India has a credit gap problem that dwarfs most economies. Over 400 million adults lack a formal credit history. Credit card penetration sits at roughly 5–6% of the population, concentrated in metros, mostly salaried professionals and customers that banks already know through their savings relationships. The rest of the country has been largely served by informal credit, and now at high-cost through fintechs and NBFCs, or not at all.

UPI reaches a different universe. Over 300 million active users, spread across urban and rural India. These users are transacting daily at kirana stores, pharmacies, fuel pumps, and vegetable carts. These users already have a financial identity. They just don't have a credit identity yet.

Credit Line on UPI (CLOU) is the architectural answer to that gap. Pre-sanctioned credit from a bank, accessible at the moment of a UPI payment. No separate app. No form. No redirect. The scans and pays drawing from a credit line that the bank has already approved in the same flow they use to split a restaurant bill.

The numbers tell the story of where this is headed. India's EMI user base crossed 100 million in FY26. The BNPL market is projected to be growing at 22.5% year-on-year.
Today, CLOU does approximately ₹500 crore a month. UPI as a whole does ₹28 lakh crore. And industry projections now estimate that by 2030, potentially ₹1lakh crore will be driven by CLOU.
That gap is the opportunity.

Slice is the largest player to enter CLOU in a big way. It has relaunched its hugely popular slice product as a CLOU product this Monday. While the product structure remains the same - ”Slice in 3" feature for 3-month no-cost EMIs, no annual/joining fees. The delivery mechanism has changed to UPI rails from VISA rails, customer can make payment by scanning any QR code or using a UPI ID for transactions, similar to standard UPI payments. PayTM also continues its post paid product now on UPI rails in partnership with Suryoday Small Finance Bank, but is yet to scale it.

The conventional assumption about Credit On UPI's target user is "new-to-credit". That is only partially correct.

There are at least three more distinct segments  that this product can serve, and each requires a different product offering and marketing.

The first is the credit-invisible urban user: a delivery executive, a gig worker, a first-generation salaried professional in a Tier-2 city.
Regular UPI transactions, a verified mobile number, perhaps an Aadhaar-linked bank account  but no/minimal credit bureau footprint. This user has the repayment capacity. The system just has no way to see it.

The second is the thin-file MSME owner: a kirana operator, a small manufacturer, a service provider whose business runs through a UPI QR code but whose borrowing has always been informal. MSMEs contribute 30% of India's GDP and face a structural credit gap of $250-300 billion. It is a meaningful first step in building a verifiable borrowing history for this segment. (And will add on volume to the cash flow based financing done by the likes of Bharatpe and Paytm)

The third is the underserved rural or semi-urban household: where active Jan Dhan accounts exist, Aadhaar is linked, and UPI transactions have been running for 2–3 years. But no NBFC or bank has ever extended a formal credit product. This is the hardest segment to reach, and also the one where CLOU's financial inclusion argument is most compelling.

ZET's secured credit card product with SBM Bank can cater to this segment meaningfully. Within 20 days of receiving its TPAP licence in December 2025, 75% of eligible card customers had linked their RuPay credit card to UPI. Approximately 75% of ZET's card base are first-time credit cardholders  people who received a secured card backed by a fixed deposit starting at ₹2,000, and who are now transacting on a formal credit line for the first time.

CLOU is not a niche, its distribution on steroids. When you meet credit-invisible users on infrastructure they already use daily, the friction of first-time credit adoption essentially disappears. To scale CLOU to its true potential RBI will need to let NBFCs in this market, as banks have historically not been able to underwrite the aforementioned segment. They already had the data available to design such a product but haven’t. NBFCs have the hunger and the innovative mindset to be able to design and deliver such a product.

CLOU is architecturally simple. The complexity is in the layers underneath.At the surface: a bank pre-sanctions a credit line for an eligible customer. That credit line appears as a payment option within the customer's UPI app. When the customer initiates a payment, they can choose to draw from the credit line  exactly as they would choose between a savings account or a linked debit card. The merchant receives the payment instantly. The credit leg settles separately, per the bank's terms.

No new app required. No separate onboarding journey. The credit product sits inside infrastructure the customer already uses and trusts.

The product has primarily two structural variants which are popular in the market.

1. The first is a revolving credit line: a pre-approved limit the customer can draw on repeatedly, with interest charged on the outstanding balance. Example: Paytm Post Paid, Phonepe-ICICI Bank Credit Line on UPI.

