Gen-AI and Large Language Models in Claims: Embracing Potential, Managing Risk - Seguridad Mania.com - España y América Latina

Today's insurers are faced with increasing customer demands and an accompanying need to increase speed with straight-through processing. In tandem with unprecedented access to client data, insurers must also manage an uncertain economic and regulatory environment and the need to maximize profitability and reduce overhead. In this context, the rise of Gen-AI and LLMs has emerged as a promising opportunity for claims professionals when it comes to processing large volumes of data and delivering a personalized client service. However, concerns exist within the industry around the impact of these technologies on the workforce, the ESG-related implications of the sheer compute power required to use them, in addition to safety and security compliance issues. This webinar will explore the very real potential of GenAI and LLMs within insurance claims, while shining a light on the potential pitfalls facing insurers along the way as they implement these technologies. Automate routine tasks and decision-making processes with Gen-AI to reduce the time it takes to process claims and boost retention Use AI-powered document generation to assist in creating claim-related documents, such as letters of explanation, FNOL forms, settlement offers, and policy updates, reducing manual paperwork and ensuring consistency in communication Transform fraud detections: Utilize AI models to analyze historical data and patterns to identify potentially fraudulent claims and reduce losses Addressing concerns, managing risk and identifying potential pitfalls when it comes to the implementation of these technologies Hear from: - Shawn Crawley, Chief Operations Officer, North American Claim, Sompo International - Sean Duffy, Executive Vice President & Chief Claims Officer, Skyward Insurance This webinar is brought to you in association with Expert AI. By registering you agree to share your information with this organisation.