A multi-input multi-label claims channeling system using insurance-based language models

作者：

Highlights：

• A channeling system to improve claims management and customer satisfaction.

• Built models using structured data and claim notes for claims classification.

• Compared multi-label approach with an equivalent binary approach for multiple tasks.

• A web-based user interface to serve the model(s) and route claims to domain experts.

摘要

•A channeling system to improve claims management and customer satisfaction.•Built models using structured data and claim notes for claims classification.•Compared multi-label approach with an equivalent binary approach for multiple tasks.•A web-based user interface to serve the model(s) and route claims to domain experts.

论文关键词：Insurance,Language models,BERT,Transfer learning,Claims classification,Fraud detection

论文评审过程：Received 11 November 2020, Revised 6 December 2021, Accepted 31 March 2022, Available online 14 April 2022, Version of Record 28 April 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.117166