Relative uncertainty in term loan projection models: what lenders could tell risk managers

Abstract

This article examines the epistemology of risk assessment in the context of financial modelling for the purposes of making loan underwriting decisions. A financing request for a company in the paper and pulp industry is considered in some detail. The paper and pulp industry was chosen because (1) it is subject to some specific risks that have been identified and studied by bankers, investors and managers of paper and pulp companies and (2) certain features of the industry enable analysts to quantify the impact of specific risk events of a given dimension on a company's future financial performance. While companies in other industries may be subject to similar risk factors, the impact of risk events may be more difficult to gauge in those industries. The ability of financial analysts to model the impact of a risk event, and hence quantify a credit risk, increases the predictive accuracy of the model. I argue that bankers and regulators should recognise the uncertainty associated with unquantifiable credit risk in financial models, and they should view this uncertainty as a credit risk factor in and of itself. Evaluating the relative degree to which credit risk is quantifiable in financial models is a potentially significant yet largely unrecognised tool for credit risk management. I consider some possible applications of this assessment tool for managing risk within the banking industry.