Evaluating the AMA and the new standardized approach for operational risk capital

Migueis, Marco

doi:10.1057/s41261-019-00095-z

Cited by 2 publications

(2 citation statements)

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“…The AMA is a quantitative modeling technique that relies on loss history to infer a loss distribution from which the likely amount of operational risk exposure in a severe stress scenario is deduced. Alternatively, banks apply the Standardized Measurement Approach (SMA), which involves the selection of one of the following: (1) The Basic Indicator Approach (BIA); (2) The Standardized Approach (SA); (3) The Alternative SA; and (4) the AMA (Girling, 2022;Migueis, 2019). In a consultative paper, the Basel Committee on Banking Supervision stated, "The inherent complexity of the AMA and the lack of comparability arising from a wide range of internal modeling practices have exacerbated variability in risk-weighted asset calculations and have eroded confidence in risk-weighted capital ratios.…”

Section: Operational Risk Measurement and Modelingmentioning

confidence: 99%

“…As indicated, BCBS (2016) advocates the Standardized Approach (SA) that combines the Business Indicator (BI), a simple financial statement proxy of operational risk exposure, with bank-specific operational loss data. This approach is subject to criticism from both industry and regulators (Hughes, 2021(Hughes, , 2023Migueis, 2019;Sands et al, 2018). According to Sands et al (2018 p. 1), Basel III is not "effective in creating appropriate incentives and loss absorbency to minimize negative externalities from operational risk events"…and is "almost entirely backward-looking, while operational risks are constantly evolving and the drivers of the biggest losses defy mechanistic prediction from historical data."…”

Section: Operational Risk Measurement and Modelingmentioning

confidence: 99%

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Time for a paradigm change: Problems with the financial industry's approach to operational risk

Butler,

Brooks

2023

Risk Analysis

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Organizational and risk cultures in the financial industry are argued to be the root cause of banking problems. It is concerning that financial regulators and practitioners still consider the industry to be seriously fragile in several respects, particularly to operational risks and risks associated with digital transformation and innovation—not that the risks of organizational misconduct have disappeared. The rescue of Credit Suisse in 2023 confirms this. This paper employs extant theories of organizational culture, learning, and action to critically evaluate the existing risk paradigm in banking and to highlight its deficiencies, which practitioners can only address by questioning the flawed assumptions and dysfunctional values and behaviors found to be endemic in banks. However, business and risk practitioners are also married to institutional approaches that focus on assessing risk and measuring historical losses to allocate regulatory capital, rather than forward‐looking approaches to measure and manage risk. This requires a paradigm change. This paper presents a novel risk measurement and accounting methodology, Risk Accounting, to help underpin such change. Risk accounting measures risk exposure in quantitative and qualitative terms and can be implemented using an AI‐enabled digital architecture that could solve endemic problems with risk data aggregation and analysis. Significantly, risk accounting enables a financial value to be placed on risk exposures at a granular level. This level of transparency provides an incentive to change behaviors in banks and support cultural change while providing a basis for a paradigm change in the way operational risk is managed.

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Section: Operational Risk Measurement and Modelingmentioning

confidence: 99%

Section: Operational Risk Measurement and Modelingmentioning

confidence: 99%