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Course Outline
Artificial Intelligence as a Strategic Asset in Financial Services
- The role of artificial intelligence (AI) in contemporary financial ecosystems.
- AI capabilities for fraud detection, credit scoring, and customer insights.
- Balancing the business value of AI adoption with operational complexity.
Responsible AI: Ethics and Fairness in Financial Applications
- Definition of ethical AI: core principles and industry standards.
- Risks associated with bias and discrimination in algorithmic decision-making.
- Strategies to ensure fairness, transparency, and accountability in AI systems.
Regulatory Environment for AI in Financial Services
- Overview of global AI regulations, including the EU AI Act and U.S. guidance.
- Regulatory expectations for explainability and model validation in financial applications.
- Compliance reporting and audit readiness for AI systems to meet regulatory requirements.
AI Governance and Risk Management
- Establishing internal governance frameworks for the responsible use of AI.
- Defining roles and responsibilities, such as data owners, model risk managers, and compliance leads.
- Managing third-party risks and ensuring vendor accountability in AI deployments.
AI Implementation Challenges and Success Factors
- Strategic planning and change management for the adoption of AI technologies.
- Developing the necessary skills, infrastructure, and cultural readiness within financial institutions.
- Lessons learned from early adopters in global finance regarding successful AI implementation.
Case Studies in Responsible AI for Financial Institutions
- Fintech companies using AI responsibly in lending and wealth management.
- Traditional banks modernizing risk management through the use of AI.
- Ethical missteps and their implications for public trust in financial institutions.
Designing an AI Roadmap with Ethics and Regulation in Mind
- Setting AI goals that align with strategic and compliance objectives for government and private sector operations.
- Developing a comprehensive roadmap for the ethical deployment of AI within your institution.
- Strategies for internal communication and stakeholder engagement to support responsible AI practices.
Summary and Next Steps
Requirements
- An understanding of financial services operations for government
- Familiarity with fundamental digital transformation concepts
- Interest in the strategic and ethical implications of artificial intelligence
Audience
- Executive-level leaders in banking and finance
- Fintech managers and transformation officers
- Compliance and governance professionals
7 Hours
Testimonials (2)
it went through language right up to automation and made me aware of what capabilities I have.
Declan Glennon - Teleflex Medical Europe Ltd
Course - Copilot for Finance and Accounting Professionals
The background / theory of LLMs, the exercise