Operational risk modelling
Don’t let the SMA kill op risk modelling
The SMA is not a good response to the AMA’s failings – but don’t throw the baby out with the bathwater
HSBC shakes up risk analytics team
Internal memo attributes changes to increased demand for analytics
Europe’s banks fret over US stress tests
CCAR could expose weaknesses in capital planning at foreign banks
Op risk family tree challenges Basel’s business line focus
Cladistic analysis shows importance of control failure, crime and fraud
Operational risk models and asymptotic normality of maximum likelihood estimation
In this paper, the author studies how asymptotic normality does, or does not, hold for common severity distributions in operational risk models.
The benefit of using random matrix theory to fit high-dimensional t-copulas
This paper uses simulation studies and an example of operational risk modeling to show the necessity and benefit of using RMT to fit high-dimensional t-copulas in risk modeling.
Two-regime approach saves up to 30% op risk capital
Modelling shift to 'crisis mode' mitigates pro-cyclical calculations
Basel’s Adachi: banks may discard some loss data under SMA
Losses from discontinued businesses may not count towards op risk capital
SMA proposal fires up op risk managers
Banks say backward-looking SMA is easily gamed and will lead to high and volatile capital charges
Correlation of op risk losses could send capital soaring
BB&T auditor's model shows capital measured by LDA might be pushed up by 16–55%
Basel op risk plans 'not fit for purpose', say banks
SMA expected to raise capital charges, but lower standards in risk management
Basel op risk reform proposal expected to be delayed
Consultation on scrapping operational risk modelling is now expected in early 2016
Random matrix theory applied to correlations in operational risk
This paper focuses on the distribution of correlations among aggregate operational risk losses.
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.
Highlights from OpRisk Europe conference 2015
Exclusive coverage of London event
Op risk models must aid management to be effective, conference hears
Quantifying risks useful, but only when informing decision making
What if operational risk asked more 'what if' questions?
Banks and regulators urged to up their game in stress tests and scenario analysis
Op risk analysis underrates human behaviour – Fed examiner
Risk managers urged to focus on group dynamics
Op risk management has tangible benefits, firms claim
Advantages include lower costs and capital
Fed: future of op risk models “in the balance”
Basel Committee mulling altered AMA – or even replacement with RSA
The problems of explaining AMA volatility
A simple model highlights how AMA capital requirements can change dramatically
GE Capital dealing with Sifi status and AMA push
Systemically important status is hard enough when you're a bank – for non-bank institutions such as GE Capital, meeting the mark can be even more challenging. Enterprise and operational risk leader Ann Rodriguez discusses the reform process with OpRisk
Benchmarking and reputation risk – editorial
Managed expectations