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Generative AI: Trends, Benefits and Risks

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Manage episode 445610658 series 1756199
المحتوى المقدم من GARP. يتم تحميل جميع محتويات البودكاست بما في ذلك الحلقات والرسومات وأوصاف البودكاست وتقديمها مباشرة بواسطة GARP أو شريك منصة البودكاست الخاص بهم. إذا كنت تعتقد أن شخصًا ما يستخدم عملك المحمي بحقوق الطبع والنشر دون إذنك، فيمكنك اتباع العملية الموضحة هنا https://ar.player.fm/legal.

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.

  continue reading

79 حلقات

Artwork
iconمشاركة
 
Manage episode 445610658 series 1756199
المحتوى المقدم من GARP. يتم تحميل جميع محتويات البودكاست بما في ذلك الحلقات والرسومات وأوصاف البودكاست وتقديمها مباشرة بواسطة GARP أو شريك منصة البودكاست الخاص بهم. إذا كنت تعتقد أن شخصًا ما يستخدم عملك المحمي بحقوق الطبع والنشر دون إذنك، فيمكنك اتباع العملية الموضحة هنا https://ar.player.fm/legal.

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.

  continue reading

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