Model Risk
Candlefocus EditorModel risk refers to the possibility that a financial model is not accurate enough to generate reliable estimations of future conditions. Many different factors can cause model risk - bad specifications, data errors, coding errors, or problems with calibration - and it can significantly impair decision-making capabilities within a business.
For instance, a model may be mis-specified by including variables which are not suitable for their intended purpose, or simply by not including other pertinent variables. In some cases, programming or data entry errors can also lead to incorrect model estimations – any deviations from the expected behavior of the model can cause major issues for its end users. Lastly, bad calibration of models can lead to distorted predictions.
The most commonly applied methods to reduce model risk are model testing and governance policies. Model testing involves a detailed validation of the components of a model to verify that it is properly specified and functioning correctly. In addition, independent reviews are used to double-check financial models. Companies can also enforce additional governance policies to help prevent misuse of models.
Effective model risk management strategies can help businesses protect their investments and make informed decisions with the help of financial models. Such strategies mitigate the likelihood of misusing an inadequate model and can thus reduce the chances of misinformed decision-making. Companies should thus take appropriate steps to assess, monitor, and control their model risk.