SMA could act as a floor for calculating op risk RWAs, suggests Filippo Curti
Bank treasurers call plan to underpin internal models with standardised floors “unmanageable”
Regulators could rescue op risk modelling through Pillar 2, writes former supervisor
Basel Committee to integrate insurance and divestitures, but SMA still lacks forward-looking approach
Bayesian approach touted for mis-selling and other management failures
Modelling shift to 'crisis mode' mitigates pro-cyclical calculations
This issue contains four technical papers. Two of which deal with an analysis of the SMA, one paper deals with data and another tackles statistical issues around the quantification of operational risk.
The author of this paper assesses operational loss data and its implications for risk capital modeling.
Lack of recognition in new SMA capital charge could cause market to shrink, worry insurers
Op risk researchers criticise logic of planned new capital method
Researchers offer academic justification for Basel's standardised measurement approach
How to turn uncertainties of operational risk capital into opportunities from a risk management perspective
Going beyond the regulatory requirements to operational risk measurement, the authors of this paper aim to provide relevant business applications to a bank.
Losses from discontinued businesses may not count towards op risk capital
"You will get some winners and some losers, but with this it's mostly losers," says ORX's Carrivick
BB&T auditor's model shows capital measured by LDA might be pushed up by 16–55%
Op risk professionals pour scorn on SMA charge, but some bank experts speak out in favour
Consultation on scrapping operational risk modelling is now expected in early 2016
Supervisors under pressure to finalise post-crisis reforms to capital rules
Mixing, not scaling, best approach for using external losses
Capital requirements incentivise banks and insurers to enhance op risk management
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.
Criticism of Pillar 2 risk insensitivity