Expected Loss and Impact of Risk: Backtesting Parameter-Based Expected Loss in a Basel II Framework

The dependency structure of credit risk parameters is a key driver for capital consumption and receives regulatory and scientific attention. The impact of parameter imperfections on the quality of expected loss (EL) in the sense of a fair, unbiased estimate of risk expenses, however, is barely covered. So far there are no established backtesting procedures for EL that quantify its impact with regards to pricing or risk-adjusted profitability measures. In this paper, a practically oriented, top-down approach to assessing the quality of EL by backtesting with a properly defined risk measure is introduced. In a first step, the concept of risk expenses ("Cost of Risk") has to be extended beyond the classical provisioning view, toward a more adequate capital consumption approach ("Impact of Risk"). On this basis, the difference between parameter-based EL and actually reported Impact of Risk is decomposed into its key components. The proposed method will deepen the understanding of the practical properties of EL, reconcile the EL with a clearly defined and observable risk measure and provide a link between upcoming IFRS 9 accounting standards for loan loss provisioning and the regulatory capital requirements under the internal ratings-based approach (IRBA). The method is robust irrespective of whether parameters are simple, expert-based values or highly predictive and perfectly calibrated IRBA-compliant methods, as long as the parameters and default identification procedures are stable. The attached pdf is aligned with respect to numbering of formulas, lemmas etc to the published version to simplify referencing. The terminology got slightly updated to provide a more consistent basis for further empirical research: PL/NPL Backtest is replaced by PL/NPL Dashboard.