Basics of AI & Machine Learning for Finance

We keep hearing “AI” and “Machine Learning” everywhere.

But what do these words actually mean in the stock market?

Think about it this way:

• Netflix suggests movies based on what you’ve watched before.
• Google Maps predicts the fastest route by learning from traffic patterns.

Both are powered by AI — systems that learn from data and improve over time.

Now bring that same idea to investing.

Before we see how AI can screen stocks, let’s get these basics clear.

What is AI?

AI, or Artificial Intelligence, simply means teaching computers to “think” or “decide” like humans. Instead of giving step-by-step instructions, you show the computer examples, and it learns patterns on its own.

In finance, AI can:

• Read and summarise long reports.
• Spot patterns in stock price movements.
• Combine different types of data (like numbers, charts, and even news).

What is Machine Learning (ML)?

Machine Learning is a branch of AI. It focuses on learning from data.

Think of it like this:

• You give ML a set of past data (stock prices, company results).
• The algorithm studies the patterns.
• It then tries to make predictions or classifications.

Example:
If you feed ML data about companies that did well (strong profits, low debt), it can learn these features. Later, when you show it new companies, it may say: “This one looks similar to successful companies.”

Why Does It Matter in Finance?

Finance is full of huge amounts of data. Every day, millions of trades happen, and thousands of news headlines are published. No human can process all of this. AI and ML step in here.

They can:

• Filter stocks based on both fundamentals and technicals at once.
• Analyse sentiment from news or social media.
• Spot unusual trading activity faster than traditional screeners.
• Help investors explore ideas without spending hours in spreadsheets.

Simple Comparison

How to Try This Yourself

1. Open any AI tool that allows natural language prompts (ChatGPT, Gemini, or Perplexity AI).

2. Type a fundamental query:
   

• “Show me Indian FMCG stocks with P/E below 20 and ROE above 15%.”
  The AI will combine financial ratios and return a shortlist.

3. Now try a technical query:

• “List Nifty 100 stocks trading above 200-day moving average with RSI below 30.”
  You’ll see how the AI filters based on price action.

4. Combine both:

• “Find Indian IT companies with profit growth for 3 years, low debt-to-equity ratio, and trading above 200-DMA.”
  This shows you how AI merges fundamentals + technicals in a single step, something traditional screeners struggle with.

Caution Point

AI is powerful, but it’s not magic.

• It can make mistakes if data is wrong.
• It can hallucinate (give answers that sound correct but aren’t).
• It cannot replace your judgment or SEBI’s rules.

This is why you should see AI as a helper, not as a decision-maker.

Final Takeaway

AI and ML make finance smarter by learning from data and spotting patterns.

In stock screening, they take you beyond rigid filters and help you ask richer questions.

But don’t mistake the shortlist for a verdict — AI can guide, not decide.

The responsibility to research and act always rests with you.