Singapore Traveller Builds AI Tool to Maximise Card Miles: What Indian Cardholders Can Learn

A Singapore resident has used artificial intelligence to build a tool that helps maximise credit card rewards, even though they wrote very little code themselves, according to reporting by The Straits Times. For Indian cardholders the message is practical: software can now help match each purchase to the card that earns the most, but the savings only count if you pay every bill in full.

The details of the tool, including how it works and how much it earned, are not covered here because only the headline of the report is available to us. What the headline does show is a shift. Tasks that once needed a programmer, such as tracking category bonuses across several cards, can now be attempted by an ordinary user with an AI assistant.

If you hold points, miles or cashback cards in India, this is worth understanding but not worth rushing into. The rewards are modest next to the interest cost of a single missed payment, and this article explains how to think about both.

Key takeaways

• According to The Straits Times, a Singaporean used AI to create a rewards-maximising tool with little coding, showing how accessible such tools have become.
• Rewards optimisation means routing each spend category to the card that earns the most on it; it does not create free money.
• On typical Indian cards, the gain from smart routing is often a few thousand rupees a year, while unpaid balances cost around 3% to 4% a month.
• Never share card numbers, CVVs or OTPs with any AI tool or app; use only spend categories and amounts you type in yourself.
• The best first step is a simple table of your own cards and their best categories, plus auto-debit for the full statement amount.

What was reported about the AI rewards tool

The Straits Times headline describes a person in Singapore who used AI to create a tool for getting the most out of credit card rewards. The wording, low on code and high on miles, suggests the builder relied on an AI assistant to produce the software instead of writing it by hand, and that the goal was airline miles.

We do not know which cards the tool covers, how it collects data, or what results the person reported, and we will not guess. Readers who want the specifics should read the original report. What we can do is explain the standing mechanics that any such tool must work with, and what they mean in an Indian context.

The broader point is that personal finance tools are no longer only for professional developers. A spreadsheet-savvy cardholder can now describe a problem in plain language and receive working software. That is useful, but it also raises the questions of accuracy, privacy and discipline that follow.

How credit card rewards and miles work in India

Most Indian credit cards reward you in one of three ways: reward points that convert to a statement credit, vouchers or travel partners; cashback credited to your statement; or airline and hotel miles, often through a transfer programme. Each rupee spent typically earns a base rate, with higher rates on chosen categories such as dining, travel, fuel or online shopping.

The catches matter as much as the headline rate:

• Caps: many cards limit the bonus points you can earn per month or per statement cycle.
• Exclusions: rent, wallet loads, fuel, insurance, utilities and government payments often earn reduced or zero points.
• Redemption value: a point is rarely worth a full rupee; the value depends on how you redeem it, and it can change.
• Fees: premium cards charge annual or joining fees that eat into the rewards, though some waive them above a spending threshold.

The Reserve Bank of India sets the framework under which card issuers operate, including disclosure of fees and charges, but issuers are free to design their own reward schemes and to change them. That is why any optimisation tool needs current data, and why the rules of your specific card, as printed in its terms, are the final word.

Worked example: what optimisation is worth in rupees

To see the scale, take a hypothetical household spending ₹50,000 a month on cards. These numbers are illustrations from standing card structures, not figures from the report.

Approach	Monthly reward	Annual reward	Annual fees	Net annual gain
One flat 1% card, no fee	₹500	₹6,000	₹0	₹6,000
Two cards: ₹20,000 at 4% on dining and travel, ₹30,000 at 1%	₹1,100	₹13,200	₹1,500	₹11,700
Same two cards, but one bill of ₹30,000 left unpaid for a month at 3.5%	₹1,100	₹13,200	₹1,500	₹11,700 minus ₹1,050 interest per month unpaid

The first two rows show that routing spend well roughly doubles the net gain, here by about ₹5,700 a year. The third row shows the risk: one month of interest on ₹30,000 at 3.5% is ₹1,050, which is close to a full month of rewards from the optimised setup. Carrying a balance for several months cancels the gain entirely.

