Quantifying Operational Risk Guided by Kernel Smoothing and Continuous Credibility: A Practitioners View

Abstract

This paper considers the benefits of applying sophisticated statistical techniques to challenges faced in the quantification of operational risk. The evolutionary nature of operational risk modelling to establish capital charges is recognised emphasizing the importance of capturing tail behaviour. Nonparametric smoothing techniques are considered along with a parametric base with a particular view to comparison with extreme value theory. This is presented without detailed proofs in the aim of demonstrating to practitioners the practical benefits of such techniques. The smoothed estimators embedded in a credibility approach supports analysis from pooled data across lines of business or across risk types/regions.

Keywords: practitioners view, operational risk, credibility theory, kernel smoothing, extreme value theory