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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

  • Smart Customer Service and Chatbot Solutions
  • Optimizing Credit Scoring and Lending
  • Wealth Management and Robo-Advisory Platforms
  • Open Banking and FinTech Innovation

Module 3: Financial Data Analytics with AI

  • Enhancing Decision-Making through Data
  • Predictive Analytics and Future Projections
  • Analyzing Customer Behavior Patterns
  • Predicting Market Trends

Module 4: AI for Risk Management

  • Evaluating Credit Risk
  • Assessing Market Risk
  • Monitoring Operational Risks
  • Implementing AI-Based Early Warning Systems

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

  • Methods for Detecting Fraud
  • Systems for Transaction Monitoring
  • Models for Anomaly Detection
  • Applications in AML Compliance

Module 6: Generative AI for Finance

  • Large Language Models (LLMs)
  • AI-Assisted Financial Reporting
  • Generating Reports Automatically
  • Prompt Engineering for Finance Specialists

Module 7: AI Governance, Ethics and Compliance

  • Principles of Responsible AI
  • Regulatory Requirements in Financial Services
  • AI Risk Management Frameworks
  • Considerations for Data Privacy and Security

Module 8: AI Strategy and Implementation

  • Creating an AI Roadmap
  • Building the Business Case
  • Managing Change and Ensuring Adoption
  • Evaluating the Success of AI Projects

Module 9: Practical Workshops and Case Studies

  • Real-World Financial AI Use Cases
  • Scenarios Involving Risk and Compliance
  • Demonstrations of AI Tools
  • Group Discussions and Practical Exercises

Requirements

Participants are expected to possess:

  • A foundational understanding of financial services, banking, accounting, or investment concepts.
  • Experience with business reporting and data analysis practices.
  • No prior background in AI or programming is necessary.
  • A keen interest in digital transformation and emerging technologies within the financial sector.

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