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Daniel Mayenberger Head of Large Model Frameworks at Barclays

Profile

Daniel is the European Head of Large Model Frameworks at Barclays, covering model applications such as ICAAP, internal stress testing, IFRS9, VaR, pricing models, counterparty credit risk, economic capital and treasury. He defines the overall modelling framework standards for these model applications to ensure their effective integration into the bank’s business and consistency of modelling standards globally.


Before joining Barclays, Daniel worked at Credit Suisse as Global Head of Portfolio Model Risk Management, where he was responsible for CCAR, firm-wide stress testing, ICAAP, economic capital, liquidity and treasury models, leading a global team. He developed the entire framework for CCAR and firm-wide stress testing, including validation and modelling standards and covered the public CCAR submission in 2018 in which the bank passed its submission for the first time. Daniel established the firm-wide stress testing validation stream and successfully contributed to all ICAAP submissions.


Prior to that he was a Director and Head of Enterprise Model Risk Methodology at Bank of America Merrill Lynch, leading teams in London and New York, where he is responsible for development of high-level methodologies for model development, model validation and implementation across all model types and asset classes firm-wide. In his previous role as Head of Model Risk Strategy at BoAML, covering Global Banking and Markets, CFO / Risk and Consumer Model Risk, he devised top-level business strategies for models used to underwrite $1.1tn in credits, to manage $900bn of mortgage servicing rights and to price a $1.8tn derivatives portfolio.


Before working at BoAML, Daniel worked as Vice President in Portfolio Risk Management at Deutsche Bank. In that capacity he was covering quantitative market projects, methodologies and production of VaR, Economic Capital and automation of stress testing. He was also responsible for risk analyses to inform board-level decisions and developed hedging strategies to reduce trading RWA by €3.5bn.


Daniel worked as Manager for KPMG in Frankfurt on cutting-edge financial engineering projects for multiple internationally operating banks and more than 120 corporate clients. He conducted professional training in the most advanced quantitative finance methods that were attended by KPMG managers at the most senior level across the company.


Daniel holds a doctorate in pure mathematics from the University of Trier and an Executive MBA with distinction from London Business School.