AI-driven risk management in financeView Agenda
Key reasons to attend
- Examine the diverse applications of artificial intelligence (AI) in risk management
- Learn how to implement AI solutions and navigate the associated challenges
- Explore the most recent AI innovations shaping the future of finance
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About the course
AI has revolutionised risk management in finance, introducing groundbreaking methods to identify and mitigate risks. This course provides an in-depth exploration of AI’s role in enhancing operational, IT and financial risk management, covering the automation of manual tasks.
Participants will discover the latest regulatory frameworks affecting AI use, ethical considerations and data privacy challenges. Expert-led sessions will guide attendees on the practical implementation of AI solutions, considering the business need and integration with existing systems. This course also introduces AI model validation techniques and strategies for optimising model results using AI.
Attendees will learn about emerging technologies, including open banking and blockchain, equipping them with the knowledge to be at the forefront of financial innovation.
- Early-bird rate: save up to $800 per person by booking in advance (refer to the booking section for the deadline)
- 3-for-2 rate: save over $2,000 by booking a group of three attendees (applicable to this course)
- Subscriber reward: save 30% off the standard rate if you are a Risk.net subscriber (use code SUB30)
- Season tickets: save over $1,000 per person by booking 10 or more tickets (available on selection of courses)
*The 30% subscriber reward discount is applicable only to current Risk.net subscribers. If this criteria is not met, we reserve the right to cancel the booking and issue an invoice for the correct rate. Discounts cannot be applied to already registered participants.
- Uncover the latest regulatory frameworks impacting AI in finance
- Explore ethical considerations and data privacy
- Apply AI techniques to enhance operational, IT, cyber and financial risk management
- Develop skills for effective data collection and preparation
- Investigate AI model validation techniques
- Understand and counter AI-related risks
- Discover the intersection of AI and quantum computing
Who should attend
Relevant departments may include but are not limited to:
- Risk management
- IT and data
- Risk model validation
- Model risk
- Financial crime
- Operational risk
- Risk technology
June 18–20, 2024
Live online. Timezones: Emea/Apac
- Artificial intelligence (AI): understanding fundamental dynamics
- Introduction to AI in risk management
- Implementing AI governance
- AI and data management
- Using AI to enhance risk management
- AI model risk management
Daniel Garcia Risk Learning Faculty
Risk management practice lead
Daniel is a Risk & Compliance Subject Matter Expert (SME) with over 16 years of global experience, having worked for major financial institutions and consulting firms in Latin America, Europe, and Asia. Currently, he is leading the Risk Management Global Practice at Verdantix, where he leads the market research intelligence and provides advisory services on risk and compliance matters.
Daniel holds a BA degree in economics and different specialisations in Capital Markets and Financial Engineering.
Paul Chammas Risk Learning Faculty
Co-founder and managing partner
Quantum Risk Advisory
Paul Chammas is a seasoned Technology Risk & Cybersecurity consultant, auditor, and trainer, with over 14 years of experience dedicated to financial services. In 2021, he co-founded Quantum Risk Advisory (QuRISK), a startup specialized in risk management for emerging technologies, particularly focusing on Artificial Intelligence and Quantum Technologies.
With an Engineering degree in Telecommunications from EFREI Paris, a Masters in Technology Management from HEC Paris, and a Masters in Quantum Technologies from UPM Spain, Paul seamlessly blends technical expertise with strategic insight. His unwavering commitment is focused on providing organizations with the appropriate methodological tools to safely adopt cutting-edge technologies.
Director - Head of AI risk, FSO technology consulting
Søren is director, FSO Nordics AI lead and head of EY’s AI Risk team based in Copenhagen that focus on model validation of artificial intelligence (AI)/machine learning models. He established and headed one of the first dedicated AI/machine learning model validation units in Europe and is one of its leading experts on AI/machine learning model risk. He has a PhD in AI/machine learning and 15+ years’ experience as a researcher and model validator, and within all aspects of model risk management. He has been actively engaged in AI/machine learning risk management in the financial sector for the past 6 years. During the years Søren has organized and chaired roundtables on AI/machine learning model risk management with leading banks in Europe and has been invited as speaker on AI model risk at conferences and universities and advised both local FSA’s and EBA on AI/machine learning risk in the financial sector. He is a co-representative of Denmark in the CEN/CENELEC (European equivalent of ISO/IEC) Joint Technical Committee 21 for Standardization on AI, in support of the upcoming European AI act.
The Risk.net resources below have been selected to enhance your learning experience:
- Navigating the adoption of generative AI - Read article | Risk.net
- Empowering risk management with AI Read article| Risk.net
- AI in risk management: one giant leap forward or a risk too far? Read article | Risk.net
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