Information plays a key role in decision  making. In this talk, we discuss how to quantify information in risky decision problems. In particular, we frame the decision problem in terms of a simple lottery where information is a collection of events. We consider two different approaches to evaluate information: expected utility and buying price of information. We analyze the relation between two, and determine the conditions for preference reversals. The relation between the risk tolerance of the decision maker and the value of information is analyzed. We provide the conditions where a monotonic relation holds between the degree of risk aversion and the value of information. As an example the impact of different information alternatives on insurance decisions is analyzed.