✳flâneur — a map of the web's best reading

Gen AI: why simple RAG does not work for insurance.

zelros.com · 419 words · saved by 1 readers

When it comes to leveraging Generative AI for insurance, Retrieval Augmented Generation (RAG) is a hot topic. Indeed, an automated understanding of insurance contracts, general terms and conditions, or procedures is a must-have to improve the global lack of insurance literacy. However, at Zelros, we believe that RAG is just one component of a sophisticated decision-making engine for insurance. On its own, it doesn’t fully satisfy consumer expectations or meet the stringent regulations of the insurance industry. Here is why! The Insurance industry is unlike any other industry. Providing incorrect or inaccurate information to policyholders isn’t an option because of the significant financial implications. This is precisely why the industry is heavily regulated. Off-the-shelf RAG doesn’t prevent wrong or incomplete answers (e.g., omitting mention of edge cases). It is the first way to mitigate hallucinations, compared to a generic ungrounded LLM, but it is not enough. Let’s take the examp

Customer Engagement for Insurance & Banking | Earnix Customer Engagement, Built for Insurance & Banking Earnix delivers real-time, explainable, and compliant customer engagement across distribution, service, and digital channels, heling insurers and banks improve experiences, increase productivity and drive growth. Products - Product Overview > Customer Engagement Customers have already achieved: + % Cross-sell uplift + % Agent & advisors productivity + % Customer retention conversion ratio + X Upskilling/onboarding The power of personalization starts here Explain Explain complex decisions, ru

Explore this link on the map →

related reading