AI Risk Management in Finance
Ik schrijf in op de interesselijst
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.
Totale prijs *
Leden: € 550
Niet-leden: € 650
Partners/ BZB: € 550
Incompany: op maat, prijzen op aanvraag
* Prijs: prestatie in het kader van permanente beroepsopleiding, vrijgesteld van BTW
Bijscholingsuren
Bank: 6u algemeen
Verzekeringen: 6u algemeen
Consumentenkrediet: 6u algemeen
Hypothecair krediet: 6u algemeen
Compliance:
6u
Bijscholing
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Doelgroep
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
- …
Vereiste voorkennis
Advanced level training: this training requires a general basic knowledge of the subject.
Programma
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
Methodologie
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
Docenten
Anita Annie Prinzie
Compliance & audit
