๐Ÿ’ณ Credit Cards ยท FY2020โ€“FY2026 ยท Portfolio saturation story

Credit Cards โ€” Deep Dive

Portfolio stalled at โ‚น3.4L Cr for 3 quarters ยท Private banks dominate ยท PAR 180+ elevated but stable

โ‚น3.4 L CrCurrent Balance Outstanding0% YoY โ€” Effectively flat
1,102 LakhActive Cards Mar-26โ–ฒ modest growth vs prior year
6.9%PAR 180+ Mar-26Elevated โ€” highest 180+ in retail
1.6%PAR 31โ€“90% Mar-26โ–ผ Improving โ€” down from 2.5%
70.7%Private Bank Share Sep-25Structural dominance
Portfolio Asset Quality Methodology Note Lender Share Geography Hidden Insights
Portfolio (Current Balance) & Active Cards
Mar 2020 โ€“ Mar 2026 ยท Note: Credit cards report "current balance" not loan outstanding โ€” includes revolving + transacting portions
โ‚น3.4 L Cr
Current Balance Mar-26
Flat for 3 consecutive qtrs
1,102 L
Active Cards Mar-26
Growing while POS stays flat = better paydown
โ‚น30,854
Avg Balance / Card
Falling โ€” disciplined repayment
2.17x
POS growth FY20โ†’FY25
Stalled in FY25-26
Current Balance (โ‚น L Cr) vs Active Cards (Lakh) โ€” Mar 2020 to Mar 2026
The flat current balance line from Mar-25 onwards โ€” while card count grows โ€” signals the paydown dynamic: cards growing, revolve shrinking

Asset Quality โ€” Two Very Different Stories in One Metric
PAR 31-90 improving ยท PAR 180+ elevated at 6.9% ยท The deep-stress tail is the credit card's structural challenge
๐Ÿ”ด PAR 180+ at 6.9% is the highest 180+ reading across all retail products. At โ‚น3.4L Cr portfolio, 6.9% = โ‚น23,460 Cr of 6+ month delinquency. Credit cards are revolving facilities with no collateral, so recovery rates on deep delinquency are structurally lower. The improving PAR 31-90 (2.5% Sep-24 โ†’ 1.6% Mar-26) reflects early-stress management tightening. The stubborn 180+ reflects accounts that can't be recovered once the revolve trap closes.
PAR Trend โ€” Sep 2024 to Mar 2026 (Comparable Series)
Using Sep-25/May-26 reporting (WITHOUT ARCs) for comparability โ€” see methodology note
PAR Data Table โ€” Full History
โš ๏ธ Pre-Sep-24 data uses WITH-ARC methodology โ€” not comparable to post-Sep-24
PeriodPAR 31โ€“90%PAR 91โ€“180%PAR 180+%ARC Method
Jun-20232.2%6.5%5.8%WITH ARCs
Jun-20242.3%7.6%5.6%WITH ARCs
Jun-20252.2%8.3%7.4%WITH ARCs
Sep-20242.5%2.0%5.9%WITHOUT ARCs
Mar-20252.3%2.0%6.2%WITHOUT ARCs
Sep-20252.3%1.8%7.1%WITHOUT ARCs
Dec-20252.1%1.7%7.6%WITHOUT ARCs
Mar-20261.6%1.4%6.9%WITHOUT ARCs

Methodology Note โ€” ARC Inclusion Creates Data Discontinuity
Critical for anyone comparing credit card PAR across reporting periods
โš ๏ธ The Jun-24 PAR 91-180 of 7.6% vs Sep-24's 2.0% is NOT a dramatic improvement โ€” it's a methodology change. Jun-24 data (from the Jun-25 report) includes accounts sold to Asset Reconstruction Companies (ARCs) as "outstanding" โ€” inflating PAR 91-180. The Sep-25 and May-26 reports exclude ARC-transferred accounts, showing the cleaner "active book" PAR. These two series cannot be compared directly. Any analysis mixing Jun-series data with Sep/Mar-series data for credit cards will show a false improvement in PAR 91-180 that does not exist in the underlying portfolio.
Comparable PAR Series: Without-ARC Only (Sep-24 to Mar-26)
The only apples-to-apples comparison available for credit cards

Lender Share โ€” Private Bank Oligopoly
HDFC Bank, SBI Cards, ICICI Bank, Axis Bank control ~80%+ of the market ยท PSU banks and NBFCs structurally excluded
Portfolio Share โ€” Private Banks vs Others (Mar-22 to Sep-25)
Private bank dominance strengthening โ€” from 67.5% (Mar-22) to 70.7% (Sep-25)
70.7%
Private Banks ยท Sep-25 POS share
HDFC Bank, SBI Cards, ICICI, Axis, Kotak โ€” top 5 control ~70% alone
29.3%
Others (PSU Banks, fintechs, co-brand NBFCs)
Shrinking โ€” PSU banks never built card infrastructure; NBFCs limited by RBI
โš ๏ธ No new private bank has successfully launched a credit card business from scratch in 10 years โ€” the network effects and interchange economics are an effective moat.

