In this paper, we analyze model risks separately in pricing models and risk measurement models as follows. (1) In pricing models, model risk is defined as "the risk arising from the use of a model which cannot accurately evaluate market prices, or which is not a mainstream model in the market." (2) In risk measurement models, model risk is defined as " the risk of not accurately estimating the probability of future losses." Based on these definitions, we examine various specific cases and numerical examples to determine the sources of model risks and to discuss possible steps to control these risks. Sources of model risk in pricing models include (1) use of wrong assumptions, (2) errors in estimations of parameters, (3) errors resulting from discretization, and (4) errors in market data. On the other hand, sources of model risk in risk measurement models include (1) the difference between assumed and actual distribution, and (2) errors in the logical framework of the model. Practical steps to control model risks from a qualitative perspective include improvement of risk management systems (organization, authorization, human resources, etc.). From a quantitative perspective, in the case of pricing models, we can set up a reserve to allow for the difference in estimations using alternative models. In the case of risk measurement models, scenario analysis can be undertaken for various fluctuation patterns of risk factors, or position limits can be established based on information obtained from scenario analysis.
