Artificial Intelligence Review of Insurance Contracts - Are we there yet?

• Date: 20 October 2020
• Author: Chvasta, Joe
• Published date: 20 October 2020
• Author: Chvasta, Joe

* The use of Artificial Intelligence to review insurance contracts is growing as AI tools can rapidly compare a high volume of contract clauses and make human reviewers faster and more effective. First implemented in 2011, the technology automating the review of contracts has progressed dramatically, leading to the question if AI technology by itself is ready to totally automate the review of contracts or if it remains a tool to assist humans in their contract review.

Insurance companies are adopting AI contract review for greater efficiency.

Insurance companies are joining law firms and other large corporations by adopting AI for contract review due to its efficiency compared to using lawyers, paralegals and other persons. LawGeex, a leader in AI contract review, is used by three of the five largest insurance companiest. LawGeex estimates that contract review by AI saves 80% of the time and 90% of the cost and results in deals closing three times faster. Kira Systems, a provider with insurance company and law firm clients estimate cost savings at 60% while other sources estimate total cost savings at a still hefty 50%. One insurance company leading in the use of AI contract review is Swiss Re which writes about 20,000 contracts a year using an AI tool to compare single clauses against the entire data set expediting the underwriting process. Some in the industry believe that comprehensive contract review without AI is impossible. One analyst commented that an insurance company could not hire enough underwriters and lawyers to review a high volume of contracts with any depth unless they used AI.

WHAT IS ARTIFICIAL INTELLIGENCE?

Artificial Intelligence consists of many related technologies including: "Machine Learning," a subset of AI in which computers use algorithms and statistical models to identify patterns in data and adapt with experience and without the need for reprogramming. Machine learning makes predictions based on data and uses techniques such as decision trees.

"Deep Learning," a type of machine learning loosely modeled on the neural pathways of the human brain. Deep learning is a self-learning model where algorithms attempt to model high level abstractions in data and requires more computational power than other types of machine learning. "Natural Language Processing (NLP)," a type of machine learning with the ability of a computer to understand, analyze, manipulate, and potentially generate human language. NLP is useful for...