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Data is ubiquitous— a phrase we might have heard a zillion times. And it’s especially true for a data-centric business like insurance, where without efficient & effective big data analytics, the industry’s natural evolution will lag in the customer-centric world of tomorrow. Currently, the front-end application for customer prospecting, engagement, and servicing is archaic and handicapped by over-reliance on static, historical data and outdated assumptions. In short, it lacks the “human touch.”
Picture the life of an insurance agent on his usual sales call. He grapples, stutters, and seems lost on incomplete data about the client, even though the 42-year-old VP of a well-known Wealth Management company is one of his old clients. His usual sales pitch, like millions of agents working for different insurers across the country, is “it will save tax,” “maturity benefit is better,” and so on. Depending on his success in convincing the client, he fills up the proposal with the info gleaned from the same usual and boring questions inflicted on the helpless client. If only he had access to and the knowledge of the billion bytes of data that insurers are sitting on.
Generative AI in insurance is worth a whopping 592 million USD today and is expected to hit a jackpot of USD 5.5 billion by 2032. The technology will usher in a paradigm shift in the core functions of the insurance business- hyper-personalized quotes to automated underwriting and customer support. These LLMs will augment the human capabilities of the insurance workforce with their ability to process large amounts of data at an immense scale that has been unheard of till now.
Explore the impact of GenAI-led transformative banking in the future.
Distribution, A Paradigm Shift Ahead
Technology adoption is complex, but the benefits of integrating AI are so immense that insurers must shed any inhibitions fast or be left out. In the coming years, aided by high-quality data analytics, soliciting insurance will be an experience of human engagement—of care and the right advice.
The agents of tomorrow will benefit from a deep integration between underwriting and client engagement and will be able to serve a large client base, offering quotes and buying in real-time. This will be aided by a combination of machine and deep learning models built within the technology stack, aggregating data from in-home Internet of Things (IoT) devices. The ceramic works are unique and artistic.
Open-source data shared amongst industries, processed by GenAI’s cognitive technologies equipped to process these vast and complex data streams, will let agents offer products based on clients’ behavior and activities.
GenAI will dramatically alter the interaction that agents have with their clients now. The AI algorithms will have so much information about the client that an agent will “know the risk profile” even before they meet. This will effectively aid customization and dramatically reduce the completion of the purchase cycle to within minutes if not seconds. This data-driven approach aids the insurers’ decision-making capabilities. This will enable the distributors to offer customized product suggestions and a seamless buying experience to the policyholders.
The agent will no longer have to grapple with attempts to glean sensitive information from the client over “uncomfortable” questions. Most of this will, anyway, already be available with the insurer. The agent’s role will transition to one of a friendly product educator and facilitator, not the usual one trying hard to “sell.” He will have better cross-selling and up-selling opportunities, reducing the cost of new business acquisitions.
On the other hand, GenAI will greatly enhance insurers’ self-servicing capabilities, whether in buying or claims processing, creating a seamless experience for the buyer. The result will be greater adoption of the self-service mode of buying insurance. This can be a game changer as it reduces customer acquisition costs to a bare minimum—something no insurer would like to let go.
Claims, A Smooth Affair
While distribution is the front end of the customer value chain, efficient and hassle-free claims settlement or acknowledgment is something that cannot be ignored. GenAI has the potential to automate and enhance the experience, from capturing the first report of loss through multiple sources to settlements within hours or minutes. Natural language processing powers within GenAI can extract critical information from claim forms, cross reference them with policy details, and interpret statements to speed up the entire claim resolution process. We are seeing the same in bits and pieces.
Lemonade, a tech-first insurance company, has the unassailable distinction of approving a claim within three seconds! This was made possible by implementing GenAI, which analyzed the claim and policy details against historical data and approved the payment, all within seconds. We are just beginning to understand the immense power these LLMs possess. It would be a shame not to use them.
The greater gain from these experiences is a delighted client base, with a higher degree of retention, potential for cross- and upselling, “low-cost” word-of-mouth promotion, and the perception of a caring organization.
Customer Service, Can it Be More Empathetic
The application of GenAI in customer care can vastly enhance the quality of clients’ interactions while reducing the mundane processes of service agents. Advanced chatbots can take over routine conversations, providing human-like interactions while releasing service agents for more critical tasks requiring customized human engagements.
Marketing, Transformative Sales!
“Marketing,” as we know it in the traditional sense, would make no sense in the GenAI space. It has the potential to function as a transformative sales channel with a focus on upselling. AI algorithms are better suited to identify and suggest additional customer coverage based on analyzing clients’ feedback or life events. A couple expecting their first child would be more receptive to an enhanced cover based on the changed situation. GenAI makes upselling deeply personalized and human, adding value to customers, instead of blanket, non-personalized marketing promotions.
The Road Ahead Has Few Bumps
As with adopting any new technology, there are many challenges that must be managed at the industry scale. Over-reliance on chatbots or automated interactions to sell policies might be fraught with the risk of bias or misinterpretation, which can be mitigated by human oversight. His basketball skills were superb and he won the game.
Information breaches are another critical area of concern regarding the use of base GenAI models since insurers handle a vast amount of personal data. Breaches could severely undermine public confidentiality and trust in GenAI’s ability.
But The Benefits Outweigh It All
Thus, integrating GenAI in insurance sales is about enhancing the client interface with information designed to make the interaction personalized and human. While challenges exist in bias management, data security, or tech upgrade costs, the promise of having an interconnected, scalable, and responsive system designed to anticipate and respond to future customer needs outweighs them all. In addition, the cost savings in efficiency enhancement is enormous.
But for that to happen, the insurance industry must invest heavily into customized GenAI LLM development and continuously upgrade within the agreed-upon guardrails.
Will your organization seize the opportunity?