Overview
Artificial Intelligence (AI) is becoming a foundational capability in finance and banking. Financial institutions are increasingly using AI to enhance risk management, fraud detection, financial analysis, customer engagement, reporting, and operational efficiency. With the rise of Large Language Models (LLMs) and Generative AI, finance professionals now have access to powerful tools that can analyse information, generate insights, and support decision-making at unprecedented speed.
However, the finance and banking sector operates in a highly regulated environment, where data confidentiality, explainability, accountability, and ethical use are critical. AI systems must therefore be understood, governed, and applied responsibly, rather than used blindly.
This course provides a practical, business-oriented introduction to AI for finance and banking professionals. Participants will learn core AI concepts, explore leading AI tools such as ChatGPT, Gemini, Copilot, Perplexity, Grok, Claude, Manus, DeepSeek, Qwen, and NotebookLM, and apply them hands-on to real financial workflows. The focus is on practical application, compliance awareness, productivity improvement, and strategic readiness, without requiring any programming background.
Skills Covered
By the end of this course, participants will be able to:
- Understand key AI concepts and terminology relevant to finance and banking
- Clearly distinguish between AI, Machine Learning, Deep Learning, LLMs, and Generative AI
- Evaluate and select appropriate AI tools for financial and banking tasks
- Apply AI tools to financial analysis, reporting, documentation, and communication
- Use AI responsibly within regulatory, ethical, and organisational boundaries
- Identify and prioritise AI use cases relevant to their own organisations
- Contribute meaningfully to AI adoption and strategy discussions in finance teams
Prerequisites
There are no prerequisites required to attend this course.
Target Audience
This course is designed for working adults and professionals, including:
- Banking and financial services professionals
- Finance managers, analysts, and executives
- Risk management, compliance, audit, and AML teams
- Credit, lending, and investment professionals
- Operations and customer service managers
- Digital transformation and innovation teams
- Business leaders responsible for AI adoption in finance
No prior AI or technical background is required.
Module 1: Understanding AI in Finance and Banking
- What is Artificial Intelligence?
- Relationship between AI, Machine Learning, and Deep Learning
- Introduction to Large Language Models and Generative AI
- How AI systems learn, predict, and generate outputs
- Key AI use cases in finance and banking:
- fraud detection and monitoring
- credit scoring and loan assessment
- risk analytics and reporting
- customer service and virtual assistants
- Strengths and limitations of AI in regulated environments
Module 2: AI Tools Landscape for Finance Professionals
- Overview of leading AI tools for finance:
- ChatGPT, Gemini, Copilot, Claude
- Perplexity, Grok, Manus, DeepSeek, Qwen, NotebookLM
- Comparing tools by:
- capabilities and limitations
- accuracy, reasoning, and reliability
- data privacy and confidentiality considerations
- Selecting the right AI tool for:
- financial research and analysis
- reporting and documentation
- internal communication and customer-facing responses
- Fundamentals of prompt engineering for finance professionals
Hands-on activities
- Writing structured prompts for financial tasks
- Comparing AI-generated outputs across multiple tools
- Identifying errors, bias, and compliance risks
Module 3: AI for Financial Analysis and Business Reporting
- Using AI to support financial statement analysis
- Identifying trends, risks, and anomalies with AI
- AI-assisted management and board reporting
- Working with spreadsheets using AI assistants:
- Excel with Copilot
- Google Sheets with Gemini
- Converting numerical outputs into business narratives
Hands-on activities
- Generating financial insights from sample datasets
- Drafting executive-ready summaries using AI
Module 4: Responsible AI, Ethics, and Compliance in Finance
- Key risks of AI usage in finance:
- hallucinations and incorrect outputs
- bias, fairness, and discrimination
- over-reliance on AI-generated content
- Regulatory and compliance considerations:
- data protection and confidentiality
- explainability and audit requirements
- Human-in-the-loop decision-making models
- Best practices for responsible and compliant AI use
Module 5: AI for Risk Management, Fraud, and Credit Support
- Role of AI in fraud detection and transaction monitoring
- AI-assisted AML documentation and reporting
- Supporting credit risk analysis using AI tools
- Generating risk narratives and explanations with AI
- Understanding AI limitations in regulated decision-making
Hands-on activities
- Analysing risk and fraud scenarios using AI
- Drafting credit and risk assessment narratives
Module 6: AI for Customer Experience and Banking Operations
- AI chatbots and virtual assistants in banking
- AI for handling customer inquiries and FAQs
- Using AI to explain banking products, policies, and procedures
- Knowledge-based AI using internal documents:
- NotebookLM and Manus
- Improving operational efficiency with AI
Hands-on activities
- Designing an AI-assisted banking FAQ
- Enhancing customer communication using AI
Module 7: AI-Enabled Workflow Automation in Finance
- Designing AI-supported workflows in finance:
- documents → analysis → reports
- Integrating AI tools into daily finance operations
- Managing risks in semi-automated workflows
- Measuring productivity, quality, and return on investment
Exercise
- Designing an AI-supported finance workflow
Module 8: AI Strategy for Finance Leaders and Decision-Makers
- Identifying high-value AI opportunities in finance departments
- Build versus buy versus partner decisions
- Developing an AI adoption roadmap
- Establishing internal AI policies, governance, and controls
- Preparing finance teams for AI-enabled roles and future skills
Workshop
- Drafting a high-level AI strategy for a finance or banking unit
Exam & Certification
This course is not associated with any Certification.
Training & Certification Guide
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