Stress Testing: Latest Developments & Best Practice Approaches
Sessions include scenario design, leveraging data, integrating CECL and stress testing for climate risk.
Due to the escalation of the COVID-19 developments and the restrictions being placed on travel, Risk Training has taken the decision to provide our May, June and July training courses virtually.
The decision to move remotely has not been taken lightly, but our utmost priority is to safeguard the wellbeing of all our delegates, speakers and staff.
We are hopeful that we will be able to return to our in-person events later this year, however as this unprecedented situation is changing every day, we remain watchful but also focused on delivering this much anticipated course.
01 July 2020
2020-07-01 08:30:00 +0100
About the course
“Stress tests play a valuable role in the regulatory dialogue and in the setting of regulatory ratios, so the final outcome and the quality assessment are important for the bank.” – Antoine Bezat, head of stress testing methodologies and models, BNP Paribas (Stress-testing to improve strategic decision-making, October 2019)
This training course will provide attendees the opportunity to get an inside scoop on the latest developments in stress testing. Topics such as the CECL integration and scenario design will be thoroughly covered by industry experts. Attendees will have the chance to learn from and network with a variety of people from different financial institutions.
What will you learn?
Best practice approach to building a stress testing framework
Understand how to optimize stress tests
Address the changes and challenges of CECL
Utilize stress testing as a risk management tool
Updates on CCAR and DFAST regulatory requirements
How to leverage data from stress testing
The role AI and machine learning play in stress testing
Who should attend?
Relevant departments may include but are not limited to:
Building a stress testing framework
Regulatory update: DFAST and CCAR
Leveraging data from stress testing
Optimization of stress testing
Integration of CECL
A machine learning based approach to stress testing