Game Theory in Life Insurance
The insurance industry has long been applying game theory to evaluate whether or not individuals are insurable and determine how much premium to charge them based on their apparent needs. This interaction between the consumer and the insurance company can be characterized as a game because not only are they playing against one another but each party is waging on an outcome more beneficial to them. In a traditional life insurance, there are many variables to consider when utilizing game theory to form a strategy as there are investment components along with complex riders. Thus, in order to keep the game relatively simple, this paper will assume the insurance being considered is term life and use game theory to help the consumer decide whether or not to buy the insurance. However, in this particular scenario, the potential buyer will be playing not against the insurance company but rather Mother Nature herself. It will begin by briefly defining game theory and consumer insurance options as well as explore the different strategies game theoretical models. In the end, the paper will also discuss why it might be important to purchase life insurance and the risks involved if not. Introduction
Before presenting how game theory can help consumers make a decision on whether or not buy life insurance, it is important to understand its framework and some its key elements particularly when payoff depends on the actions taken by another. Game theory is a method of analyzing situations and studying strategic interactions among game participants, or players, where they choose different actions in an attempt to maximize their returns. It studies decisions that are made in an environment where various players interact. In other words, game theory studies choice of optimal behavior when the costs and benefits of each option are not fixed, but depend upon the choices of other individuals (Browning, 2014). In every game theory model, there are at least three elements in common: players, strategies, and payoffs. The players are the decision makers whose behavior we must try to predict. The strategies are the possible choices of the players while the payoffs are the outcomes, or consequences, of the strategies chosen. Now that we have explored the general framework of game theory, it is also essential for the potential buyer to get familiar with the objective. In this case, that objective is making the decision to purchase life insurance. There are several different types of life insurance. However, for the sake of simplicity, this game will assume that insurance being considered is pure life insurance as opposed to the traditional, or permanent life insurance which contains investment variants. Term life insurance is considered “pure insurance” because when one purchases a term insurance policy, he or she is only buying a “death benefit”. Unlike with other types of “permanent insurance” such as whole life, universal life, and variable universal life, there is no additional cash value built up with this kind of policy. Term insurance only gives a specific death benefit. Furthermore, it is the easiest type of life insurance to understand as the insured person pays a minimal premium per thousand dollars of coverage on a periodic basis. Thus, if he or she dies within the term of the policy, the life insurance company will pay the beneficiary the face value of the policy (Automatic Information, 2014).
In order to take the right approach to this game, it is important to examine two fundamental characteristics. The first characteristic that must be explored is the probability of an unfortunate event rendering fatal to the consumer. Another is the statistical morality which may play a role in risk aversion of the prospective consumer looking to purchase life insurance. For example, if one feels particularly healthy, he or she might estimate their probability to be negligible for...
References: Automatic Information. (2014). Term Life Insurance. Retrieved from http://www.automaticinformation.org/term-life-insurance/?lang=en
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Browning. (2014). Game Theory and the Economics of Information. Retrieved from
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