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Duration 35 hours
Course Outline
Foundations of AI in Finance
- Core concepts of Artificial Intelligence
- Overview of Machine Learning and Generative AI
- Current AI trends in financial services
- Advantages and obstacles of AI integration
AI Use Cases in Banking and Financial Services
- Smart Customer Support and Chatbots
- Credit Evaluation and Lending Optimization
- Wealth Management and Robo-Advisory Solutions
- Open Banking and FinTech Innovations
AI-Driven Financial Data Analytics
- Strategic Data-Driven Decision-Making
- Predictive Analytics and Financial Forecasting
- Analyzing Customer Behavior
- Forecasting Market Trends
AI in Risk Management
- Evaluating Credit Risk
- Analyzing Market Risk
- Monitoring Operational Risks
- AI-Enabled Early Warning Systems
Fraud Prevention and Anti-Money Laundering (AML)
- Techniques for Fraud Detection
- Transaction Monitoring Solutions
- Anomaly Detection Modeling
- AML Compliance Applications
Generative AI in Finance
- Large Language Models (LLMs)
- AI-Assisted Financial Reporting
- Automated Report Creation
- Prompt Engineering for Finance Specialists
AI Governance, Ethics, and Compliance
- Principles of Responsible AI
- Regulatory Standards in Financial Services
- AI Risk Management Frameworks
- Considerations for Data Privacy and Security
AI Strategy and Deployment
- Crafting an AI Roadmap
- Building the Business Case
- Change Management and Adoption Strategies
- Evaluating the Success of AI Projects
Hands-On Workshops and Case Studies
- Real-World Financial AI Applications
- Risk and Compliance Scenarios
- AI Tool Demonstrations
- Collaborative Discussions and 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.
- No prior background in AI or programming is necessary.
- A curiosity regarding digital transformation and emerging technologies in finance.
Testimonials (1)
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