India’s Fraud Curve Is Rising Quietly – What the Data Really Says About Digital Payments and Risk
India’s Fraud Curve Is Rising Quietly – What the Data Really Says About Digital Payments and Risk
Digital payment systems in India weren’t introduced in a grandiose way; instead, they became an integral part of everyday life quietly, but very quickly. Now when you buy vegetables from a farmer, he scans your QR code. As you turn around to leave, your pension is deposited into your bank account! And when a college student goes out with friends and the bill comes, he simply transfers his share within seconds. Digital payment systems are no longer just a novelty; they have become a part of everyone’s daily routine. As a result, most people who use these technologies do not think about the infrastructure that supports them anymore.
Digital payments in India represent virtually all non-cash payment activity in the country, with digital payment modes representing nearly all transaction volume and representing most of the payment value (RBI Payment Systems Indicators, 2025).
Data from the Payment Systems Data (2025) as published by the Reserve Bank of India show that Digital Payments represented approximately 97.5% of total payment value and approximately 99.80% of transaction volume by early 2025. This information indicates the growing use of digital payment platforms throughout the country. In fact, the number of Digital Payment Transactions continues to be counted in the tens of Billions with a significant decrease in the number of paper-based instruments each year.
While much of this transformation is regarded as a “success story” (and for good reason), it is not without its “dark” side – a “continuum” of risks related to fraud that has “scaled” with the growth of digital payment systems, albeit at a more “sustained” rather than “explosive” rate.
The illusion of safety in percentages
One may initially feel comforted by the RBI’s reported amounts for fraud. The level of fraud, as defined by the ratio of fraud value to total value paid, has remained consistently low . In September 2022, that ratio was 0.127 basis points, and it increased to 0.146 basis points in October 2025. There have been even some months when the ratio has been lower.
On the face of it, based on just this analysis, a conclusion may be that the digital payments ecosystem is growing at a rate faster than that of fraud. However, this conclusion is based completely on the ratio, and not on absolute numbers. Monthly digital fraud payment values in the dataset increase from approximately ₹250 crore in late 2022 to over ₹400 crore by late 2025. When you have a constant ratio of fraud to total payment based on a much larger volume, it produces quite a different set of problems.
In fact, a small percentage of the much larger amount of money being sent (or received) through digital payment systems during a period of fraud would create a larger problem than a small percentage of the smaller number of payments being sent through digital payment systems.
What the fraud data reveals over time
According to the Reserve Bank of India (RBI), the statistics for domestic digital payment fraud indicate that fraud within the payment systems has increased steadily over time. Monthly fraud amounts were in the range of about 40,000 to 125,000 cases, and the value of fraud associated with those transactions was ₹200 – ₹300 crore each month, during late 2022. Although there was a certain degree of fluctuation in the overall monthly totals, both the monthly number of fraud cases per category, along with their corresponding value, remained consistently higher than average.
Beginning in mid-2023, the upper end of that monthly range continued to move up over the next year. By late 2023, the overall monthly number of fraud cases surpassed the previous peak , with a few months reporting fraud-related transaction values exceeding ₹400 crore. This trend continued through 2024 and into early 2025. For instance, on several occasions, the transaction value for fraud activity was above ₹400 crore, with exceeding fraud volumes.
The data also indicates that there have not been sudden spikes in the amount of fraud that would indicate a point of break down or crisis within the payment system. There have not been any dramatic spikes or outliers that would indicate an imminent risk to the payment system due to the increased level of fraud activity. Rather, this also highlights that there is an issue with the underlying structure of the system since fraud activity is growing parallel to the dramatic increase in the amount of digital payments being made across all channels. In this context, stable ratios of fraud, when applied to increasing transaction volumes, create the likelihood of steadily increasing total fraud exposure. This reinforces the need for continuous risk management versus a more episodic approach.
Where payment system data changes the interpretation
The wider payment system indicators have an important role to play, and this is why they are especially useful today. RBI’s Payment System Data Shows that retail digital instruments (i.e., UPI, card payments, mobile based transfers, prepaid instruments) represent almost all of the recent growth in the payment system in terms of total transaction volume. Each of these payment channels has been characterised by:
- A very large user base.
