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Course Outline

Module 1: Introduction to AI in Finance

  • Core fundamentals of Artificial Intelligence
  • Overview of Machine Learning and Generative AI
  • Current AI trends in financial services
  • Advantages and challenges associated with adopting AI

Module 2: AI Applications in Banking and Financial Services

  • Intelligent customer service solutions and chatbots
  • Optimizing credit scoring and lending processes
  • Wealth management strategies and Robo-Advisory services
  • Open Banking and FinTech innovations

Module 3: Financial Data Analytics with AI

  • Driving decisions through data analytics
  • Predictive analytics and financial forecasting
  • Analyzing customer behavior patterns
  • Predicting market trends

Module 4: AI for Risk Management

  • Evaluating credit risk
  • Analyzing market risk
  • Monitoring operational risks
  • Implementing AI-based early warning systems

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

  • Techniques for detecting fraud
  • Transaction monitoring systems
  • Models for anomaly detection
  • Applications of AML compliance

Module 6: Generative AI for Finance

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

Module 7: AI Governance, Ethics and Compliance

  • Principles of Responsible AI
  • Regulatory requirements in the financial sector
  • Frameworks for AI risk management
  • Considerations for data privacy and security

Module 8: AI Strategy and Implementation

  • Formulating an AI roadmap
  • Developing a robust business case
  • Managing change and ensuring adoption
  • Metrics for measuring AI project success

Module 9: Practical Workshops and Case Studies

  • Real-world AI use cases in finance
  • Scenarios involving risk and compliance
  • Demonstrations of AI tools
  • Group discussions and practical exercises

Requirements

Participants are expected to have:

  • A foundational understanding of financial services, banking, accounting, or investment principles.
  • Experience with business reporting and data analysis practices.
  • No prior experience in AI or programming is necessary.
  • A genuine interest in digital transformation and emerging technologies within finance.
 35 Hours

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