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Recovery, resolution and liquidity

Your recovery, resolution and liquidity highlights on the RiskMinds International 2018 agenda

Recovery, resolution and liquidity agenda

  • Funding and resolution: how to meet the requirements?
  • Liquidity and resolution: getting a leg-up back to business as usual
  • Clarification on the identified substantive impediments sanctions for banks
  • Will the new category of non-preferred senior debt issued by banks under the directive (EU) 2017/2399 finally make European G-SIBS resolvable?
  • Complying with new TLAC requirements
  • How will Internal MREL/TLAC work within the banking union?
  • Internal MREL: what should the instruments look like?

Why Not Also Attend:

The Global Risk Regulation Summit

International supervisors join together with heads of regulation from global banks to review the latest regulatory horizon. Themes include rethinking financial stability, the final Basel rules, ECB's priorities, BOE's transition to risk free rates, resolution in Europe, ring fencing banking, EBA's stress testing lessons, adoption of FRTB, regulating innovation, the GDPR journey and dealing with disruption and diversification.

Stress Testing: Theory and Practice Workshop

Workshop leader: Ken Abbott, Former US IHC Chief Risk Officer, Barclays & Professor, Baruch College, CUNY and Thomas Groen, Head of Capital Risk, Barclays

This will be an interactive workshop focusing on the theory and practice of enterprise wide stress testing for banks.  It will explain the evolution of stress testing over recent years and define the many different stress tests currently run by banks.  It will compare the different approaches of regulators and provide practical guidance for those involved in implementing stress testing programmes within banks.

Machine Learning in Finance Workshop

Workshop leader: John Hull, Maple Financial Professor of Derivatives & Risk Management at Joseph L. Rotman School of Management, University of Toronto   

This workshop is designed for participants who are new to machine learning and want to acquire skills in this area.  In order to succeed in finance, individuals need to understand enough about machine learning to use it as a tool. This means that they must (a) understand in a general way how the algorithms work, (b) know how to interpret machine leaning output and be able to make decisions on next steps in an analysis, and (c) communicate effectively with data-science professionals. The workshop will focus on developing these skills.