The Anatomy Of Artificial Intelligence Solution For Automation Of Underwriting Decision-Making Process

Experience and good judgment are essential attributes of underwriters. Systematic analysis of the underwriting decision-making process was expected to increase the efficiency in developing these attributes in underwriters. However, this approach fell short of expectations. The industry still struggles with the pace of knowledge and experience delivery to next generation of underwriters. The solution may lay in development and deployment of artificial intelligence (AI) methods and algorithms in automation of the underwriting decision-making process. This paper outlines the current state of the performance measurement of underwriting decision-making process through underwriters’ performance metrics (including a novel one). Further, this paper provides an in-depth description of artificial intelligence methods and algorithms that can be successfully used to automate underwriting decision-making process. The real data from one of the leading insurance companies was used for analysis and testing of proposed approaches.

Tanya Kolosova is an innovator and actionable analytics expert having served as the Chief Analytics Officer at InProfix Inc, a stealth mode startup that develops AI solutions for the insurance industry. Tanya has extensive knowledge of software development methods and technologies, artificial intelligence methods and algorithms, statistically designed experiments. Samuel co-authored two books on statistical analysis and metadata-based applications development with SAS.