Abstract

As the Life Insurance industry undergoes rapid digital transformation, the need for more intelligent and adaptive testing methods has become crucial. Traditional test case generation methods often struggle to keep pace with the industry’s dynamic requirements, intricate processes, and evolving regulatory landscapes. In this context, Generative AI (GenAI) is emerging as a game-changer, bringing a new level of efficiency, scalability, and intelligence to software quality assurance.
This paper delves into the application of GenAI for autonomous test case generation in life insurance applications, exploring how it can streamline testing, enhance accuracy, and reduce manual effort. Through comparisons with traditional approaches, real-world case studies, and a discussion of best practices, we uncover the tangible benefits and challenges of adopting GenAI in this domain. Additionally, the paper sheds light on future possibilities, aiming to inspire innovation and drive further advancements in quality assurance for life insurance systems.