Meet your new financial advisor: AI that never sleeps and might ruin you

Everyone wants an AI tool that can help grow their money. But what if it quietly ruins it, without you even realising it? Let’s set the scene.

Suppose you have linked your salary account to a “smart” budgeting app. You have also allowed a robo-advisor to invest your savings. And you have given your digital wealth manager permission to “optimise” your portfolio.

Then one day, you log in and something feels off. Your emergency fund has been pushed into a “high-yield” product you don’t remember approving. Your credit score has mysteriously dropped 60 points. And your “AI assistant” insists that everything is fine.

That’s when it hits you; you’ve been outsmarted by your own algorithm.

Invisible black box

AI runs on data. But here’s the twist, it learns from your behaviour and other people’s mistakes.

If you spend too much on Swiggy, it assumes you are “impulsive.”
If you pay rent late, it flags you as “risky.”
If thousands of others in your income group chase short-term returns, you start thinking that’s what you want too.

What this creates is a financial mirror that reflects everyone’s biases and projects them onto you.

In India, that’s a disaster waiting to happen. AI models trained on Western data or salaried professionals often fail when applied to gig workers, small business owners, or people with multiple side hustles. Your chai-tapri owner who collects payments on UPI might be invisible to the model.

So when the system tells you, “Based on your profile, we recommend…,” it’s not divine wisdom. It’s just math built on assumptions you never agreed to.

Gautam Kalia, Head of Investment Solutions and Distributions at Mirae Asset ShareKhan, puts it simply, “Adoption and usage of AI in investment decision making shall happen only with explainability. AI systems need to be able to clearly demonstrate the logic for each decision. This will lead to trust and reliability."

“As humans, we are comfortable with other humans making mistakes. But we can't tolerate any mistake from systems. That's why blackbox systems will always need a human overlay along with another system that will check for hallucinations, misrepresentations and errors in logic,” Kalia added.

When the robots get it wrong

AI tools make mistakes all the time, but the scary part is how confidently they do it.

Picture this:

• A debt-ridden user gets a notification saying, “You qualify for a premium credit card with 2X rewards.”
• A doctor paying off a home loan is told to “diversify” into small-cap ETFs that tank six months later.
• A startup employee’s ESOP sale is logged as “bonus income,” triggering an unexpected tax hit.

All because a machine somewhere categorised a number the wrong way. AI doesn’t understand your life. It only predicts patterns. And sometimes, those predictions burn real money.

Secrets behind the code

Here’s the uncomfortable truth: most fintech apps aren’t neutral.

They make money when you spend, invest, or borrow, so their AI quietly nudges you in that direction. Hidden fees are tucked behind cheerful dashboards. Recommendation engines are trained not just for your benefit, but for their revenue goals.

Some apps even monetise anonymised spending data, your grocery bills, rent, EMIs, and selling insights to insurers and marketers. And you can not find out what variables their algorithm actually uses. Because it’s a black box, and you’re the input.

How to outsmart your money-managing AI?

If you can’t see the algorithm, you can still test its behaviour. Here’s how:

1. Audit your permissions: Check what data your finance apps have access to. You’ll be shocked at how many read SMS inboxes “for analytics.”
2. Compare multiple tools: Run the same query on two apps. If their advice differs wildly, something’s fishy.
3. Ask for explanations: If your robo-advisor changes your allocation, ask why. “Because the model said so” isn’t an answer.
4. Watch for fee creep: Hidden “advisory” or “performance” fees quietly nibble your returns. Read every disclosure.
5. Stress test: Simulate bad months, salary delays, market crashes. See if the system adapts or panics.

And most importantly, never outsource common sense. AI is great at math, not empathy.

Agentic finance and AI that explains itself

The next generation of financial AI won’t just “decide”, it will discuss.

Imagine an AI that says:

“I suggest increasing your SIP by ₹2,000 because your expenses dropped last quarter. Want me to run a 12-month projection first?”

That’s agentic finance, AI that collaborates, not commands.

In the near future, you’ll see tools that can explain every decision, justify every fee, and even negotiate on your behalf. The RBI and SEBI are already eyeing frameworks for algorithmic accountability and explainability. But until that world arrives, you’re better off being the human in charge of your own money.

Expert perspective

Trivesh D, COO, explains it bluntly, “In India’s fintech space, agentic AI that learns, decides, and trades on behalf of users is increasingly replacing human judgment. But AI never works in isolation, it’s only as good as the data and programming behind it. When those inputs are biased, incomplete, or poorly designed, the investment decisions can easily go wrong.

Algorithmic trading runs on rigid rules, ‘buy if this, sell if that.’ AI-driven systems, on the other hand, adapt to trends across vast data sets. They’re flexible, but unpredictable. A model that performs brilliantly one quarter might misread patterns the next, quietly eroding returns without the investor realising it.

“That’s where accountability comes in,” he added. “You can’t build trust in finance by relying on algorithms alone. It has to come from disclosure and accountability.”

In conclusion, AI can definitely analyse faster than any human. But it doesn’t care. It doesn’t feel guilty. It doesn’t lose sleep when your SIP underperforms or your tax bill explodes. So the question isn’t whether AI would make mistakes. It’s whether you would be able to catch them before they cost you dearly.

Your money deserves curiosity, not blind faith. The smartest algorithm in your financial life is still your own brain.