Clustering-based Optimal Resource Allocation Strategy in Title Insurance Underwriting

Abstract

Production of insurance policies in all types of Insurance requires a thorough examination of the entity against which the Insurance is to be issued. In health insurance, it is the past medical data of the individuals. Vehicle insurance needs the examination of the vehicle and the owner’s data. Likewise, in Title Insurance, it is the historical data of the property which needs scrutiny before the policy issuance. Underwriters perform the job of examining the property records. The scrutiny of the property records requires a high degree of the domain and legal expertise, and title insurance underwriters are often associated with legal professions. They do the final round of validation of the examination process. There are examination teams that take care of the initial set of regular examination tasks associated with each title insurance order. Some human experts assign the orders to the team associates. Not all the orders are of the same complexity in terms of examination. The allocation of the tasks happens based on the gut feeling of the supervisor, considering their experience with the team members. Our research creates clusters of the orders based on specific parameters associated with the orders. It builds a cost model of the past associates working on orders belonging to different clusters. Based on this cost matrix, we have built an optimal task allocation model that assigns the orders to the associates with the promise of optimal cost using a Linear programming solution used frequently in operations research.