Legal data is incredibly valuable. In the insurance field, data about the average similarity score of the clauses in a policy - a measure of the relative similarity or divergence for one clause in relation to a set of other similar clauses that are meant to accomplish the same function - can be used to instantly show how one policy stacks up against another. Data about the composition of cyber policies can be used to reveal which clauses or information a given policy might be missing.
The following series of posts survey how the seemingly nascent features of an insurance policy - policy metadata - can be levereaged to create artificial intelligence that improve the quality and efficiency of drafting these policies. By using even the most rudementary AI tools, underwriters and legal professionals can begin to speed up the work they are doing by more effectively spotting areas that deviate from industry standards.