Insurance customer behavior: Lessons from behavioral economics

• Date: 01 July 2019
• DOI: http://doi.org/10.1111/rmir.12121
• Author: Andreas Richter,Stefan Schelling,Jochen Ruß
• Published date: 01 July 2019

© 2019 The American Risk and Insurance Association

Risk Manag Insur Rev. 2019;22:183–205. wileyonlinelibrary.com/journal/rmir

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183

Received: 1 May 2019

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Accepted: 1 May 2019

DOI: 10.1111/rmir.12121

INVITED ARTICLE

Insurance customer behavior: Lessons from

behavioral economics

Andreas Richter

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Jochen Ruß

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Stefan Schelling

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1

Institute for Risk Management and

Insurance and Munich Risk and

Insurance Center, Ludwig‐Maximilians‐

Universität Munich, Munich, Germany

2

Institut für Finanz‐und

Aktuarwissenschaften, Ulm and Institute

of Insurance Science, University of Ulm,

Ulm, Germany

3

Institute of Insurance Science,

University of Ulm, Ulm, Germany

Abstract

In economics it has traditionally been assumed that people

make all their decisions like the so‐called homo oeconomi-

cus –that is, maximizing (expected) utility of total wealth.

In recent years, economics increasingly recognized that

people often exhibit behavioral patterns which are incom-

patible with the idea of the homo oeconomicus. The field of

behavioral economics incorporates insights from the field of

psychology to explain discrepancies between predictions of

traditional economic theory and actual observed behavior.

In this paper, we summarize a selection of well‐established

behavioral patterns observed in reality and discuss their

relevance for the insurance industry when it comes to better

understanding and predicting customer behavior. We also

explain that people are not always risk‐averse and give a

brief overview over Prospect Theory (probably the most

popular behavioral economics alternative to Expected

Utility Theory), its shortcomings for predicting behavior

over a long time horizon, and its extensions. In total, we

point out that, since dealing with risks and insurance

products requires complex decision making processes, a

deep understanding of the impacts of behavioral factors is

essential to better assess and explain costumer behavior.

This article is based on the book “Moderne Verhaltensökonomie in der Versicherungswirtschaft—Denkanstöße für ein

besseres Verständnis der Kunden”, Springer (2018) by the same authors. The authors gratefully acknowledge the

support of Joëlle Näger who translated the first draft.

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FAREWELL TO THE HOMO OECONOMICUS

In economics it has traditionally been assumed that people make all their decisions like the so‐

called homo oeconomicus. The consequences of economic decisions are assessed exclusively with

respect to the utility that is generated for the decision‐maker, regardless of the situational context or

emotions and without errors in information processing. One basic principle is that more money is

always better than less. The utility function is increasing. Also, it is commonly assumed that the

marginal utility decreases. Thus, the slope of the utility function decreases with increasing wealth.

With respect to decisions under uncertainty, it is assumed that a homo oeconomicus always choses

the alternative with the highest expected utility. In this context, the typical property of decreasing

marginal utility is equivalent to the assumption that people are risk‐averse.Thisisalsoempirically

supported. For example, a homo oeconomicus who is not risk averse would not take out insurance. A

risk‐averse decision maker prefers a safe amount over a lottery with the same expected value.

In recent years, economics increasingly recognized that people often exhibit behavioral patterns

which are incompatible with the idea of the homo oeconomicus. Various so‐called cognitive biases

canmassivelyinfluencehumandecisions.Individual information processing capacities are limited,

so we often tend to use mental short‐cuts, so‐called heuristics. Decisions are also strongly

determined by the context in which information is presented to the decision‐maker. Further,

emotions can play an important role and oftentimes, not only one’s own utility is of relevance.

Behavioral economics tries to identify behavioral patterns that drive actual human decision

making.

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While Expected Utility Theory is a normative theory, behavioral economics is

descriptive. It tries to describe, understand and predict how people actually behave in reality.

In section 2, we present a (subjective) selection of behavioral patterns observed in reality and

discuss their relevance for the insurance industry when it comes to better understanding

customers and predicting customer behavior.

Subsequently, in section 3, we take a closer look at the above‐mentioned willingness to take

risks and the risk aversion usually assumed in Expected Utility Theory. In doing so, we will

focus on the fact that people are not always risk‐averse and that a differentiated approach is

necessary in many cases.

In section 4, we further focus on the presentation of descriptive models that are better able to

describe and predict actual decision making by taking into account different behavioral

patterns. In particular, we look at Prospect Theory and its extensions. Prospect Theory is

probably the most popular behavioral economics alternative to Expected Utility Theory.

Finally, we give a short summary as well as an outlook on further applications, open

questions and future research topics.

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SELECTED COGNITIVE DISTORTIONS AND

HEURISTICS AND THEIR RELATION TO INSURANCE

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Fairness

Experiments show that people deviate from rational behavior when they can punish or avoid

a perceived inequity. Probably the best known experiment is the so‐called ultimatum game

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This approach is increasingly being used in insurance economics under the label “Behavioral Insurance”. Numerous studies based on laboratory experiments

are to be mentioned here (for an overview see, e.g., Jaspersen, 2015), but increasingly also studies based on real data such as Sydnor (2010), Barseghyan,

Molinari, O’Donoghue, and Teitelbaum (2013), and Browne, Knoller, and Richter (2015).Cf., also Richter, Schiller, & Schlesinger (2014) for a review of the role

of experiments and theory in analyzing insurance demand from a behavioral perspective.

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