Technical paper/Operational risk
Truncated lognormals as a power-law mimic in operational risk
This paper makes use of the power-law mimicry properties of the truncated lognormal distribution and shows how they fit operational risk data considerably well.
A weighted likelihood estimator for operational risk data: improving the accuracy of capital estimates by robustifying maximum likelihood estimates
This paper proposes the use of a robust generalization of MLEs for the modeling of operational loss data.
Mitigating rogue-trading behavior by means of appropriate, effective operational risk management
This paper discusses the violation of applicable firm guidelines by individuals employed by a bank or financial institution and suggests specific metrics to identify and prevent such behaviour.
Monitoring IT operational risks across US capital markets
This paper suggests an approach for assessing IT risk through an incident-based method for monitoring operational IT risk across an extended enterprise based on the ISACA Risk IT framework.
Bayesian operational risk models
This paper proposes a methodology to frame risk self-assessment data into suitable prior distributions that can produce posterior distributions from which accurate operational risk measures.
A simple, transparent and rational weighting approach to combining different operational risk data sources
The authors propose a generic weighting function based on a nonparametric approach that can be used to weight the different distributions.
Scaling operational loss data and its systemic risk implications
A scaling methodology to include external data in operational risk calculation is introduced
Operational risk modelled analytically
Regulators require banks to use an internal model to compute a capital charge for operational risk, which is thought to be sensitive to assumptions on dependence between losses that still remain a matter of debate. Vivien Brunel proposes an analytical…