Models in risk management : wrong but useful / Helgard Raubenheimer

Abstract

Financial institutions include a wide range of business operations within the financial sector, including banks, insurance companies, brokerage firms, and investment companies. Society relies on the smooth functioning of the financial system and has a shared interest in its stability. Therefore financial institutions are regulated by the national government or central bank. Regulatory frameworks such as Basel and Solvency II were initially motivated to prevent institutions from insolvency and safeguard against systematic risk to protect stakeholders such as customers, policyholders, shareholders and, more broadly, society. Quantitative risk management is the science that uses probability and statistics to model the financial risks arising from these institutions and to address the regulatory frameworks. Generally, the models used in quantitative risk management are an approximation to an unknown, complex reality and model risk may arise from using inappropriate or inaccurate models when assessing or managing financial risks. We will discuss the critical role of these models in quantitative risk management and highlight some of the past failures of these models and where they are successfully used.