AI in Banking & Finance

Save. Predict. Secure.

Course Objective
This foundational course explores how Artificial Intelligence is transforming the financial services landscape. Perfect for banking professionals, finance students, and tech-curious learners, it blends real-world tools, simplified AI concepts, and practical simulations. From automating repetitive banking tasks to predicting risks and safeguarding data, this course will help you understand how AI is used to improve financial decision-making, enhance customer experience, and ensure digital security — all without requiring a coding background.

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Module 1:
AI in Financial Services – A 360° Introduction

  • What is AI and how is it different from automation?
  • Core uses of AI in the banking system
  • Global and Indian case studies: SBI YONO, Paytm AI, JPMorgan COIN
  • 📌 Activity: Learners map AI applications across various financial departments (lending, investment, KYC, fraud detection, customer service).

Module 2: AI-Driven Customer Service

  • Chatbots, IVRs, and financial virtual assistants (e.g., HDFC’s Eva)
  • Demo of tools like Tidio, ManyChat, or ChatGPT
  • Creating a simple loan inquiry bot using drag-and-drop tools
  • 📌 Hands-On: Build a customer support bot that answers FAQs about personal loans.

Module 3: AI in Fraud Detection

  • Understanding fraud patterns using AI
  • Introduction to anomaly detection
  • How real-time monitoring works (cards, wallets, accounts)
  • Tools demo: Google AutoML anomaly detection
  • 📌 Simulation: Spot fraud in transaction datasets using provided templates.

Module 4: AI for Credit Scoring

  • Traditional credit scoring vs AI-based dynamic scoring
  • Introduction to financial datasets
  • How AI finds relationships between repayment behavior and risk
  • 📌 Mini Project: Use a spreadsheet + ML add-on to simulate credit score predictions.

Module 5: AI in Investment & Wealth Management

  • Robo-advisors (e.g., Zerodha, Groww AI)
  • Portfolio optimization using AI
  • Predictive models in trading and asset management
  • 📌 Workshop: Build an AI-powered “investment assistant” using ChatGPT prompts or no-code templates.

Module 6: AI & Financial Regulations

  • RBI, GDPR, and data security in AI systems
  • Case study: What went wrong in the Equifax breach?
  • Ethics: Bias in AI credit scoring, surveillance, and financial inclusion
  • 📌 Classroom Debate or Roleplay: Ethical dilemma in approving an AI-based loan rejection.

Module 7: Final Capstone Project

  • Choose one track:
  • Track A: Build a chatbot for a bank product (FD, home loan, insurance).
  • Track B: Simulate a fraud detection alert system.
  • Track C: Design a financial dashboard powered by AI tools.

Module 8: AI-Powered Customer Insights & Personalization

  • What You’ll Learn:
  • How banks and financial services use AI to analyze customer behavior
  • Basics of predictive analytics in financial marketing
  • Personalization strategies using AI (email offers, investment plans, chat responses)
  • Tools like Tableau Public, ChatGPT, and Segment for insights
  • Real examples of customer segmentation and micro-targeting
  • 🛠 Hands-On Activity:
  • Create a mock customer persona dashboard using AI-generated insights
  • Design an AI-powered personalized finance plan or offer campaign
  • 📈 Why It Matters:
  • Understanding customers better means smarter marketing, improved satisfaction, and better conversion — a must-know skill in digital banking.

Learning Tools & Platforms Used

  • ChatGPT
  • Google Sheets + ML add-ons
  • Tidio / BotPress (for chatbot creation)
  • AutoML tables (for predictions)
  • Canva AI for infographic creation
  • Case study kits (PDFs + video summaries)

📈 Learning Outcomes

By the end of this course, learners will:

  • After completing the course, learners will:
  • Confidently discuss key applications of AI in banking and finance.
  • Design basic AI-powered workflows (like credit scoring or support bots).
  • Apply ethical and compliance principles in financial AI use.
  • Be prepared for internships, interviews, and practical AI use in finance.

Duration:

  • Total Duration: 6 weeks
  • Total Learning Time: ~24 hours
  • Weekly Commitment: ~4 hours/week
  • Structure:
  • Week 1: Introduction to AI in Finance
  • Week 2: AI in Customer Service
  • Week 3: Fraud Detection
  • Week 4: Credit Scoring
  • Week 5: Investment Tools + AI Ethics
  • Week 6: Capstone Project & Portfolio
  • This course made AI in finance so easy to understand. I built my own chatbot by Week 2!
    Meenal S.
    B.Com Student
  • I finally understand how fraud detection works behind the scenes — the simulation was brilliant!
    Arjun D.
    MBA Finance Intern
  • The weekly structure was perfect for my schedule. I could learn at my own pace and still build a project.
    Neha K.
    Working Professional
  • As someone with no tech background, I was nervous. But the tools were simple, and now I’m confident with AI basics.
    Ravi B.
    Bank Clerk
  • Great blend of finance and future tech! The investment bot activity was a highlight for me.
    Tarun S.
    Final Year BBA Student
  • Highly recommend this for anyone entering the banking world. The course is practical, engaging, and current.
    Divya M.
    Banking Aspirant
  • The instructors broke complex ideas into simple steps. I even used some of the tips in my internship presentation.
    Harshil R.
    Finance Intern at a FinTech Startup
  • The fraud detection project opened my eyes to how AI fights cybercrime. Loved the real-life examples.
    Aditi V.
    Cybersecurity Student

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