Discussion on “A Principal-Agent Model of Optimal Search Effort in Life Insurance Policy Replacement” by Carson, Cupach and Russell Discussed by Enya He.

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Presentation transcript:

Discussion on “A Principal-Agent Model of Optimal Search Effort in Life Insurance Policy Replacement” by Carson, Cupach and Russell Discussed by Enya He University of North Texas August 2007

Brief Summary of the Paper What does the paper do? –Modeling the optimal search effort by the agent within the life insurance policy replacement decision How does it fit into the literature –Conflict of interest created by the traditional agent compensation structure (i.e. non-recourse, up-front commission system) –Prior studies finding no connection between agent compensation and product recommendations have limitations in research design and measurement –No prior study on how to improve the alignment of incentives between consumers and agents in the life insurance policy replacement decision ??? Replacement of policy 1/3

The Model Optimal search effort expended by the self-utility maximizing insurance agent, S*, is determined by –Θ: a given state of the world –R: the fixed regulatory penalty –β: sensitivity of the regulatory environment to search effort

Implications of the Model Two Scenarios –Case 1: R = 0 → S* = 0 → Max. policy surrender –Case 2: R > 0 → S* is ↑ in β → states with greater β lower replacement related surrender Policy implications –Change of the agent compensation structure, or –More aggressive regulatory authority

Potential Areas to Extend the Study Differentiate between exclusive agents (EA) and independent agents (IA) Consider differences in the degree of regulatory scrutiny among different states Possible solutions to the problem of misalignment of interests between agents and consumers

IA vs. EA Different alignment of interest between insurers and agents Different Incentives of recommend a replacement –IA: better replacement opportunities; higher search costs; no penalty by insurer –EA: fewer choices of policy; lower search costs; potential penalty by insurer Empirical testing? –IA vs. EA → Policy surrender activities

Differences in State Regulation S* is ↑ in β Empirical evidence? –Difference in policy surrender activities ← variances in state regulation on agents –Higher customer satisfaction (e.g. fewer complaints, lower number of lawsuits/settlements) ← variances in state regulation on agents –Challenge: data available and measurement

Better System of Agent Compensation? A retrospective compensation system –Difficult for policyholder to assess the performance of agents Double-agent system –Agent for consumer work with agent for insurer