Ruben D Cohen
Howden Group Holdings
Ruben’s career in the financial industry began in 1999 at Citi, London, working in Asset Management, Corporate Finance, Audit, Compliance, Operational and Credit Risk Analytics and, finally, Model Validation. After Citi, he had a spell at Bank of America working in Model Audit and prior to joining Howden Group in January 2022, Ruben worked at Aon for three years, where he was the technical lead on a number of operational risk and credit risk engagements.
Prior to entering the financial industry, Ruben spent 10 years on the faculty of Mechanical Engineering & Materials Science at Rice University in Houston, specializing in Fluid Mechanics and Thermodynamics.
Ruben has a BEng and an MS in Mechanical Engineering, an MA in Economics from McGill University, Canada; and a PhD in Mechanical Engineering from MIT.
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Articles by Ruben D Cohen
Integrating internal and external loss data via an equivalence principle
The authors put forward a means address data scarcity in operational risk modelling by supplementing internal loss data with external loss data.
Estimating the probability of insurance recovery in operational risk
The authors put forward a novel methodology for the estimation of probability of insurance recovery.
An investigation of cyber loss data and its links to operational risk
This paper investigates cyber loss data and focuses on quantifying the direct financial and compensatory losses emanating from cyber risks.
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.
How to save op risk modelling
Drop loss categories and correlations and adopt simple loss distribution, advises AMA expert
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.
An assessment of operational loss data and its implications for risk capital modeling
The author of this paper assesses operational loss data and its implications for risk capital modeling.
Even for me, AMA models are too complicated
The AMA doesn’t make any sense – but the idea of a single, simple equation does, writes Ruben Cohen