Ever been stuck in a bank queue or scrolling through loan terms and thought, “Why is finance always so complicated?”
But giants like JPMorgan, Razorpay, and HDFC are solving these same problems with a simple magic tool – AI. And the best part? You don’t need to be a big bank to use it. Anyone can.
So let’s break down how these biggest names are using AI for finance, and what simple steps you can take to get started.
JPMorgan’s AI Empire
Let’s start with the world’s largest bank: JPMorgan Chase.
This isn’t just a financial giant; it has quietly turned into an AI-first institution, running artificial intelligence across more than 400 business functions. That means almost every corner of the bank has AI baked in.
Here’s how:
- Fraud Detection – Imagine billions of daily transactions happening worldwide. Old systems took too long to catch fraud. Now, AI flags suspicious activities 50% faster. That’s like having a financial watchdog that never sleeps.
- Contract Intelligence (COIN) – Lawyers used to spend months reviewing complex legal contracts. JPMorgan’s AI tool now scans thousands of them in seconds, saving the bank 360,000 hours every year.
- AI-Driven Trading – Their wealth managers don’t just rely on gut feeling. Predictive AI models read markets, trends, and risks to help them make faster, sharper investment calls.
Lesson:
- Even if you’re not managing millions, you can set up AI-powered monitoring.
- Example: Connect your expenses and invoices in Google Sheets with Gemini AI. It can summarise cash flow, highlight sudden spikes, or even suggest where costs look suspicious.
- Use Zapier to feed bank alerts or PayPal notifications straight into Sheets. Now, Gemini or ChatGPT can scan and say: “This vendor suddenly billed you 3x more than last month — check it.”
Practical Tip: Think of it as your mini-JPMorgan fraud desk, keeping an eye on every rupee/dollar.
Razorpay’s AI Advantage
Now, let’s come home to India.
Think of Razorpay. Just a few years ago, it was a startup; today, it’s one of India’s biggest fintech players. How did it get here so fast? Simple: it embraced AI for finance early on.
Here’s what Razorpay does with it:
- Smart Fraud Detection – Razorpay’s AI system checks 100+ data points per transaction in real-time. If something looks fishy, it blocks it instantly. This alone cut fraud attempts by over 40% in 2024.
- Personalised Lending – Not every small business has a big credit history. Razorpay uses machine learning to study patterns and alternative data, so even new businesses can get loans.
- Customer Support – With over a million merchants onboard, human support would collapse. So AI chatbots now solve most queries instantly, keeping everyone happy without long wait times.
Lesson:
- You can mirror this predictive power with your customer or sales data.
- Example: Upload your client payment history into Sheets. Ask ChatGPT or Claude: “Who usually delays payments beyond 30 days?”
- Automate follow-ups: Write a small script in Replit that sends gentle reminders via email or WhatsApp to clients who are late.
- For trend spotting, Gemini can show you: “20% of your clients pay earlier if given a discount reminder.”
Practical Tip: Don’t just track payments — let AI predict behaviour and act before problems occur.
HDFC’s AI Transformation
And then comes a name every Indian household knows—HDFC Bank.
Now, HDFC could have sat back, depending on its brand power. But instead, it chose to go full throttle with AI.
Here’s how HDFC is using it:
- Eva – AI Chatbot – If you’ve used HDFC’s website, you’ve probably met Eva. This chatbot has answered over 6.5 million queries in its first six months itself, with about 85% accuracy. That’s customer care at lightning speed.
- AI-Driven Credit Scoring – Many young Indians don’t have a CIBIL score. HDFC uses AI models on alternative data to judge their creditworthiness and open doors to loans.
- Robo-Advisors – For the middle-class investor, robo-advisors give personalised wealth tips, predictive insights, and portfolio tracking—services once reserved only for the rich.
Lesson:
- At your scale, personalisation means showing customers you “get them.”
- Example: Store customer purchase or service data in Sheets. Run Gemini to summarise: “This customer usually spends on weekends” or “This client buys high-value services every quarter.”
- With Zapier, trigger personalised offers or emails when patterns are met. For example: “Offer 10% discount if someone spends above ₹10,000 this month.”
- Use Claude to analyse long customer feedback forms and find hidden needs like “better support” or “faster delivery.”
Practical Tip: Personalisation = loyalty. Even small gestures powered by AI make your service feel like HDFC-level care.
Why All These Giants Use AI
Different names, same problem: scale, fraud, and complexity.
JPMorgan in New York, Razorpay in Bangalore, and HDFC in Mumbai, each faces the same three challenges.
And AI solves them by offering:
- Speed – Shrinking processes from weeks to seconds.
- Accuracy – Reducing human error in compliance, trading, or credit checks.
- Scalability – Managing millions of transactions and queries without breaking down.
In short: AI for finance is not optional anymore; it’s the backbone of modern banking.
How You Can Use AI in Finance
Now comes the big question: How can you use AI without having JPMorgan’s billions?
The real trick isn’t fancy tech, it’s using AI tools on the data you already have.
- Start small: Begin with Google Sheets and Gemini to track patterns in expenses, payments, or customer habits.
- Automate smartly: Use Zapier to connect apps (email, payments, invoices) and save time.
- Go deeper when needed: ChatGPT and Claude can explain patterns, answer “why” something happened, or draft responses for clients.
- Experiment with scripts: If you’re a bit technical, Replit lets you build tiny automations (like auto-reminders or smart calculators).
You don’t need a bank’s budget. You just need the same mindset: AI is not a luxury anymore — it’s your everyday business assistant.
Conclusion
At the end of the day, whether it’s a giant like JPMorgan, a disruptor like Razorpay, or a trusted name like HDFC—the story is the same. They turned confusion into clarity, complexity into efficiency, and customer doubt into trust.
And they did it with AI.
So the real question for you is: Will you wait and watch, or will you start adopting AI for finance today?
If you want to move beyond reading and actually apply AI in your financial career or business, check out The WallStreet School’s AI for Finance Course Online (Live).
It’s designed to make you confident in using AI tools, automation, and data-driven decision-making — the exact skills top firms are betting on in 2025.
Your next step: Don’t just admire what banks are doing with AI. Learn it. Apply it. Grow with it.