2. The second is common among fintechs like ZET, Slice is a RuPay credit card linked to UPI  where the card functions as both a credit instrument and a UPI payment method, combining the economics of a credit card with the distribution of UPI.

Each variant sits in a different regulatory classification  which is, as discussed, where the complications begin. (More on this in the next section.)

What the product structure enables, at scale, is something that traditional credit delivery never could: credit at the moment of need, embedded in the moment of use, with zero additional friction for the customer and near-zero acquisition cost for the lender. A bank can go live with CLOU in 8–12 weeks. Acquisition costs run at roughly one-fifth of traditional credit card onboarding.

The most consequential thing about CLOU is not the credit line. It is the underwriting model underneath it. Traditional credit assessment in India runs on bureau data  CIBIL, Experian, CRIF. For customers with no bureau history, lenders have typically relied on income documents, bank statements, and field verification. All of it backward-looking. All of it slow. All of it dependent on the customer's willingness to produce paperwork.

UPI transaction data is different in kind, not just degree.A six-month UPI history reveals: income credit patterns (salary or business receipts), merchant category spend (groceries, fuel, EMI payments, insurance), bill payment regularity, geographic location and peer-to-peer transaction behaviour. A customer who pays electricity bills on time, receives a regular salary credit, and spends predictably across categories has a legible financial life even if no credit bureau has ever seen their name. The customer behavior pattern also provides useful details for collection.

Research by NBER (Shashwat Alok et al.) studied India's fintech lending data from 2015–2019 and found that a 1% increase in UPI transactions was associated with a 0.73% increase in formal credit  without a corresponding increase in defaults. The signal is clean. The data works.

Lenders running CLOU are already operationalising this. Early adopter banks report NPA rates under 2% for standard small-ticket CLOU transactions. The combination of pre-sanctioned limits (set by the bank's underwriting model before the transaction occurs) and real-time transaction signals (informing dynamic limit adjustment) is producing a credit product that is simultaneously lower-risk and lower-cost than any equivalent offline model.

The more interesting question and the one the industry is beginning to ask is what happens when this data loop runs continuously. Each CLOU transaction adds to the customer's financial history. Repayment behaviour feeds back into the underwriting model. Limits can be adjusted in real time. The credit relationship deepens without any incremental customer action.

That is a fundamentally different credit architecture. Not a loan product sitting on top of a payment rail. A credit system that learns from every transaction.

UPI data does not just enable CLOU. It makes CLOU smarter with every rupee transacted. Whoever builds the best decisioning model on this data will not just issue more credit, they will build India's most accurate financial identity layer for the underserved.

CLOU's promise is large. So are the risks if it scales without the right framework. The industry has seen this before BNPL grew fast, underwriting discipline slipped, and RBI stepped in with a master direction that reset the entire sector. The conditions for a repeat are worth examining carefully.

The first structural risk is concurrent lending without bureau visibility. RBI has not mandated a standard for how CLOU credit lines are reported to credit bureaus. Some banks report under the credit card master direction. Others treat it as a personal loan. Some have not standardised reporting at all. In practice, this means a customer can hold active CLOU credit lines with multiple lenders  and no single lender has full visibility into the customer's total credit exposure. This is exactly the over-leverage dynamic that preceded the BNPL correction.

The second risk is purpose drift. NPCI's July 2025 circular explicitly stated that CLOU drawdowns must be used only for the purpose the credit was originally sanctioned. A credit line approved for grocery purchases should not be drawn for peer-to-peer transfers or cash-equivalent transactions. In practice, enforcing this at a transaction level  across a network of 300 million UPI users and hundreds of merchant category codes  requires a level of real-time monitoring that most banks do not yet have in place. Then there is also the question of onboarding of UPI QR merchants which was not very diligent in the first few years, leading to a lot of non-authorised categories like gaming where payments were flowing in.

The third risk is interest rate opacity. New-to-credit customers drawing on a CLOU facility may not fully understand the cost of revolving credit. UPI's interface is designed for frictionless payment  which is a feature in the payment context and a potential problem in the credit context. A customer who treats a credit line like a savings account balance and revolves month after month at 24–36% per annum is not being served well, even if each individual transaction was technically compliant.

RBI's response, when it comes, will likely address all three. The question is sequencing. The classification circular  whether CLOU is credit card or personal loan needs to arrive before CLOU scales, not after. Once lenders have built competing infrastructure on different regulatory assumptions, harmonisation becomes significantly harder