Explanatory Variables

Definition

Explanatory Variables (also Characteristics, Attributes) is the set of variables (for example ratios, scalar numerical values or boolean indicators) that are used in the context of a statistical Risk Model to explain (and thus potentially also forecast) random behaviour.

Examples

• Credit Score Factors are typical explanatory variables using in Credit Scoring Models
  • In corporate credit models explanatory variables typically include financial ratios obtained from Balance Sheet / Accounting data such as Profitability, Leverage, Liquidity, Debt Coverage etc.
  • In retail credit models they typically encompass demographic information, wealth indicators etc.

Issues and Challenges

• There is no scientific means of certifying that the set of explanatory variables is comprehensive (includes all variables with explanatory power). It rests with domain experts to validate this aspect
• The adjective explanatory puts emphasis on causal relationships, in practice a Characteristic may be used without a clear view on causal influence

See Also

• Casual Chain
• Variable Types: Categorical Variable, Numerical Variable
• Dummy Variable
• Binned Variable
• Retail Credit Data, SME Credit Data