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 Duration 35 hours

Course Outline

Module 1: Introduction to AI in Finance

  • Core concepts of Artificial Intelligence
  • Overview of Machine Learning and Generative AI
  • Emerging AI trends in Financial Services
  • Advantages and obstacles of AI adoption

Module 2: AI Applications in Banking and Financial Services

  • Intelligent customer support and chatbots
  • Optimising credit scoring and lending
  • Wealth management and Robo-Advisory services
  • Open Banking and FinTech innovation

Module 3: Financial Data Analytics with AI

  • Data-driven decision-making processes
  • Predictive analytics and forecasting techniques
  • Analysing customer behaviour
  • Forecasting market trends

Module 4: AI for Risk Management

  • Assessing credit risk
  • Analysing market risk
  • Monitoring operational risk
  • AI-based early warning systems

Module 5: Fraud Detection and Anti-Money Laundering (AML)

  • Techniques for fraud detection
  • Transaction monitoring systems
  • Anomaly detection models
  • Applications for AML compliance

Module 6: Generative AI for Finance

  • Large Language Models (LLMs)
  • AI-assisted financial reporting
  • Automated report generation
  • Prompt engineering for finance professionals

Module 7: AI Governance, Ethics and Compliance

  • Principles of Responsible AI
  • Regulatory requirements in Financial Services
  • Frameworks for AI risk management
  • Considerations for data privacy and security

Module 8: AI Strategy and Implementation

  • Formulating an AI roadmap
  • Developing a strong business case
  • Change management and adoption strategies
  • Evaluating the success of AI projects

Module 9: Practical Workshops and Case Studies

  • Real-world financial AI use cases
  • Risk and compliance scenarios
  • Demonstrations of AI tools
  • Group discussions and exercises

Requirements

Prospective learners are expected to have:

  • A foundational understanding of financial services, banking, accounting, or investment principles.
  • Familiarity with business reporting and data analysis processes.
  • No previous experience in AI or programming is necessary.
  • A strong interest in digital transformation and emerging technologies in finance.

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