Survey respondents represent a range of sizes and regulatory regimes. Mean respondent asset size is just below 50 billion USD (median is 34 billion), though the minimum size is less than 1 billion, and the maximum size is 240 billion. Half of the respondents are public firms, and roughly one-quarter each are organized as private firms and mutual firms, respectively. Most are from the United States, though there are several survey respondents that represent a U.S. subsidiary of a European or Canadian parent organization.
Respondents have varied approaches to characterizing credit risk. We found that firms utilizing different credit risk modeling techniques have materially different responses throughout the survey, including the applications of credit risk, research agendas, portfolio allocations, and the presence and/or severity of any institutional constraints. Public stock, private stock and mutual tended not to be key differentiators of how firms model credit risk, nor did the provenance of the parent organization. Two stratifications of the data that we found significant were "large" firms (above median size) relative to small firms and "quantitative" firms versus non-quantitative firms. We define “quantitative” credit modeling approaches as Credit Migration, Structural, Reduced Form, Hybrid, Actuarial, or Credit Scoring models, and “quantitative” firms as those who practice as least one “quantitative” credit modeling approach somewhere within the organization.