Model Inputs

Definition

Model Inputs denotes the list of numerical or categorical variables (Risk Data) that are used as mathematical inputs to be processed by a Risk Model

Examples

There is a wide variety of possible model inputs:

• Continuous Numerical values (valuations, hedge sizes, continuous risk scores)
• Discrete Numerical values or Categorical variables (ratings)
• Distributions (rankings of possible scenario losses)
• Discrete indicators (yes / no)
• Tabular Data (risk allocation to positions)

Issues and Challenges

• Model inputs are frequently the outcome of previous Model Outputs creating chains of dependencies and possible Model Risk propagation
• Careful documentation of all model inputs in use is part of good Model Governance

See Also

• Model Outputs