Generative AI in Financial Services
Generative AI & LLM Basics; Prompt Engineering for Finance; Financial AI Assistants; RAG Systems; GenAI Governance, Risk & Compliance; Enterprise GenAI Strategy
- Level: Advanced
- Duration: 20 hours
- Language: English
- Provider: Accredian
- Certificate on completion
About this course
An advanced, hands-on course on applying Generative AI and LLMs across banking, insurance, lending and wealth management — building AI assistants, RAG systems, and enterprise GenAI strategies, using tools like OpenAI API, LangChain and Pinecone.
What you'll learn
- Understand Generative AI architectures and LLMs
- Apply GenAI across banking, insurance, lending, and wealth management
- Design AI-powered financial assistants
- Build Retrieval-Augmented Generation (RAG) systems
- Implement prompt engineering techniques for finance
- Evaluate risks, governance, and compliance requirements
- Develop enterprise GenAI strategies for BFSI
Curriculum
Foundations of Generative AI & LLMs
- Evolution of Generative AI
- Large Language Models (LLMs)
- Transformer Architecture
- Foundation Models
- Tokenization & Embeddings
- Financial AI Landscape
Prompt Engineering for Financial Services
- Prompt Engineering Fundamentals
- Zero-Shot & Few-Shot Prompting
- Chain-of-Thought Prompting
- Financial Research Automation
- Report Generation
- Prompt Optimization
Building Financial AI Assistants
- AI Assistants for Banking
- Customer Service Automation
- Financial Knowledge Assistants
- Workflow Automation
- Conversational Design
- Deployment Considerations
Retrieval-Augmented Generation (RAG) for Finance
- RAG Fundamentals
- Vector Databases
- Embeddings & Retrieval
- Financial Knowledge Bases
- Document Intelligence
- Enterprise Search
GenAI Governance, Risk & Compliance
- Hallucinations & Reliability
- AI Governance
- Data Privacy & Security
- Model Monitoring
- Responsible AI
- Regulatory Considerations
Enterprise GenAI Strategy & Future Trends
- GenAI Adoption Frameworks
- Business Use Case Prioritization
- AI Transformation Roadmaps
- ROI Measurement
- Multi-Agent Systems
- Future of AI in Finance
Frequently asked questions
What will I build during the course?
Build a banking AI assistant, a RAG application, financial research prompts and an enterprise GenAI roadmap with prioritised use cases and ROI measures.
Which tools will I work with?
Work with Python, OpenAI API, Azure OpenAI, LangChain, LlamaIndex, Hugging Face, ChromaDB, Pinecone, Streamlit and Jupyter Notebook.
Which parts of financial services does the course apply GenAI to?
Apply Generative AI to banking, insurance, lending and wealth management.
Does the course cover hallucinations, privacy and governance?
Yes. Learn about hallucinations, reliability, governance, data privacy, security, model monitoring, responsible AI and regulatory compliance.
How is the course assessed?
Complete a financial AI assistant project, RAG demonstration, prompt engineering assessment and enterprise AI strategy presentation.
How do instalments work?
Pay ₹10,000 to register, then pay the remaining balance in instalments. The balance depends on your chosen price option: ₹70,000, ₹54,000 or ₹38,000.