Considerable evidence suggests that many people for whom insurance is worth purchasing do not have coverage and others who appear not to need financial protection against certain events actually have purchased coverage. There are certain types of events for which one might expect to see insurance widely marketed are now viewed today by insurers as uninsurable and there are other policies one might not expect to be successfully marketed that exist on a relatively large scale. In addition, evidence suggests that cost-effective preventive measures are sometimes rewarded by insurers in ways that could change their clients' behavior. These examples reveal that insurance purchasing and marketing activities do not always produce results that are in the best interest of individuals at risk. Insurance Decision Making and Market Behavior discusses such behavior with the intent of categorizing these insurance "anomalies." It represents a first step in constructing a theory of insurance decision making to explain behavior that does not conform to standard economic models of choice and decision-making. Finally, the authors propose a set of prescriptive solutions for improving insurance decision-making.
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Howard Kunreuther is the James G. Dinan Professor of Decision Sciences and Business and Public Policy at the Wharton School, University of Pennsylvania and co-director of the Wharton Risk Management and Decision Processes Center. He has a long-standing interest in ways that society can better manage low-probability, high-consequence events. Dr Kunreuther is a member of the World Economic Forum's Global Agenda Council on Insurance and Asset Management for 2011 2012 and in 2009 2010 served as co-chair of the Forum's Global Agenda Council on Leadership and Innovation for Reducing Risks from Natural Disasters. He is a Fellow of the American Association for the Advancement of Science and a Distinguished Fellow of the Society for Risk Analysis, which honored him with a Distinguished Achievement Award in 2001.
Pauly-University of Pennsylvania
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