How legacy players can reinvent the Insurance value chain
By Leon Gauhman, Co-Founder & CPO/CSO, Elsewhen
Generative AI is poised to disrupt every sector – and the insurance industry is not immune.
The good news is that Large Language Models (LLMs) are tailor-made for the fast-
Changing insurance sector.
Language forms the basis of many facets of risk management, from modelling to quotes and underwriting. So, if incumbents can use LLMs to leverage their high-quality, first-party data, they will have a ready-made defence against BigTech contenders at the gate. With Amazon targeting home insurance, Apple eyeing the health insurance market, and Lemonade, Zego and Clearcover also making waves, LLMs and AI could be legacy insurers’ game-changing opportunities. Here’s how to embrace the shift:
Personalised product development: Using their rich reserves of proprietary data, incumbents like Zurich can focus on breaking down the rigidity of underwriting, which currently confines them to offering consumers commoditised, one-size-fits-all products in areas such as health, home, car, and travel insurance. Cut loose; insurers can deploy LLMs to create valuable IP at speed. This could be a personalised AI broker to deliver nuanced recommendations that fit precisely with a customer’s circumstances and risk profile.
Accelerated distribution: Once insurers have deployed LLMs to create new products, AI can also help with their rapid roll-out to market by generating product descriptions and marketing collateral at scale. Using an LLM-enabled drill down of multiple data sets around individual customers’ risk profiles and requirements, insurers can use AI to generate personalised marketing campaigns across various channels and formats, including bespoke offers and incentives. At the other end of the campaign, LLMs constantly learn from data about the success or failure of new product launches and related marketing campaigns. Consequently, these services accelerate the feedback loop, adjusting and improving insurance products and campaigns in near real-time.
Next-generation underwriting: Because LLMs can understand and process unstructured and natural language, adopting them will also speed up the automation of underwriting – prompting more accurate pricing and reduced risk. This year, for example, insurance platform Cytora introduced new capabilities to its digital risk assessment and underwriting processes, which it claims will enable customers to reduce the time to onboard new businesses. By providing risk-specific LLMs that build upon Cytora’s proprietary AI, underwriters can ‘cut through the noise and reach decisions more efficiently and effectively’, said CEO Richard Hartley.
Rethinking the business model: Perhaps the most fundamental way LLMs will impact the insurance industry value chain lies in the technology’s ability to reinvent the entire operational model. Insurers’
current models follow a linear, step-by-step framework covering product development, underwriting, distribution, policy issuance, admin, accounting, and claims. Using LLMs presents an opportunity to rewrite and transform this time-consuming approach from the ground up.
In this scenario, AI would draw on an insurance company’s structured and unstructured data to plan and generate risk and underwriting models for product details. There would still need to be humans.
Oversight to set parameters and decide strategically significant outputs. However, this calibre of AI-led operating model would allow insurers to create particular variants of their products tailored to
Customers’ circumstances with previously unimaginable scale and speed.
LLMs offer a bold leap forward for legacy operators, especially since they have largely failed to take advantage of the web and mobile revolutions. There’s no question that the transformation required for this AI-driven shift is significant, particularly for analogue underwriters that – like Lloyds of London – are still weaning themselves off paper-based processes. The payoff is worth it. LLMs could become a transformational tool, allowing them to reinvent the insurance value chain in a previously impossible way.
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