Participants will receive access to the recorded sessions of the course.
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The course will provide professionals with the knowledge of basic elements needed to establish an effective Governance framework which oversees and manages AI systems responsibly. Covering foundational concepts in AI ethics, AI risk lifecycle, and social and ethical considerations, this programme offers a high-level understanding of the components of AI governance in financial services.
Participants will also gain insights into how European regulations affect planning, development and deployment of AI systems, as well as understand core trustworthy AI principles such as explainability, interpretability, and reliability.
Furthermore, the course will explore AI Performance, model governance, and third-party system oversight, both concerning traditional AI as well as GenAI equipping professionals with the basic knowledge required to develop ethical, resilient, and compliant AI frameworks.
Training Objectives
By the end of the programme, participants will:
- Understand the primary components of AI governance programme for banks and financial institutions (FIs)
- Know how to navigate some common problems and challenges faced by Banks and FIs in building an effective AI Governance framework
- Learn about emerging standards in AI risk management and their relevance to AI Governance
- Understand via case studies how to apply concepts learned practically in their organisation
- Learn how to create effective AI risk taxonomy and AI risk management programmes for their organisations.
- Comprehend the interplay between AI governance, regulations and risk management in the AI context within Banking & Finance
Training Outline
Foundations of AI ethics and Trust
- Concept of Trustworthy AI
- Role of AI ethics
- The EU Framework for trustworthy AI
Defining and Characterising AI systems
- Defining AI
- Unique characteristics of modern AI systems
- Strong and Weak AI
Social and Ethical Dimensions
- Fairness concepts: Bias, Discrimination and exclusion
- Malicious and harmful uses: Toxicity, Dis-information and Adversarial threats
- Misinformation and hallucination
- Behavioural impact on society
Introduction to AI risks
- AI risk taxonomy and classification
- Uniqueness of AI risks and challenges in risk identification strategies
Emerging Standards in AI risk and governance
Understanding Regulations and compliance via the EU AI Act
- Major provisions for financial institutions
- Risk based classification
- Impact of non-compliance
- Impact on technology and corporate strategy
AI and Model risk management
- Traditional elements of Modern risk management
- AI risk management and traditional MRM
Introduction to AI Lifecycle, Standardisation and Evaluation
- Primer on AI lifecycle
- Governance elements across the AI lifecycle
- Importance of standardisation
- Evaluation strategies
Introduction to the AI Risk management Lifecycle
- Role and rationale for AI risk management cycle
- Elements of AI risk management cycle
Who Should Attend
- CROs (Chief Risk Officers)
- CIOs (Chief Information Officers)
- Chief Data Officers
- Chief Technology Officers
- Heads/Managers of Business Units
- Directors
- Governance, Risk and Compliance Managers and Officers
- Chief legal officers
- Legal advisors
Training Style
This course adopts a practical and interactive training approach, combining expert-led presentations with real-world case studies and open discussions. Sessions include structured lectures supported by PowerPoint presentations, interactive quizzes, and practical examples from finance and banking. Participants are encouraged to ask questions, share insights, and discuss challenges from their own professional experiences.
CPD Recognition
This programme may be approved for up to 3 CPD units in Financial Regulation. Eligibility criteria and CPD Units are verified directly by your association, regulator or other bodies which you hold membership.
In-house Training
For groups within the same organisation, this course may be customized to meet any specific needs and delivered in-house.
Training Objectives
By the end of the programme, participants will:
- Understand the primary components of AI governance programme for banks and financial institutions (FIs)
- Know how to navigate some common problems and challenges faced by Banks and FIs in building an effective AI Governance framework
- Learn about emerging standards in AI risk management and their relevance to AI Governance
- Understand via case studies how to apply concepts learned practically in their organisation
- Learn how to create effective AI risk taxonomy and AI risk management programmes for their organisations.
- Comprehend the interplay between AI governance, regulations and risk management in the AI context within Banking & Finance
Training Outline
Foundations of AI ethics and Trust
- Concept of Trustworthy AI
- Role of AI ethics
- The EU Framework for trustworthy AI
Defining and Characterising AI systems
- Defining AI
- Unique characteristics of modern AI systems
- Strong and Weak AI
Social and Ethical Dimensions
- Fairness concepts: Bias, Discrimination and exclusion
- Malicious and harmful uses: Toxicity, Dis-information and Adversarial threats
- Misinformation and hallucination
- Behavioural impact on society
Introduction to AI risks
- AI risk taxonomy and classification
- Uniqueness of AI risks and challenges in risk identification strategies
Emerging Standards in AI risk and governance
Understanding Regulations and compliance via the EU AI Act
- Major provisions for financial institutions
- Risk based classification
- Impact of non-compliance
- Impact on technology and corporate strategy
AI and Model risk management
- Traditional elements of Modern risk management
- AI risk management and traditional MRM
Introduction to AI Lifecycle, Standardisation and Evaluation
- Primer on AI lifecycle
- Governance elements across the AI lifecycle
- Importance of standardisation
- Evaluation strategies
Introduction to the AI Risk management Lifecycle
- Role and rationale for AI risk management cycle
- Elements of AI risk management cycle
Who Should Attend
- CROs (Chief Risk Officers)
- CIOs (Chief Information Officers)
- Chief Data Officers
- Chief Technology Officers
- Heads/Managers of Business Units
- Directors
- Governance, Risk and Compliance Managers and Officers
- Chief legal officers
- Legal advisors
Training Style
The training style is interactive, combining lectures, real-life case studies, group discussions, and practical exercises. Participants will engage in scenario analysis and risk assessment simulations to solidify their understanding of operational risk management.
CPD Recognition
This programme may be approved for up to 3 CPD units in Financial Regulation. Eligibility criteria and CPD Units are verified directly by your association, regulator or other bodies which you hold membership.
In-house Training
For groups within the same organisation, this course may be customized to meet any specific needs and delivered in-house.