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.
- 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