View source for Definition:Prospect theory

🧠 '''Prospect theory''' is a behavioral economics framework, developed by Daniel Kahneman and Amos Tversky in 1979, that describes how individuals evaluate potential gains and losses relative to a reference point rather than in terms of absolute outcomes — and it has profound implications for how people perceive, purchase, and interact with [[Definition:Insurance | insurance]]. The theory demonstrates that people are loss-averse: the pain of losing a given amount exceeds the pleasure of gaining the same amount. In insurance, this asymmetry explains much about consumer behavior — why individuals overpay for low-[[Definition:Deductible | deductible]] policies, why they overinsure against vivid but statistically rare perils, and why they sometimes refuse to buy coverage for genuinely catastrophic risks that feel abstract or distant.

🔬 Two core features of the theory — the value function and probability weighting — map directly onto insurance decision-making. The value function is concave for gains and convex for losses, which means consumers feel increasingly diminished marginal pain as losses grow larger. This can make them undervalue [[Definition:Catastrophe risk | catastrophe coverage]] because the psychological difference between a $500,000 loss and a $1,000,000 loss feels smaller than the difference between $0 and $500,000. Probability weighting, meanwhile, shows that people overweight small probabilities and underweight large ones. This explains the persistent demand for coverage against dramatic but rare events like airline crashes or terrorism — the vivid mental image inflates the subjective probability — while simultaneously explaining why consumers may neglect [[Definition:Flood insurance | flood insurance]] even in moderate-risk zones where the actual probability of loss is meaningful. Insurers and [[Definition:Actuarial science | actuaries]] who design products assuming purely rational expected-utility calculations often find their take-up rates, [[Definition:Lapse | lapse]] patterns, and [[Definition:Claims | claims]] behaviors deviating from predictions in ways that prospect theory readily explains.

💡 Recognizing prospect theory's influence gives insurers and [[Definition:Insurtech | insurtech]] companies a sharper lens for product design, pricing communication, and customer engagement. Framing a policy as protecting against loss rather than as an expenditure leverages loss aversion to improve conversion rates. Offering lower deductibles — even when a higher deductible is actuarially optimal for the consumer — responds to the reality that people disproportionately value certainty of small-loss coverage. Behavioral nudges informed by the theory, such as default enrollment in coverage or anchoring quotes to a mid-tier option, have been adopted by digital platforms seeking to optimize purchasing flows. On the [[Definition:Underwriting | underwriting]] side, understanding how [[Definition:Moral hazard | moral hazard]] and [[Definition:Risk perception | risk perception]] are distorted by reference-point thinking helps insurers anticipate policyholder behavior after a loss. Far from a purely academic construct, prospect theory has become a practical tool for insurers seeking to bridge the gap between how people should buy insurance and how they actually do.

'''Related concepts:'''
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* [[Definition:Behavioral insurance]]
* [[Definition:Moral hazard]]
* [[Definition:Adverse selection]]
* [[Definition:Risk perception]]
* [[Definition:Insurance demand]]
* [[Definition:Loss aversion]]
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