Bertrand Hassani
Université Paris 1 Panthéon-Sorbonne
Bertrand Hassani is a risk measurement and management specialist (Credit, Market, Operational, Liquidity, Counterparty etc.) for SIFIs. He is also an active associate researcher at Paris Pantheon-Sorbonne University. He wrote several articles dealing with Risk Measures, Risk Modelling, and Risk Management. He is still studying to obtain the D.Sc. degree (French H.D.R.). He spent two years working in the Bond/Structure notes market (Eurocorporate), four in the banking industry in a Risk Management/Modelling department (BPCE) and one year as a Senior Risk Consultant (Aon-AGRC within Unicredit in Milan). He is currently working for Santander where he successively held the Head of Major Risk Management position (San UK), the Head of Change and Consolidated Risk Management position (San UK), the Global Head of Advanced and Alternative Analytics position (Grupo Santander) and is now Global Head of Research and Innovations (Grupo Santander) for the risk division. In this role, Bertrand aims at developing novel approaches to measure risk (financial and non-financial) and integrating them in the decision making process of the bank (business orientated convoluted risk management), relying on methodologies coming from the field of data science (data mining, machine learning, frequentist statistics, A.I., etc.).
Follow Bertrand
Articles by Bertrand Hassani
Model risk management: from epistemology to corporate governance
In this paper, the authors conduct an analysis of model risk in an attempt to understand the main issues that lead to failures and the best way to address such issues.
Shapley allocation, diversification and services in operational risk
In this paper, the authors propose a method of allocating operational risk regulatory capital using a closed-form Shapley method, applicable to a large number of business units (BUs).
Should the advanced measurement approach be replaced with the standardized measurement approach for operational risk?
This paper discusses and studies the weaknesses and pitfalls of the SMA and the implicit relationship between the SMA capital model and systemic risk in the banking sector.