Indian fintech companies are facing rising technology expenses as the growing use of artificial intelligence increases demand for computing power, cloud infrastructure and data-centre capacity. Paytm, Groww and PB Fintech have all reported significant increases in technology-related costs in the September 2026 quarter.
Paytm’s software, cloud and data-centre expenses climbed 59% year over year to ₹211 crore, while Groww’s cost to serve increased 66% to ₹206 crore and PB Fintech’s internet expenses rose 65% to ₹71 crore. The trend highlights a new challenge for fintech companies: AI can improve productivity and automate operations, but running these systems is becoming more expensive. Importantly, the increases are not entirely attributable to AI, as higher transaction volumes, platform consolidation and other infrastructure expenses are also contributing.
Key Takeaways
- Paytm’s software, cloud and data-centre expenses rose 59% to ₹211 crore in Q2 FY27.
- Groww’s cost to serve increased 66% to ₹206 crore.
- Groww separately reported ₹13 crore in AI costs for the quarter.
- PB Fintech’s internet expenses increased 65% to ₹71 crore.
- PhonePe expects computing, storage and memory costs to remain under pressure.
- Upstox reported data-processing costs 25–30% higher year over year.
- Long-term cloud contracts are temporarily protecting some companies from immediate price increases.
- Fintechs are extending hardware lifecycles and optimising workloads to manage expenses.
Paytm’s Technology Expenses Rise 59% to ₹211 Crore
Paytm reported a substantial increase in software, cloud and data-centre expenses during the September quarter.
The company’s spending increased to ₹211 crore in Q2 FY27, compared with ₹133 crore in the corresponding quarter of the previous financial year.
This represents a year-over-year increase of approximately 59%.
Paytm attributed the higher expenses to increased AI usage and the consolidation of its technology platforms.
The platform consolidation is an important part of the explanation. Paytm had been operating separate online and offline payment technology stacks and began combining them to improve transaction-processing capacity and operational efficiency.
The company also acknowledged that greater AI usage contributed to the increase.
Paytm said quarterly expenses could fluctuate depending on how its cloud contracts are structured.
The distinction matters because the entire ₹211 crore should not be treated as spending on artificial intelligence. It includes broader software, cloud and data-centre expenses.
Groww and PB Fintech Also Report Higher Costs
The increase in technology spending is not limited to Paytm.
Groww reported a 66% increase in its cost to serve, which includes internet and data-centre expenses.
Its cost to serve reached ₹206 crore in Q2 FY27, compared with ₹124 crore in the year-ago quarter.
Groww identified several reasons for the increase:
- Higher technology and computing expenses.
- More trading days during the quarter.
- One-time reimbursements to customers following abnormal trades.
- Inflation in computing costs associated with AI.
The company separately disclosed that its AI expenses amounted to ₹13 crore during the quarter.
Groww expects some inflation-driven technology costs to remain part of its regular operating expense base.
PB Fintech, the parent company of Policybazaar and Paisabazaar, also experienced higher infrastructure expenses.
Its internet costs increased 65% to ₹71 crore from ₹43 crore a year earlier.
These figures indicate that rising technology expenses are affecting multiple fintech business models, including digital payments, stockbroking, insurance distribution and financial services.
Technology Expense Comparison Across Indian Fintechs
| Company | Expense category | Q2 FY27 | Year-ago quarter | Increase |
|---|---|---|---|---|
| Paytm | Software, cloud and data centres | ₹211 crore | ₹133 crore | 59% |
| Groww | Cost to serve | ₹206 crore | ₹124 crore | 66% |
| PB Fintech | Internet expenses | ₹71 crore | ₹43 crore | 65% |
Note: These are different expense categories and should not be directly compared as identical measures of AI spending.
Why Is AI Making Fintech Infrastructure More Expensive?
AI systems require substantial computing resources.
Fintech companies are increasingly using AI for customer support, fraud detection, risk assessment, merchant services, sales operations and internal software development.
These applications can require large amounts of computing power, particularly when companies process millions of transactions and customer interactions.
AI models also consume tokens when processing information and generating responses. The cost can increase as businesses deploy more sophisticated models and expand the number of automated workflows.
However, the pressure extends beyond AI software itself.
Rahul Chari, co-founder and CPTO of PhonePe, told Moneycontrol that computing, storage and memory costs are increasing because of the capacity being built for GPU infrastructure and AI training.
He expects the cost pressure to continue over the next six to twelve months.
This reflects a broader infrastructure challenge: global demand for AI computing is influencing the availability and cost of hardware, memory and storage used by other technology businesses.
Upstox Reports 25–30% Higher Data Processing Costs
The rising cost of infrastructure is also affecting stockbroking platforms.
Shrini Viswanath, co-founder of Upstox, said the company’s overall data-processing costs were running 25–30% higher year over year.
The company is responding through several measures:
- Extending hardware lifecycles.
- Optimising workloads to avoid unnecessary computing.
- Using tiered storage systems.
- Securing infrastructure capacity earlier.
These measures are particularly relevant for regulated financial companies.
Such businesses must maintain data-retention systems, backup infrastructure and disaster-recovery capabilities. This limits their ability to reduce technology spending simply by cutting storage or processing capacity.
Long-Term Cloud Contracts Offer Temporary Protection
Some fintech companies have avoided immediate increases in infrastructure bills through long-term agreements with cloud providers.
Contracts with companies such as Google Cloud and Amazon Web Services can provide a degree of cost predictability.
However, this protection may not last indefinitely.
When contracts expire and companies negotiate new arrangements, higher infrastructure prices could affect their operating expenses.
A large brokerage firm cited in Moneycontrol’s reporting expects contract renewals, potentially around two years away, to create additional cost pressure.
Hardware purchases also affect companies gradually. Higher prices are generally reflected when businesses expand computing capacity or replace existing equipment.
This means the full impact of rising hardware and infrastructure costs may take time to appear in financial results.
Zerodha Focuses on Lean Engineering to Control Costs
Not every fintech company is experiencing the same cost trajectory.
Zerodha CTO Kailash Nadh said the company has managed to reduce overall hardware and infrastructure costs as it has scaled.
He attributed this to a focus on lean engineering and efficient technology systems.
Nadh also warned that companies with poorly optimised software infrastructure could face additional expenses when introducing AI.
If businesses deploy AI without improving their underlying systems, they may end up increasing hardware requirements and creating more complicated technology stacks.
Zerodha’s experience suggests that engineering efficiency can be an important factor in controlling infrastructure expenses, even as AI adoption expands.
The Bigger Picture
The rising expenses highlight a developing challenge for India’s fintech industry.
AI is becoming an important tool for improving customer service, automating operations, identifying financial risks and helping businesses make better decisions. However, these capabilities require computing infrastructure that is becoming more expensive.
The financial benefits will depend on whether productivity gains and additional revenue eventually exceed the cost of running AI systems.
For fintech companies, the next phase will involve balancing AI adoption with infrastructure efficiency. Simply deploying more AI tools will not guarantee better profitability.
Looking Ahead
Over the next six to twelve months, fintech companies will be watching cloud pricing, hardware availability, memory costs and AI-related computing expenses. The renewal of long-term infrastructure contracts could also become an important factor in determining how much additional spending reaches company financial statements.
The bigger test will be whether AI investments generate measurable improvements in operating efficiency, customer retention and revenue. Companies that combine useful AI applications with efficient engineering may be better positioned to manage rising infrastructure costs while expanding their services.
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