Incentive Compensation and Performance Measurement in the Property and Casualty Insurance Industry

PMA Conference Proceedings, pp. 147-153, July 2006

Posted: 22 Nov 2006 Last revised: 17 Sep 2009

See all articles by Joseph Calandro, Jr.

Joseph Calandro, Jr.

Fordham University - Gabelli Center for Global Security Analysis

Scott Lane

Quinnipiac University; Quinnipiac University

Date Written: July 1, 2006

Abstract

Changes in the property and casualty (P&C) insurance industry, and changes in executive compensation in general, have lead to a situation where P&C managers have increased opportunities and motivation to influence earnings. A significant opportunity to influence earnings arises out of establishing and managing insurance claims reserves, which are composed of both case and actuarial reserves. This is significant because many insurance incentive compensation programs are based on yearly reported earnings. This paper presents an alternative insurance executive compensation approach. The approach utilizes a more accurate measure of insurance performance, accident year analysis — in place of the more traditional calendar analysis — and a bonus bank program.

Keywords: Insurance, Incentive Compensation, Economic Profit

JEL Classification: J33, L20, M21

Suggested Citation

Calandro, Jr., Joseph and Lane, Scott, Incentive Compensation and Performance Measurement in the Property and Casualty Insurance Industry (July 1, 2006). PMA Conference Proceedings, pp. 147-153, July 2006 . Available at SSRN: https://ssrn.com/abstract=946234

Joseph Calandro, Jr. (Contact Author)

Fordham University - Gabelli Center for Global Security Analysis ( email )

531 Hughes Hall
441 E. Fordham Rd
Bronx, NY 10458
United States

HOME PAGE: http://www.linkedin.com/in/josephcalandro/

Scott Lane

Quinnipiac University ( email )

Mount Carmel Ave
Hamden, CT
United States
(203) 582-8367 (Phone)

Quinnipiac University ( email )

United States
2035828367 (Phone)
2035828367 (Fax)

Here is the Coronavirus
related research on SSRN

Paper statistics

Abstract Views
581
PlumX Metrics