Sophie Lavaud
Société Générale
Sophie has been working for 8 years in the banking industry. She started in 2010 in Credit Agricole as a Quantitative Analyst in Credit Risk and then focused on Operational Risk modeling from 2011 to 2014. She joined Société Générale in 2014 in the Operational Risk modeling team as a Quantitative Project Manager. She wrote papers on different topics related to operational risk measurement and graduated as a Statistician and Economist Engineer from the ENSAE. She teaches Copulas and Multiple risks measurement at ENSAI. She is now in charge of a team responsible for the data science projects meant to help the Risk division in his decision processes, the methods and production of the operational risk capital computation, the stress-testing exercises and the set up of the IFRS 9 methodological framework.
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Articles by Sophie Lavaud
Tail dependence in small samples: from theory to practice
In this paper, the authors study tail dependence by defining the conditions required for all the methods used to perform and to quantify their efficiency and accuracy.
Random matrix theory applied to correlations in operational risk
This paper focuses on the distribution of correlations among aggregate operational risk losses.