Dear Insurance companies, start your GenAI journey HERE

Generative artificial intelligence (GenAI) is the fastest adopted technology in history (Hu, 2023), however, it comes with risks.? The appeal of GenAI is the incredible potential to reduce costs and enable digital transformation.? It’s no surprise then that there is massive interest from my clients. The most common question I get is: “Where should we begin our GenAI journey?”? This usually leads to discussions and demos of all that we are doing, which is exciting stuff. But for some, instead of action, I see pondering.? And questioning.? And eventually, nothing.? When you are in the Insurance industry, it is all about managing risks. ?But that doesn’t need to prevent progress. So, how should Insurance companies jumpstart GenAI??

To answer this, I asked Kevin Kane, TCS Insurance Consulting Partner, to share his guidance for Insurance companies that are unsure of where to start. Kevin highlighted four key factors that should be considered collectively:

• What are the primary benefits of GenAI, and how do these align with your key business objectives?
• What are your customer’s expectations with GenAI?
• Where has GenAI proven itself and matured?
• How do you best mitigate the inherent risks of GenAI?

He recommends an approach that takes these criteria into consideration. Successful organizations need to identify uses cases that weigh these key factors. Early AI solutions were introduced years ago and have since matured greatly. Insurance companies are seeking to optimize operations, control costs and redirect staff to higher priorities, while improving the customer experience. Customers in turn want ease of use and increased personalization. The most effective GenAI solutions are based on these core principles.

GenAI applications that meet the above criteria best are those that are internally focused on assisting associates and improving processes by augmenting employees with real-time contextualized data.?

Customer-facing GenAI applications inherently have more risks, and should be considered in later phases once experience, governance and capabilities demonstrate sufficient value.?

To explore what’s been developed for insurance companies, I talked with Ram V, CTO BFSI at TCS. Our discussion reinforced focus on internal productivity with GenAI. ?He shared that the BFSI Research & Innovation (R&I) team is one of many in TCS helping customers with GenAI. “The path we believe works best for insurance companies is to first assist internal associates, then augment the human and lastly transform the process.”? Per Ram, some recent engagements are:?

Policy Comparison:

R&I recently helped a large commercial insurer in utilizing GenAI to enable brokers and agents to quickly make comparisons between existing policies and new quotes.? The proof-of-concept proved beneficial by summarizing and comparing key data from both policies to enable informed decisions in a fraction of the time.? ?

Compliance:

Another proof-of-concept was for a European insurer to for their compliance team to extract obligations from the Digital Operational Resilience Act to check for obligations within their operational policy documents and to suggest appropriate steps to be compliant. ?This greatly reduced efforts and improved compliance.? ?

Bots:

For a Life and Pensions Company, a Q&A Bot was created for answering policy questions for brokers and agents. It was able to immediately and accurately answer detailed questions, remembering context from previous questions and providing the source of the answer, rather than manually sifting through lengthy documents. ?

Co-Pilots:

Multiple customers were demonstrated co-pilot applications for Claims and Call Center. ?These work by quickly summarizing claim files, notes, call transcripts and call quality. These summarizations significantly reduce an adjuster’s or call center agent’s time getting the needed context to complete their task accurately.??

Modernization:

Insurers are also focusing on speeding up IT Transformation using GenAI. ?There are multiple engagements here, including extracting and migrating business rules, data mapping and performance test scripts from legacy systems.? These GenAI applications will help Insurers’ IT reduce time in transforming to modern platforms that better enable business growth.

Conclusion

Even with so many beneficial GenAI uses cases, there remains the alternative to wait. Per Kevin, “the risks of inaction on GenAI continue to grow for insurers.” Market trends indicate that customers may drop their insurance provider for a competitor. Over the last several years, Insurtechs have continued to grow in part by providing digitally enhanced customer experiences. Organizations that embrace such capabilities are better positioned for future insurance industry consolidation.

With so many considerations facing Insurance companies in adopting GenAI, I recommend focusing first on use cases that improve internal productivity, efficiencies, compliance, and by extension, cost savings.? This approach will best manage risk while generating value and enabling a transformation jumpstart with GenAI.?