What is Model Risk?
Financial firms use models for anything from analysing risk exposures to guiding day-to-day operations. Even minor errors in the model-building process might have significant ramifications for a bank. Data acquisition is a crucial component of it, notably input risk because models rely on it. If the model results go wrong, financial institutions’ risk is termed Model Risk.
Model risks include:
- Input risk – refers to the effect of not knowing the actual, correct distributions of the basic stochastic processes that drive a computer simulation.
- Estimation risk – The estimated risk in asset pricing is investor uncertainty regarding the return or cashflow process parameters. In a nutshell, estimation risk can help determine and test market efficiency.
- Valuation risk – Valuation risk is the risk of loss arising from the difference between the price of an instrument reported on a bank’s balance sheet – as determined by accounting rules
- Hedging risk – Hedging is a strategy for reducing exposure to investment risk. An investor can hedge the risk of one investment by taking an offsetting position in another investment. The values of the offsetting investments should be inversely correlated.
Why is managing it critical?
Automated predictive, economic, and financial models assist financial organisations in making faster and better business decisions as their use and dependence on technology grows. Hence, it is critical to assess it in an organisation.