from our recent webinar “How AI Impacts underwriting & claims journey to improve CX”, jointly conducted by Aspire Systems and Aite-Novarica.