How Monzy Scores Credit Cards?
Most credit card review sites assign scores based on a fixed rubric, a checklist of benefits weighted by what the reviewer thinks matters.
The problem with that approach is obvious: what matters to a frequent flyer is irrelevant to someone who just wants cashback on Swiggy orders.
Monzy scores cards differently.
Our scores are situation or spend-specific, derived from the same recommendation engine we use to match real users to cards every day.
What does Monzy score mean?
A Monzy Score is always shown alongside the persona it was calculated for, for example, "7.1 / 10 for online shoppers" or "5.8 / 10 for frequent flyers."
The same card may carry different scores for different personas, and that is intentional. It reflects reality: there is no single best credit card, only the best card for a specific set of priorities.
The score is recalculated automatically whenever our recommendation logic is updated, so it stays consistent with what our engine would actually recommend, not what a static rubric from two years ago would suggest.
Steps We Use to Score Credit Cards
Here is exactly how our scoring methodology works:
Step 1: We learn what benefits actually matter for you
Before anything else, we ask your preferences. Based on that, we identify which benefit categories genuinely move the needle for you.
We do this by running a simulated preference exercise across benefit attributes — things like extra rewards on online shopping, dining benefits, lounge access, fuel cashback, entertainment perks, and so on.
Attributes that you consistently rate as important get positive weight. Attributes you consistently deprioritise get negative weight.
A card is then scored by how well its actual benefits align with that weight.
A card packed with golf benefits and international lounge access scores poorly for a user whose top priorities are Swiggy and Amazon.
A flat cashback card with no travel perks scores poorly for a frequent flyer.
Both scores are correct, for those users.
Step 2: We shortlist based on your preferences
From the shortlist, we filter out based on 3 fundamental questions about credit cards:
- Does this user want a lifetime-free card, or are they comfortable paying an annual fee for higher value?
- Do they prefer straightforward cashback, or reward points they can redeem flexibly?
- Is UPI spending a priority, or not?
These three choices eliminate many irrelevant choices.
A cashback seeker should never be matched against a rewards or miles card, and a lifetime-free preference should not be matched with premium paid cards.
Step 3: We validate the fit
Finally, we check whether the card's overall benefit profile genuinely matches the preferences revealed in the first step — not just on individual attributes, but as a complete package.
This catches cases where a card looks good on paper but is a poor fit in practice, for example a card with a strong online cashback rate but an exclusion list so long that most of a typical user’s spend earns nothing.
Cards that pass this validation cleanly receive a higher confidence score.
Cards where there is a meaningful mismatch between headline benefits and real-world fit are scored lower and flagged accordingly.