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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
- Evolving AI Trends in the Financial Sector
- Advantages and Obstacles of AI Integration
Module 2: AI Applications in Banking and Financial Services
- Smart Customer Support and Conversational AI
- Optimizing Credit Scoring and Lending Decisions
- Wealth Management and Robo-Advisory Solutions
- Open Banking and FinTech Innovations
Module 3: Financial Data Analytics with AI
- Strategic Data-Driven Decision-Making
- Implementing Predictive Analytics and Forecasts
- Analyzing Customer Behavior Patterns
- Predicting Market Trends
Module 4: AI for Risk Management
- Assessing Credit Risk
- Conducting Market Risk Analysis
- Monitoring Operational Risks
- Utilizing AI-Driven Early Warning Systems
Module 5: Fraud Detection and Anti-Money Laundering (AML)
- Advanced Fraud Identification Methods
- Monitoring Financial Transactions
- Developing Anomaly Detection Models
- Applying AML Compliance Strategies
Module 6: Generative AI for Finance
- Understanding Large Language Models (LLMs)
- Supporting Financial Reporting with AI
- Automating Report Creation
- Prompt Engineering for Finance Professionals
Module 7: AI Governance, Ethics and Compliance
- Principles of Responsible AI
- Adhering to Regulatory Standards in Finance
- Establishing AI Risk Management Frameworks
- Addressing Data Privacy and Security Issues
Module 8: AI Strategy and Implementation
- Creating an AI Strategic Roadmap
- Building a Strong Business Case
- Managing Change and Ensuring Adoption
- Evaluating the Success of AI Initiatives
Module 9: Practical Workshops and Case Studies
- Examining Real-World Financial AI Scenarios
- Analyzing Risk and Compliance Situations
- Demonstrations of AI Tools
- Collaborative Discussions and Practical Exercises
Requirements
Prospective participants are expected to have:
- A foundational grasp of financial services, banking, accounting, or investment principles.
- Competence in business reporting and data analysis.
- No background in AI or programming is necessary.
- A keen interest in digital transformation and emerging technological trends within finance.
Testimonials (1)
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