AI-driven risk management in finance
View AgendaKey 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.
Pricing options:
- 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.
Learning objectives
- 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
- Quant/analyst
- Financial crime
- Operational risk
- Risk technology
- Compliance
Agenda
October 14–16, 2024
Live online. Timezones: Emea/Americas
Agenda sessions:
- Artificial intelligence (AI): understanding fundamental dynamics
- Introduction to AI in risk management
- Implementing AI governance
- AI and data management
- Model risk management for AI
- Using AI to enhance risk management
Tutors
Antony Hibbert
AI Governance Expert
ING Bank
Antony is an AI Governance Expert at ING Bank, specializing in data protection (19+ years), cybersecurity (15+ years), risk management (4+ years), and ethics (4+ years) in the AI domain. With a background in both law and cybersecurity, he focuses on keeping the AI department at ING out of trouble and keeping the trust of its customers. He speaks regularly at international conferences about data protection and cybersecurity, like #Risk, Amsterdam. As an experienced AI Governance Expert, Antony has helped financial services and tech companies bring order to the chaos, by navigating the path to responsible AI. Currently based in the Netherlands, he has had great adventure in moving here from my hometown situated on the north coast of Australia, via the long route of London and Frankfurt.
Jesús Calderón
Managing director
Maclear Data Solutions
Jesús Calderón advises Canadian and international clients in the financial services and energy industries on the implementation of data-driven solutions for risk management in banking, insurance, capital markets, and energy trading, as well as anti-money laundering and regulatory activities. Jesús has over twelve years of experience in risk management, internal audit, and fraud investigations, where he has specialized in the application of data science and machine learning methods to optimize risk control activities and examinations.
Grigoris Karakoulas
President
InfoAgora Inc
Grigoris has over 26 years of experience in predictive modelling and risk management. He is the president and founder of InfoAgora that provides risk management consulting and more to financial services organisations. He is an adjunct professor in the department of computer science at the University of Toronto.
Prior to founding InfoAgora, Grigoris was working at CIBC as vice president of customer behavior analytics, responsible for customer decisioning and credit risk measurement solutions for adjudicating new customers and proactively managing existing ones. He has been a postdoctoral fellow in the Institute of Information Technology at the National Research Council. He is on the PRIMA subject matter boards for stress-testing and enterprise risk management and has published more than 40 papers in journals and conference proceedings. He holds a PhD in computer science.
Paul Chammas
Managing partner
CLARICE SAS
Pre-reading materials
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
A Risk.net subscription will provide you access to these articles. Alternatively, register for free to read two news articles a month.