What are the determinants of the operational losses severity distribution ? A multivariate analysis based on a semiparametric approach.

In this paper, we analyse a database of around 41,000 operational losses from the European bank UniCredit. We investigate three kinds of covariates: firm-specific, fi-
nancial and macroeconomic covariates and we study their relationship with the shape
parameter of the severity distribution. To do so, we introduce a semiparametric approach
to estimate the shape parameter of the severity distribution, conditionally to
large sets of covariates. Relying on a single index assumption to perform a dimension
reduction, this approach avoids the curse of dimensionality of pure multivariate nonparametric
techniques as well as too restrictive parametric assumptions. We show
that taking into account variables measuring the economic well being of the bank
could cause the required Operational Value-at-Risk to vary drastically. Especially,
high pre-tax ROE, efficiency ratio and stock price are associated with a low shape
parameter of the severity distribution, whereas a high market volatility, leverage ratio
and unemployment rate are associated with higher tail risks. Finally, we discuss the
fact that the considered approach could be an interesting tool to improve the estimation
of the parameters in a Loss Distribution Approach and to offer an interesting
methodology to study capital requirements variations throughout scenario analyses.