A Commentary on the Application of Artificial Intelligence in the Insurance Industry

Abstract

Millions of uninsured individuals in the US live in the areas, which are highly vulnerable to health and other risks. Artificial intelligence (AI) has become one-point solution for a variety of socioeconomic, health, environmental, technological, and business challenges and insurance industry is not an exception. This article highlights how machine learning (ML) and deep learning (DL), the two pillars of AI, help to resolve a variety of challenges in the insurance industry. The data produced in the insurance industry is unique, and the challenges are complex. Therefore, solutions have to be designed accordingly. The application of AI in the insurance industry is still in the rudimentary stages. Traditional statistical and ML methods may not do justice while developing various prediction models. Data scientists and engineers have to work together and get their hands dirty to find innovative ways of resolving them as well as developing robust and sustainable solutions that could last for years. These professionals require a very strong research background in handling a variety of data and abstract thinking style with an analytical brain. The daunting goals cannot be accomplished in a typical lift-andshift approach. Reinforcement and transfer learnings, ensemble models, natural language understanding, processing, and generation, and DL could help. Innovations in the insurance industry and emerging technologies such as Drone, the Internet of Things, and Fitbit would be brought additional challenges to AI professionals.