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 Duration 35 hours

Course Outline

Module 1: Introduction to AI in Finance

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

Module 2: AI Applications in Banking and Financial Services

  • Intelligent customer service and chatbot technologies
  • Credit scoring and optimization of lending processes
  • Wealth management and robo-advisory solutions
  • Open Banking and FinTech innovations

Module 3: Financial Data Analytics with AI

  • Data-driven decision-making strategies
  • Predictive analytics and forecasting methods
  • Analysis of customer behavior patterns
  • Prediction of market trends

Module 4: AI for Risk Management

  • Assessment of credit risk
  • Analysis of market risk
  • Monitoring operational risks
  • AI-powered 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
  • AI risk management frameworks
  • Considerations for data privacy and security

Module 8: AI Strategy and Implementation

  • Creating an AI roadmap
  • Developing the business case
  • Managing change and adoption
  • Measuring 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 hands-on exercises

Requirements

Participants are expected to bring the following:

  • A foundational knowledge of financial services, banking, accounting, or investment principles.
  • Experience with business reporting and data analysis.
  • No prior background in AI or programming is necessary.
  • A curiosity toward digital transformation and emerging technologies within the finance sector.

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