Policyholder cluster divergence based differential premium in diabetes insurance

Benjiang Ma, Qing Tang, Yifang Qin and Muhammad Farhan Bashir

Managerial and Decision Economics, 2021, vol. 42, issue 7, 1793-1807

Abstract: Traditional health insurance pricing, which is based on experience rates, cannot correctly estimate the risk types of policyholders, can lead to serious adverse selection. Due to massive data volumes and developments in data analysis technology, the underwriting process can more accurately reflect the insured's risk type. Therefore, this paper based on policyholder cluster divergence proposes a differential premium approach by employing fuzzy c‐means algorithm (FCM) with an extended initial multistate Markov model to formulate the differential premium that matches the policyholder's risk category. Our results confirm that the proposed differential premium approach better reveals the policyholder's risk type as compared with unified pricing and effectively counteracts adverse selection.

Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
https://doi.org/10.1002/mde.3345

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wly:mgtdec:v:42:y:2021:i:7:p:1793-1807

Access Statistics for this article

Managerial and Decision Economics is currently edited by Antony Dnes

More articles in Managerial and Decision Economics from John Wiley & Sons, Ltd.
Bibliographic data for series maintained by Wiley Content Delivery ().