Loss distribution approaches (LDAs)
How to choose the dependence types in operational risk measurement? A method considering strength, sensitivity and simplicity
The authors put forward a method for banks to choose the most appropriate dependence type based on an empirical analysis of the Chinese Operational Loss Database.
On the selection of loss severity distributions to model operational risk
This paper presents truncation probability estimates for loss severity data and a consistent quantile scoring function on annual loss data as useful severity distribution selection criteria that may stabilize regulatory capital.
Estimation of losses due to cyber risk for financial institutions
The objective of this paper is to analyze cyber risk from an operational risk perspective and to measure cyber risk empirically.
Quants propose new method of calculating op risk VAR
So-called ‘incremental value-at-risk’ offers future snapshot of op risk exposure, authors say
Cyber modelling masks scale of potential losses, study finds
Different statistical approaches produce big variations in future loss estimates, says Esma researcher
Operational risk measurement: a loss distribution approach with segmented dependence
This paper proposes an approach, called the loss distribution approach with segmented dependence (LDA-SD), which can model the different dependencies of HFLI and LFHI losses in the framework of LDA.
Wells Fargo adds $2 billion to op risk capital
Risk-weighted asset increases follow wave of regulatory sanctions
Quants tout exposure-based approach to op risk modelling
Ebor especially suited to modelling loss events such as legal claims, say proponents
Operational risk measurement beyond the loss distribution approach: an exposure-based methodology
In this paper, the authors present an alternative quantification technique, so-called exposure-based operational risk (EBOR) models, which aim to replace historical severity curves by measures of current exposures and use event frequencies based on…
An operational risk capital model based on the loss distribution approach
In this paper, the author constructs a capital model for operational risk based on the observation that operational losses can, under a certain dimensional transformation, converge into a single, universal distribution.
Modeling catastrophic operational risk using a compound Neyman–Scott clustering model
In this paper, the authors discuss the hazard generated by OpRisk driven by natural and human-made disasters, and argue the position of the LDA as the most-fitted statistical approach to deal with it.
Pillar 2 moves to centre stage for op risk capital
US banks set for sharp falls in Pillar 1 requirements, but regulator-set add-ons cloud SMA’s impact
Standardized measurement approach extension to integrate insurance deduction into operational risk capital requirement
The SMA proposed in BCBS (2016) presents several issues: in particular, its two components are not sufficient to discriminate banking institutions by risk profile, thus penalizing the more virtuous ones. This paper describes a possible solution to extend…
Toward an efficient people-risk capital allocation for financial firms: evidence from US banks
In this paper, the authors address the issue of an efficient people-risk capital allocation for financial institutions.
How to save op risk modelling
Drop loss categories and correlations and adopt simple loss distribution, advises AMA expert
A note on the standard measurement approach versus the loss distribution approach–advanced measurement approach: the dawning of a new regulation
This paper presents a nonexhaustive review of the literature on operational risk quantification under a combination of the loss distribution approach model – the most commonly used of the AMA models – and extreme value theory.
Fast, accurate and straightforward extreme quantiles of compound loss distributions
In this paper, the author presents an easy-to-implement, fast and accurate method for approximating extreme quantiles of compound loss distributions (frequency + severity), which are commonly used in insurance and operational risk capital models.
The issues with the standardized measurement approach and a potential future direction for operational risk capital modeling
This paper discusses the criticism and praise the SMA and AMA have received, respectively, in many recent articles.
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.
Optimal B-robust posterior distributions for operational risk
The aim of this paper is to integrate prior information into a robust parameter estimation via OBR-estimating functions.
Operational risk modelling – finally?
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