Geography โ€” Most Metro-Concentrated Product in Retail
Top 8 cities dominate โ€” credit cards remain a formal-salaried, urban product despite 15 years of "financial inclusion" pushes
Credit Card Outstanding by City Tier vs Other Products
Credit cards have the lowest BT100 share โ€” the structural urban concentration is not changing

Hidden Insights
The most complex product in retail credit โ€” five non-obvious findings
Insight 01 ยท Portfolio Saturation
โ‚น3.4L Cr Flat for 3 Quarters โ€” Credit Card India Has Reached Addressable Market Saturation
Credit card current balance was โ‚น3.4L Cr in Mar-25, Dec-25, and Mar-26. Despite 1,102L active cards (growing), the outstanding balance is not growing. This is the classic saturation signal: new cards are being issued to better-quality revolvers who pay down faster. The revolve rate (the % of spenders who carry a balance) is declining as spend on cards grows. India's formal credit-eligible, card-issuable population has been substantially penetrated. Future card portfolio growth will come from existing cardholders spending more and revolving less โ€” not from new-to-card borrowers.
3 consecutive quarters at โ‚น3.4L Cr โ€” first plateau in this decade-long growth story
Insight 02 ยท PAR Discontinuity
The Jun-25 PAR 91-180 of 8.3% Is a Methodological Artefact โ€” Not a Real Deterioration
When analysts compare Jun-25's PAR 91-180 of 8.3% against Sep-24's 2.0%, they see an alarming 630 bps deterioration. This comparison is invalid. The Jun-series includes ARC-transferred accounts; the Sep/Mar-series excludes them. On a comparable (without-ARC) basis, PAR 91-180 went from 2.0% (Sep-24) to 1.4% (Mar-26) โ€” an improvement, not deterioration. This methodology gap has caused genuine mispricing of credit card risk in analyst models that naively use CRIF data without adjusting for ARC inclusion.
ARC-adjusted PAR 91-180: 2.0% โ†’ 1.4% โ€” improving, not deteriorating
Insight 03 ยท Spending vs Revolving Divergence
Card Spend Is Growing 15%+ But Current Balance Is Flat โ€” Revolve Rate Is Structurally Falling
Industry card spend data (from RBI payment system reports) shows credit card spends growing at 12โ€“15% annually through FY25โ€“FY26. Yet current balance outstanding is flat at โ‚น3.4L Cr. This means the same or more spending is generating less revolving balance โ€” the revolve rate is falling. This is structurally positive for credit quality (less balance at risk) but negative for card issuer revenue: interchange revenue grows with spending, but interest income (the high-margin component at 36โ€“42% APR) requires revolvers. Falling revolve rates compress net interest income per card even as transaction volumes grow.
Card spend +12-15% YoY but current balance flat โ†’ revolve rate compressing
Insight 04 ยท Competitive Moat
No New Entrant Has Cracked the Credit Card Business in India โ€” The Incumbent Moat Is Structural
Despite fintech disruption in personal loans, BNPL, and UPI payments, private bank market share in credit cards rose from 67.5% (Mar-22) to 70.7% (Sep-25). The reasons are structural: (1) credit card economics require 25โ€“30 million card-year track records for actuarially sound pricing; (2) co-brand programs (Amazon, Flipkart, Swiggy) require bank-grade balance sheets as the underlying issuer; (3) RBI's PPG (Pre-Paid Instruments) guidelines restrict NBFCs from issuing full credit cards. Any "fintech credit card" in India is actually a private bank card with a fintech front-end โ€” the bank takes the credit risk.
Pvt bank CC share: 67.5% (Mar-22) โ†’ 70.7% (Sep-25) โ€” moat widening, not narrowing
Insight 05 ยท PAR 180+ as Write-off Proxy
6.9% PAR 180+ = โ‚น23,500 Cr That Will Largely Be Written Off โ€” The Question Is When, Not Whether
Credit card recovery rates on PAR 180+ accounts are typically 10โ€“20% of outstanding (through debt collectors, legal action, settlements). At 6.9% PAR 180+ on โ‚น3.4L Cr, approximately โ‚น23,500 Cr is in deep delinquency. Assuming 15% recovery, the expected net credit loss from this cohort is ~โ‚น20,000 Cr. This amount is not yet in write-offs โ€” banks tend to carry NPA/SMA accounts for 12โ€“18 months before write-off. The FY26 and FY27 write-off acceleration is therefore mechanically predictable from current PAR 180+ readings. Investors in credit card-heavy banks should be modelling โ‚น18,000โ€“22,000 Cr in credit card write-offs over the next 6 quarters.
โ‚น23,500 Cr PAR 180+ โ†’ est. โ‚น20,000 Cr net credit loss over FY26-FY27