Information sharing and regulation effect in experimental insurance markets

Recent advances in information technology and regulatory policies have changed the way firms do business in the insurance industry. Information technology has increased insurance companies’ access to information about consumer riskiness, thereby enabling the implementation of more effective organizational strategies. For example, health insurance companies may use genetic testing technologies to determine the insured’s risk of acquiring specific diseases. In addition, insurance companies may use data mining technology, intelligent search engines, and decision support tools to unravel relationships between consumer behaviors and their riskiness and their risk attitude. However, recent trends in regulatory policy tend to prohibit insurance companies from using information technology to gather and use such consumer information to price insurance policies. One example of such informational privacy legislation is the NJGPA, which prohibits individual health insurance companies in New Jersey from using any genetic information to price policies or deny coverage. It is difficult to test the impact of the regulatory policy on the insurability of individuals with real world data, because there are so many unobserved and uncontrolled factors affecting the data. Observations of agents’ behavior in a controlled experimental environment might provide insights to the economic impact of these policies. Following experimental economic methods, we test a set of hypotheses in a laboratory.