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The following is a synopsis of a recent presentation at Pinnacle U in March 2019 by James Ridgeway, Alec McClintock, Matthew McMaster and Amanda Mickelson, students from the Milwaukee School of Engineering.
The worlds of gambling and insurance are similar in many ways. Both are built upon elements of probability, modeling and quantification of risk. Both use a variety of means to attract individuals to participate. Professional gamblers are well informed as to the odds of one play versus another; an understanding of modelling can improve those odds to improve the chances of winning. Professional underwriters and actuaries understand premiums must be adequate to pay future claims and expenses; an understanding of modelling helps quantify risk and improve the ratemaking process.
Gambling and insurance each deal with potential outcomes involving large dollar payouts for rare events. Casinos must anticipate adverse results if and when there is a sporting event involving an unexpected upset or jackpots paid on a slot machine with greater frequency than expected. Likewise, insurers deal with large, unexpected claims all the time. Despite knowing the “expected” outcome, actual outcomes in both worlds will deviate (sometimes significantly) on certain days, weeks or months.
Both worlds try to mitigate the potential for such variability by embracing the law of large numbers. By increasing the number of participants (placing wagers or buying insurance policies), the difference between expectations and actual results (i.e., risk) is diversified but not eliminated. Neither wants to win or lose based on a small number of participants.
There are also psychological similarities between the worlds of gambling and insurance. Individuals make conscious choices to participate. Despite laws mandating the purchase of certain types of insurance, many make the choice to go uninsured. Such individuals recognize the distinct possibility of loss, but are “betting” an otherwise covered event will not happen to them. Likewise, those engaging in a game of chance are well aware that a likely outcome is a loss. Each hopes, however, to beat the odds and come home a winner.
Psychological bias influences individual decisions in insurance and gambling. Participants on the other side of the table – insurance companies and gambling venues – understand the law of large numbers and will supplement their underwriting of such risk. That may mean purchasing reinsurance or laying off certain bets that are deemed a risk to underlying capital and surplus. These may be one-off decisions on a particular risk or a management decision regarding the aggregate risk assumed over a period of time.
Yet, there are many differences between gambling and insurance. In particular, providing insurance coverage is assuming risk for a predetermined price. The insured seeking coverage has a chance for no loss (other than payment of the premium) but zero chance for gain. Mitigating the potential for a large loss is the primary motivation to pay premiums in advance. Gambling is a speculative risk with hopes for a gain. In both worlds, the ultimate gain or loss is dependent, in part, on the player’s ability to accurately predict future outcomes.
A second significant difference between gambling and insurance is timing. Cost, gain and payout in gambling happens immediately. Conversely, timing is a significant risk factor for insurance companies. Insurance companies will not know the outcome of a policy’s profitability until years after the premium has been paid. It may take many years until all claims arising during a policy’s coverage period become known, are reported, settled and paid.
Gambling and insurance inherently involve risk. In gambling, the risk is speculative, while the world of insurance deals with underwriting and timing risk. Both are conversant in probabilities, modeling and the law of large numbers. But both systems deal with people and their very human decisions to participate in each world.
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