Clustering-based Optimal Resource Allocation Strategy in Title Insurance Underwriting

Title

Clustering-based Optimal Resource Allocation Strategy in Title Insurance Underwriting

Creator

Guha A.; Obaidat M.S.; Samanta D.; Islam S.K.H.

Description

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. 2022 IEEE.

Source

Proceedings of the 2022 International Conference on Computer, Information and Telecommunication Systems, CITS 2022

Date

2022-01-01

Publisher

Institute of Electrical and Electronics Engineers Inc.

Subject

Clustering; Gower distance; Linear optimization; Operations Research; Optimal Resource Allocation; PAM.

Coverage

Guha A., CHRIST University, Eagle Labs First American India Private Limited, Department of Computer Science, Karnataka, Bangalore, India; Obaidat M.S., Department of Computer Science, Cybersecurity Center, University of Texas-Permian Basin, United States, University of Jordan, KASIT, Amman, 11942, Jordan, University of Science and Technology, School of Computer and Communication Engineering, Beijing, China, Amity University, Noida, India; Samanta D., Department of Computer Science, CHRIST University, Bangalore, Karnataka, India; Islam S.K.H., Indian Institute of Information Technology Kalyani, Department of Computer Science and Engineering, West Bengal, 741235, India

Rights

Restricted Access

Relation

ISBN: 978-166548615-6

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1109/CITS55221.2022.9832993

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