This paper studies alternative mixing models for external data for a particular risk class.
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Operational risk loss data – October 2015
NYC-based LMRKTS first broke cover two years ago; third bank participant is unknown
Scrapping op risk modelling in Europe could take five years, say lawyers
Firms doubtful about risk sensitivity of standardised replacement charge
Free-to-view photographs from the OpRisk Awards 2015
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Cakes and candles can help risk managers get flavour right, argues Ariane Chapelle
Oracle addresses problems caused by Basel rules on data aggregation
BAE Systems uses sophisticated network analysis to curb threat of money laundering
MetricStream benefits from exclusive focus on governance, risk and compliance
FATF promotes risk-based approach in response to worries about 'de-risking'
Swift offers firms assistance in avoiding entities and individuals hit by sanctions
Thomson Reuters managed service eases burden of know-your-customer rules
Consultancy firm offers joined-up approach to ERM and operational risk issues
New technique may help limit errors in AMA capital estimates
Human failings can subvert well-intentioned efforts to avoid disaster
AMA's likely demise is latest sign of worrying trend in bank capital rules
This paper identifies three steps in sourcing 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.
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.