Live Online Training Course: Stress Testing
A structured online course delivered in four half day sessions over four days, focused on adapting stress testing to meet contemporary challenges
4-7 May 2021
Online, United States of America
- Why You Should Attend
Live Online Training Course: Stress Testing
To ensure we meet your expectations and maximise your return on training investment, we favour a classroom/workshop style set up for the delivery of our courses. Please note we therefore have a limited number of spaces available and these will be assigned on a first come, first accepted basis. We recommend early booking to avoid disappointment.
Stress testing has long been a critical element of risk management within banks and other financial institutions, particularly those regulated by the Federal Reserve and subject to CCAR. Although banks have experience in this field, the emergence of new types of risk and continued economic volatility mean that it is crucial for them to evaluate their current processes and ensure that they are able to adapt to effectively adapt them for the current era.
Given the current travel and in-person meeting constraints associated with the coronavirus, we’ve adapted our live workshops to an online format so that there is still an opportunity to interact with the workshop leader and your peers. This 4-part online program (3 hours each session), provides understanding of the regulatory requirements and internal risk management principles related to stress testing. This also elaborates various types of stress testing programs and how practitioners can carry out stress testing and integrate it into their overall risk management framework. This will be supported by practical examples and hands-on case studies. This includes an examination of how Covid-19 has affected stress testing and what can be done to adjust stress testing practices to the new economic conditions.
How will you benefit?
Participants will gain:
- Better understanding of the factors / parameters impacting stress testing
- Ability to carry out stress testing for different risk types
- Insight into integrating stress testing into risk management
- Knowledge on how to meet the regulatory expectations around stress testing
· Advice on how Covid-19 factors should be incorporated into estimates stress testing
About your expert trainers:
Rafic Fahs is a strategic c-suite level Risk Management leader with broad experience in all risk types, including model risk, and deep quantitative expertise covering all asset classes and model types. He has transformed modeling capabilities through process innovation, advanced software and modeling techniques including AI.
Fahshas founded McGyver Analytics a financial servicing Consuting Firm and he ispartnering with Genpact to enhance their capability in the risk space and drive value for their clients in today’s challenging environment.
Fahs was most recently the Chief Model Risk Officer at Santander US, he successfully built a model risk management function, repairing significantly damaged relationships with regulators and creating a new strategic vision for Santander Holding USA SHUSA. During his tenure at SHUSA, significant changes have been made in the MRM Framework that translated into improved Model Risk Management. He was appointed as a risk subject matter expert by global Santander Risk division to accelerate risk management and enhance talent through collaboration within the Group.
Lee Medoff is the founder and CEO of Hedgehog Analytics, a data and analytics consulting firm that provides analytics services and solutions across a variety of industries, with Financial Services firms (including a number of Fintechs) a primary focus.
Lee began his career in finance with the Decision Sciences group of the credit card division of JPMorgan Chase, where he developed models to optimize the return on the bank’s card portfolio. He then joined the Models and Methodologies group of the New York Fed, where as part of Bank Supervision he focused on Credit and Operational risk, reviewing the models banks in the 2nd District used for Regulatory, Economic Capital and Stress Testing purposes. Following the Fed he moved to Moody’s Analytics Risk Management Services, where he oversaw analytics teams in New York and India developing and customizing models for the firm’s software. He was also a consultant for the Quantitative Advisory Services Group of EY’s Financial Services Risk Management practice, where he worked on stress testing, CCAR and CECL banking and trading book projects for large US and Global financial services clients, before launching Hedgehog.
He holds advanced degrees in Statistics from Columbia University and Economics from New York University.
Matt McDonald is a Managing Director at Kroll Bond Rating Agency and manages the Quantitative Modeling team, which builds and deploys financial and predictive quantitative models used in the credit rating process. Matt joined KBRA in October 2015 to develop and implement KBRA’s Quantitative Risk Management function, including Model Governance and Validation. Prior to joining KBRA, Matt held the role of Senior Manager at GE Capital, and worked on the Model Validation team. He has also worked at IBM Global Financing, priceline.com and PriceWaterhouseCoopers.
Matt has a Masters in Statistics from Columbia University, an MBA in Finance from the University of Connecticut, and a BA in Mathematics from Colgate University. He is an Adjunct Professor at the University of Connecticut.
Amir Sarosh is Assistant Vice President and Advanced Analytics Solution Leader with Genpact. He is a risk professional with extensive experience in model development, validation, monitoring and implementation of regulatory risk programs like CCAR/DFAST, IFRS9 and CECL. He is responsible for developing risk analytics solutions, products and digital accelerators for first and second lines of defense for Genpact’s global banking clients.
Amir started his career as Associate Scientist in the field of pricing and revenue management with PROS Revenue Management, Houston, Texas and led teams in analytics and modeling with Cognizant Analytics, Genpact India and Genpact US.
Amir has a Master’s in Applied Mathematics from University of Houston, Texas. He has a rigorous research and academic background in statistical modeling, AI and ML approaches, linear and non-linear optimization and operations research.
A detailed questionnaire will be sent to all course participants to establish exactly where the group training needs lie. The completed forms will be analysed by the course leader/trainer and followed by telephone if further clarification is required. As a result we can guarantee that the course is pitched at exactly the right level and that the issues that you regard as relevant are addressed. The course material will reflect these issues and will enable you to digest the subject matter after the event in your own time.
Who should attend?
From Financial Institutions, Insurance Companies, Regulators and other Federal or State supported Credit Organizations, practitioners within:
- Stress Testing
- Risk Modeling
- Model Development/Validation
- Strategic Planning
- Why Choose GFMI marcus evans?
marcus evans specialises in the research and development of strategic events for senior business executives. From our international network of 63 offices, marcus evans produces over 1000 event days a year on strategic issues in corporate finance, telecommunications, technology, health, transportation, capital markets, human resources and business improvement.
Above all, marcus evans provides clients with business information and knowledge which enables them to sustain a valuable competitive advantage and makes a positive contribution to their success.
- Voice of Our Customers
- “Benefitted from invaluable lessons learned” BNP Paribas
- “The practical approach solidified my understanding of the topic, well structured course” ING Bank
- Join the Discussion
- Event Contact
For all enquiries regarding speaking, sponsoring and attending this conference contact:
101 Finsbury Pavement, London, EC2A 1RS
Telephone: 0044 203 002 3172