Risk management has become an essential part of the process for any company that trades derivatives. Banks and corporations own risk-management offices dedicated to the development of risk models involving market, credit and operational risk, assure controls are operating effectively, and provide research and analytical support. Their models and operations have to be compliant to current European Central Bank legislation, which supervises the process. In the thesis we provide a new machine learning approach to detect anomalies in option pricing models. The research focuses on a preliminary analysis to assess the applicability of the method, starting with an analysis of call options quoted on the S&P500 index, with historical data from 2010 to 2021.