# Risk exposure modeling

*/Processes/Risk_exposure_modeling*

## Digital Scalar

**Band**: digital
**Digital**: 0.9
**Rationale**: With no child occupations seeded in the grounding block, the scalar is derived entirely from the process name. 'Risk exposure modeling' is inherently analytical, data-driven knowledge work involving statistical analysis and computer simulations, firmly placing it in the digital band.

## Process Profile

**Outcome**: A calibrated risk exposure model outputs quantified potential losses and scenario impacts for strategic decision-making.
**Trigger**: A scheduled assessment cycle begins or a significant change in market conditions triggers a portfolio re-evaluation.
**Key Steps**:
- Aggregate historical market data and internal asset metrics
- Define stress test parameters and risk scenarios
- Execute exposure algorithms and simulations
- Perform sensitivity analysis on key portfolio variables
- Validate model outputs against historical baselines
- Generate quantified risk exposure reports
**Measured By**:
- [Model Execution Time](/Metrics/Model_Execution_Time)
- [Value At Risk Accuracy](/Metrics/Value_At_Risk_Accuracy)
- [Scenario Coverage Ratio](/Metrics/Scenario_Coverage_Ratio)
- [Model Validation Failure Rate](/Metrics/Model_Validation_Failure_Rate)

## Neighborhood

### Who runs this

- [Hedge Fund](/CompanyTypes/Hedge_Fund) — runs · CompanyTypes