The distinction between risk and uncertainty among credit rating analysts

The idea that risk can be calculated is central to financial markets. The overwhelming amount of available financial data and ever more sophisticated mathematical models to process the information seem to make the transformation from uncertainty into risk feasible and unproblematic. Since the 1980ies, credit rating agencies have used more and more of these models to transform the assessment of creditworthiness from a simple ordinal evaluation scale (from AAA to D) to a calculated probability of default risk. Since the crisis however, rating agencies have replied to criticism by claiming that they only give simple "opinions", not probabilities of default. They often emphasize the "qualitative" or judgmental aspect of credit ratings and rebut the idea that they calculate the risk of default.

Using semi-structured interviews, I show how credit rating analysts themselves deal with this tension between officially declaring ratings as "opinions" and their highly sophisticated rating methodologies and practices. Two narratives can be extracted from the interviews conducted. Some analysts explicitly make a distinction between risk and uncertainty. They argue that there will always be a certain amount uncertainty that cannot be transformed into risk. Accordingly, their ideas to improve the rating process is to make it even more "qualitative" and less dependent on sophisticated financial mathematics. Others, especially analysts from smaller rating agencies suggest that it is exactly this qualitative aspect in the methodology of the big rating agencies that produces uncertainty, while their own – more stochastic and feedback sensitive – methods can calculate the risk of future default of financial products accurately.