Model Risk Management – Expanding quantification of model risk
Model risk from risk models has become a focal point of discussion between regulators and the banking industry.
Model risk from risk models has become a focal point of discussion between regulators and the banking industry. As financial institutions strive to enhance their model risk management practices, the need for robust model risk quantification becomes paramount.
An introduction to model risk quantification
Many firms already have comprehensive model risk management frameworks that tier models using an ordinal rating (such as high/medium/low risk). However, this provides limited information on potential losses due to model risk or the capital cost of already identified model risks. Model risk quantification uses quantitative techniques to bridge this gap and calculate the potential impact of model risk on a business.
The goal of a model risk quantification framework
As with many other sources of risk within a financial institute, the aim is to manage risk by holding capital against potential losses from the use of individual models across the firm. This can be achieved by including model risk as a component of Pillar 2 within the Internal Capital Adequacy Assessment Process (ICAAP).
Key components of a quantification framework
An effective model risk quantification framework should be:
- Risk-based: By utilising model tiering results to identify models with risk worth the cost of quantifying.
- Process driven: By providing a system for identifying, measuring and classifying the impact of model risks.
- Aggregable: By producing results that can be aggregated and including a methodology for aggregating model results to a firm level.
- Transparent & capitalised: By regularly reporting aggregated firm-wide model risk and managing it using capitalisation.
Blockers impeding model risk quantification
Complications of quantification include:
- Implementation and running costs: Setting up and regularly running any quantification test involves significant resource costs.
- Uncovered risk: Trying to quantify all potential model risk is a Sisyphean task.
- Internal resistance: Quantification and capitalisation of model risks will require increased resources to produce, leading to higher costs, making it a hard initiative to motivate individuals to follow.
Concepts in Model Risk Quantification
Impacts of Model Risk
Model risk significantly influences financial institutions through valuations, capital requirements, and overall risk management strategies. The uncertainties tied to model outcomes can have profound impacts on regulatory compliance, economic capital, and the firm's standing in the financial ecosystem.
Model tiering is a qualitative exercise that assesses the holistic risk of a model by considering various factors (e.g. materiality, importance, complexity, transparency, operational intricacies, and controls).
The tiering output grades the risk of a model on an ordinal scale, comparing it to other models within the institute. However, it doesn't provide a quantitative metric that can be aggregated with other models.
Overlap with quantitative regulations
Most firms already perform quantitative processes to measure the performance of Pillar 1 models that impact the regulatory capital held (such as the VaR backtesting multiplier applied to market risk RWA).
Model Risk Quantification Framework - The Model Uncertainty Approach
A crucial step in building a robust model risk quantification framework is classifying and assessing the impact of model risk. The model uncertainty approach is an internal quantitative approach in which model risks are identified and quantified on an individual level. Individual model risks are subsequently aggregated and translated into a monetary impact on the bank.
Regulatory Model Risk Quantificaiton Methods - RNIV, Backtesting Multiplier, Prudent Valuation and MoC
Most banks are already familiar with quantification techniques recommend by regulators for risk management. Below we highlight some of these techniques that can be used as the basis for expansion of quantification within a firm.
Expanding Model Risk Quantification
Our approach to efficient measurement relies on two key components. The first is model risk classifications to prioritize models to quantify, and the second is a knowledge base of already implemented regulatory and internally developed techniques to quantify that risk. This approach provides good risk coverage whilst also being extremely resource efficient.