The management, mitigation and measurement of model risk in financial risk models

Abstract

Financial risk models are simplifications of complex real-world phenomena used to better understand the intricate nature of an underlying process such as the loss generating process in financial risk analyses. Due to this simplification the model-representation of the real-world is by definition an approximation which implies a risk that the model may not fully reflect the real-world dynamics it is designed to mimic — this is referred to as model risk. This inherent model risk can probably not be eliminated completely since that would require an exact representation of the real-world which is arguably unattainable due to the complexity thereof. Model risk impacts a number of risk categories within financial risk, including operational risk, credit risk, strategic risk, reputational risk and more. In this dissertation a contribution is made to the management, mitigation and measurement of model risk of financial risk models. The contributions include the proposal of a standardised definition of model risk through the categorisation of model risk types based on definitions of model risk available in literature, summarising model risk mitigating techniques, the development of a practical and repeatable risk assessment method to establish model risk management maturity in a financial institution, the development of a method to measure the impact of model risk due to parameter uncertainty, and the proposal of a subjective scorecard to evaluate the relative model risk of a suite of models.