Hear from Bo Xu, a Principal at Boston Consulting Group (BCG) and a member of GARP’s Risk and AI Advisory Committee, about GenAI use cases and challenges, as well as its impact on modeling, governance, regulation and risk careers.

Even though generative AI is in its early days, its already having a big effect in financial risk management. As a powerful, interactive technology that can understand natural language, quickly search through reams of data and provide human-style answer to questions, GenAI is being used today for everything from data processing to risk monitoring and measurement to quantitative risk modeling.

At the same time, financial institutions must decide how to properly govern GenAI, particularly as critics have expressed concerns about data leakage, intellectual property protection and third-party risk. What’s more, there are questions about the impact GenAI could have on risk jobs and about how regulators are going to respond to this innovative technology.

Relevant Links:

GARP Benchmarking Initiative

Risk Intelligence: Technology Section

Speaker’s Bio

Bo Xu serves as a Principal at Boston Consulting Group (BCG), where he is a core member of the global GenAI expert team. His professional journey at BCG began in 2019, following a four-year tenure at KPMG in the risk consulting practice, concentrating on CCAR/DFAST model development and validation work.

In his role at BCG, Xu leads a multi-disciplinary team focused on AI and GenAI programs. His responsibilities encompass strategy development, AI/GenAI implementation, and change management. He also has expertise in credit risk analysis, model risk management, and data governance from his earlier career.

Hear from Cristian deRitis, deputy chief economist at Moody’s analytics, about the evolution of stress testing, current trends, and the biggest challenges facing banks and regulators.

Regulatory stress tests play a vital role in ensuring that large banks hold enough capital to withstand extreme recessions, while internal stress tests at banks are used for everything from capital and liquidity planning to risk monitoring, risk identification and operational resilience.

The 2023 failures of a group of mid-sized U.S. banks, however, have led some critics to question whether the Federal Reserve’s annual stress test is broad enough, comprehensive enough and sufficiently proactive – particularly with respect to emerging threats and rare tail risks. Globally, meanwhile, we’ve seen stress testing expand beyond capital and liquidity and into areas like climate risk, which has created a whole new set of hurdles for regulators and banks.

In the future, to address perceived flaws, it’s feasible that we could see a broadening of regulatory stress tests and changes to central banks’ approaches to scenarios. Banks, meanwhile, may consider increasing the frequency of their internal tests and expanding their use of AI models to rapidly factor in a wider array of scenarios.

Relevant Links:

GARP Benchmarking Initiative

Modeling Risk (Risk Intelligence column by Cristian deRitis)

Speaker’s Bio

Cristian deRitis is Managing Director and Deputy Chief Economist at Moody's Analytics. As the head of econometric model research and development, he specializes in the analysis of current and future economic conditions, scenario design, consumer credit markets and housing. In addition to his published research, Cristian is a co-host on the popular Inside Economics Podcast. He can be reached at cristian.deritis@moodys.com.