Loss aversion, a cornerstone concept in behavioral economics, profoundly influences insurance decision-making by amplifying individuals’ sensitivity to potential losses over equivalent gains. This study investigates the bidirectional effects of loss aversion across diverse risk scenarios—public health crises, natural disasters, and cybersecurity threats—and proposes behavioral interventions to reconcile its dual role as both a driver of risk mitigation and a source of cognitive bias. Through integrating prospect theory with empirical case analyses, this finding demonstrate that loss aversion leads to irrational insurance demand surges (e.g., a 58% increase in health insurance purchases during COVID-19 despite a 0.3% severe illness rate) while simultaneously causing underinsurance in imperceptible risks (e.g., only 17% of small businesses purchasing cyber insurance despite a 22% attack probability). Behavioral strategies such as default options, framing effects, and risk visualization tools are shown to optimize decision efficiency by recalibrating loss aversion’s psychological weight. This research contributes to both theoretical advancements in behavioral economics and practical applications for insurance product design and policy implementation.
Yao Jiang (Mon,) studied this question.