AI and risk management
View AgendaKey reasons to attend
-
Learn the requirements of explainable AI models from a regulatory perspective
-
Understand the implication of AI on MRM and its processes
-
Identify best practices for mitigating fraud and AML using AI
Customised Solutions
Does your team require a tailored learning solution on this or any other topic?
Working with the portfolio of expert tutors and Risk.net’s editorial team, we can develop and deliver a customised learning to make the most impact for your team, from initial assessment to final review.
About the course
Join us for a 4-day interactive course, led by subject matter experts, to get a deeper understanding of topics such as AI model explainability, interpretability and bias.
With the fast-paced nature of AI, attending this course allows attendees to develop a stronger understanding of how AI is changing the face of traditional banking supported by practical uses of AI such as managing financial crime and impact on operational risk.
This course will guide attendees in understanding best practices for implementation of AI into their financial institution, providing insight into the tools needed to better identify the risks associated with AI and to help mitigate setbacks from immature use of AI.
Learning objectives
-
Learn to comply with regulations regarding AI
-
Differentiate between explainability and interpretability
-
Manage risks associated with bias and fairness
-
Identify key ethics indicators
-
Utilize model validation tools
-
Assess the quality and maturity of AI systems
Who should attend
Relevant departments may include but are not limited to:
-
AI/ML
-
Risk management
-
Model validation
-
Data science
-
Operational risk
-
Digital innovation
Agenda
November 28 - December 1, 2022
Time zones: EMEA / Americas
Start time: 14.00 GMT / 9.00 EST
Finish time: 16.15 GMT / 11.15 EST
Sessions:
-
AI basics and governance
-
Interpretability and explainability
-
AI ethics and conduct
-
Model risk management for AI
-
Fraud and AML: managing financial crime with AI solutions
-
Quality and maturity in AI
-
AI implementation roadmap
-
Forward looking trends for AI
Tutors
- Agus Sudjianto, Head of Corporate Model Risk at Wells Fargo
- Dr Daniel Mayenberger, Corporate & investment bank, JP Morgan
- Vishal Gossain, Practice leader, EY
- Søren Mørk, Director - head of AI risk, EY
- Ben Steiner, General manager, causaLens
Pre-reading materials
The Risk.net resources below have been selected to enhance your learning experience:
-
Vulnerabilities arise in financial services as AI and machine learning use balloons - Read article | Risk.net
-
Why machine learning quants need ‘golden’ datasets - Read article| Risk.net
-
Banks fear Fed crackdown on AI models - Read article | Risk.net
To access some of the above articles you need to have a current subscription to Risk.net. If you don’t have one now, please subscribe to a free trial
Expand your learning
Events
The premier meeting place for the risk community. Providing clarity and guidance on the fast-changing regulatory landscape of capital, credit and market risk, liquidity and derivates use.
Journals
Risk Journals deliver academically rigorous, practitioner-focused content and resources for the rapidly evolving discipline of financial risk management.
Books
Risk Books are authored by leading professionals and academics. With over 150 books spanning 1,000s of chapters, our publications team is committed to connecting readers with these world class experts.
Glossary
Regularly updated by our team analysts, journalists and producers, our glossary demystifies the terminology and acronyms used in risk management, risk transfer, policy, technology and innovation.