The arithmetic is simple, which is the point. You do not need an AI tool to see whether a strategy pays; you need the rate on each card, the caps, and honesty about whether you clear the bill on time.

What AI tools can and cannot do for your cards

An AI-built tool can be good at the repetitive parts. It can compare which of your cards has the best rate for a given category, remind you of caps, track progress toward a fee-waiver threshold, and suggest when to redeem. For someone with three or four cards, that removes a lot of mental bookkeeping.

It cannot change your card's terms, guarantee that its reward data is current, or judge whether a purchase is wise. AI-generated code can also contain errors, and a tool written quickly by a non-programmer may not have been tested against the edge cases, such as merchant category codes that put a shop in a different reward bracket than you expect.

Treat any tool's suggestion as a starting point and check it against the issuer's current terms. If a recommendation looks too good, it probably relies on an old rate or misses an exclusion.

Risks: data, interest and overspending

Three risks deserve attention before you try anything similar.

Data safety. A rewards tool only needs to know your spend categories and amounts. It never needs your full card number, CVV, PIN or OTP. If an app or assistant asks for these, stop. Card fraud in India often begins with a request for an OTP under some pretext.

Interest cost. Revolving credit on Indian cards commonly costs in the region of 3% to 4% a month, which is roughly 36% to 48% a year, and late fees and GST can add to it. A personal loan is often cheaper than a rolled-over card balance; compare options on our personal loan guides and the interest rates page if you already carry a balance.

Overspending. Points chasing can push you to buy things you did not need to reach a bonus threshold. A 2% return on a purchase you would not have made is a 100% loss.

How to build a simple rewards routine this week

You can capture most of the benefit without any software. A short checklist:

1. List every card you hold, its annual fee and its base reward rate.
2. Note the one or two categories where each card earns the most, and any monthly caps.
3. Assign each of your usual spends, such as groceries, fuel, online shopping, travel and bills, to a single card.
4. Set an auto-debit for the full statement amount on every card, not just the minimum due.
5. Check your credit utilisation; keeping the balance well below the limit is generally better for your score.
6. Review once a quarter, since issuers change rates and caps.

If you are considering a new card, first check whether you qualify with the eligibility check, because repeated applications that are declined can leave hard enquiries on your credit report. And if you plan to finance a large purchase on a card and repay it over months, run the numbers in the EMI calculator before you swipe.

Who benefits and who should not bother

The people who gain most are those who already pay in full every month, spend a meaningful amount on cards, and hold at least two cards with different strengths. Frequent flyers who value airline miles may see a larger benefit if they redeem well.

People who should skip the optimisation game include anyone who revolves a balance, anyone whose card spending is small enough that the gain is a few hundred rupees a year, and anyone who finds tracking several cards stressful. For them, a single no-fee card with a flat reward, paid in full and on time, is a sound choice.

For a wider view of what is happening across cards and lending, follow our news hub for updates on rules and rates.

Frequently asked questions

Can I use an AI tool to pick the best credit card for each purchase?

Yes, in principle: you describe your cards and their reward rules, and the tool suggests which to use per category. Enter only categories and amounts, never card numbers, CVVs or OTPs. Verify its suggestions against the current terms from your card issuer, since rates and caps change.

Do credit card rewards outweigh the interest if I carry a balance?

Almost never. Rewards are typically 1% to 5% of spend, while revolving balances on Indian cards commonly cost 3% to 4% a month. If you cannot pay in full, cheaper borrowing or repaying the balance first is usually the better move.

Is it safe to share my card details with an app that promises to maximise rewards?

No. A rewards planner does not need your full card number, expiry, CVV, PIN or OTP, and you should refuse any tool that asks for them. Prefer tools where you type in categories and amounts yourself, and treat unrequested links or calls about rewards as possible fraud.

Does the Straits Times report mean this tool is available in India?

The headline describes a tool built by an individual in Singapore, and it does not say the tool is public or that it works with Indian cards. Indian card reward structures differ from those overseas, so you should not assume it applies directly.