AI Risk Management in Finance
AI can deliver significant business value - but only when its specific risks are actively managed.
From August 2026, financial institutions must comply with Article 9 of the AI Act, requiring a risk management system for AI systems used in credit and insurance risk assessments. This course is essential for professionals in governance, compliance, and risk management roles who want to integrate AI risk into their overall risk framework, as well as for AI leaders aiming to operationalize trustworthy AI together with risk stakeholders.
The objective of this training is to:
- understand the necessity of AI risk management and the specific risks involved;
- gain insight into leading AI risk management frameworks;
- learn how to make AI risk management interoperable with existing risk, security, and compliance frameworks;
- discover best practices to manage AI risks across the entire AI lifecycle.
Total price *
Members: € 550
Non-members: € 650
Partners/ BZB: € 550
Incompany: tailor-made, prices on request
* Price: service in the context of continuing professional training, exempt from VAT
CPD Hours
Banking: 6h general
Insurances: 6h general
Consumer credit: 6h general
Mortgage credit: 6h general
Compliance:
6h
Continuing Professional Development
Please let us know you're interested in this training should there be no date available, the planned date does not suit you and/or this session is full. As soon as about 5 people are registered on the interest list, we will propose a new course date. Your registration on the interest list is free of charge and without any obligation.
Target group
This training course can be followed by multiple target groups:
- Risk, compliance, audit, and governance roles: Risk officers, legal and regulatory professionals, compliance officers, data protection officers
- AI, data & innovation roles: AI governance officers, chief innovation officers, data governance managers
- Fintech entrepreneurs and investors seeking to align innovation with regulatory expectations and safeguard trust
- …
Required prior knowledge
Advanced level training: this training requires a general basic knowledge of the subject.
Programme
CONTENT
- Why AI Risk Management?
- Categories of AI-specific risks (bias, opacity, drift, adversarial attacks, etc.)
- Repositories and tools: MIT AI Risk Repository, Mitre Atlas, Pot4AI
- Overview of Leading AI Risk Management Frameworks
- EU AI Act: Art. 9 and related standards
- EN AI Risk Management Standard & AI Cybersecurity Guidelines
- NIST AI RMF & AI Cybersecurity
- ISO/IEC 23894:2023
- MITRE’s Sensible Regulatory Framework for AI Security
- Integrating AI into Existing Risk Frameworks
- Mapping AI risks to traditional risk domains (security, privacy, business continuity)
- Making AI risk management interoperable with existing ERM/IRM processes
- Mastering the AI Risk Lifecycle
- Risk Analysis: Identifying AI hazards and estimating risks
- Risk Treatment: Defining controls, setting thresholds, evaluating effectiveness
- Monitoring & Review: Ensuring control effectiveness over time
- Recording & Reporting: Documentation and audit readiness
PRACTICAL INFORMATION
- Duration: 1 day of training (6 class hours)
- Hours: 09:00 to 17:00
- Location: Febelfin Academy: Phoenix building, Koning Albert II-laan/Boulevard du Roi Albert II 19, 1210 Brussels
- Language: This training will be given in English
Methodology
You follow a ‘Classroom training’ in a group. You, the other participants and the teacher are all present in the same classroom at an agreed time. There is an opportunity for interaction and feedback, both from the participants to the teacher and vice versa. The teaching material consists as a basis of a presentation via the MyFA learning platform, supplemented with various other items (such as digital syllabus, presentation, audiovisual fragments, etc.).
Training material: Powerpoint presentation
Teachers
Anita Annie Prinzie
Compliance & audit