- A high level of transaction volume (i.e., the number of transactions);
- A relatively small average ticket size (i.e., the amount of money received for each transaction);
On the other hand, settlement systems (RTGS/CCIL) represent a very small number of transactions (i.e. ) but with a comparatively high dollar value. As a result, the risk profile of the system is changing. The movement and distribution of money through the system are now shifting from large financial institutions to millions of people and small businesses. As a result, fraudsters are finding it easier to perpetrate their scams; the systems they’re attempting to defraud may not be faulty or compromised, but the way people behave around those systems creates an opportunity for fraud.
Social engineering, impersonation scams, and indicative fraud are all potential targets for high-frequency, low-value transaction activity. The technologies required to commit these types of fraudulent acts do not have to be complex; they simply must have an established trust relationship, a time-sensitive urgency to act, and a level of familiarity between victim and perpetrator.
Linking growth and fraud: can we model it?
This leads us into the core analytical question, namely, whether or not data on payment growth and fraud can be synthesised into a predictive or econometric framework.
In principle, the answer is affirmative, but with caveats.Fraud exposure could theoretically be modelled as a function of:
- The total value of digital payments
- The number of retail transactions
- The make-up of the different payment methods being used (the percentage of transactions being paid for via each channel)
there is no direct estimation of the relationship with econometric methods. It instead operationalized the framework using scenario-based simulations. The simulations allow for the payment growth paths and possible values of fraud intensity to be incorporated to illustrate the potential range of exposure outcomes.
Assumptions for scenario analysis
- Baseline period: FY2024–25
- Fraud intensity metric:
- FTS (Fraud / Payment Value × 10,000)
- Baseline fraud intensity:
- ~0.15 bps (based on recent RBI data)
- Institutional response assumed constant
- No major regulatory shock or authentication redesign
Illustrative Scenario Simulations
| Scenario | Annual Growth in Digital Payment Value | Assumed Fraud Intensity (bps) | Projected Annual Payment Value (₹trillion) | Projected Annual Fraud Value (₹crore) |
| Baseline | 10% | 0.15 | 3,500 | 5,250 |
| High Growth with Managed Risk | 20% | 0.16 | 3,850 | 6,160 |
| High Growth with Risk Stretch | 20% | 0.18 | 3,850 | 6,930 |
| UPI-Dominant Expansion | 25% | 0.19 | 4,000 | 7,600 |
Finally, the relationship between the growth in payments and the incidence of fraud likely will not be a simple linear one. During the adoption phase of a new payment platform, new users entering the market increase risk disproportionately, whereas during the maturity phase, that risk stabilises or shifts into new forms of risk.
How will the addition of new customers (marginal) growth, affect the amount of (marginal) Risk?
Payment System data allows us to see how fast Retail Digital Transaction usage is growing. fraud data allows us to see how fraud exposure increases as that growth occurs. Together, these two types of data sets can be used to determine certain thresholds (points at which the addition of more retail digital transactions may lead to an exponential increase in fraud Risk).
Using this framework will not generate exact predictions of fraud numbers, but it does mean something arguably more important: that at certain points, the growth of Retail Digital Transactions goes from being a relatively safe to relatively risky period of growth.
For Banks, Payment Platforms, and Regulators, this important distinction is far more valuable than an overall Fraud Ratio.
The conclusive analysis of the data
Based on the statistical information gathered by the RBI, including the indicators of the payment systems and fraud statistics, the Indian digital payments environment is safe and secure. On the contrary, it is growing exponentially and is still a stable platform.
However, from the gathered statistics, we can also infer that Fraud Risk, which has previously been treated as a Margin Risk, has now fully integrated into the digital payments scale. Fraud Risk is now an integral part of the overall scalability of retail digital payments; while the overall number of Retail Digital Payments is continually increasing, there will always be a direct increase in the exposure to Fraud Risk.
The fundamental fraud risk is not an immediate crisis, it is complacency which has built up with a very small risk ratio, while at absolute exposure the risk continues to grow into a heavily populated region.
The success of India’s Digital Payments story is well documented and celebrated. The next chapter of India’s Digital Payments journey will be how it is able to effectively identify, establish a baseline, and manage that risk as it grows and becomes more successful.
Finally, when your success grows, even the smallest vulnerability can quietly become the largest.
Sources
- Reserve Bank of India, Payment System Indicators – Domestic Payment Frauds (Monthly)
Methodology (Summary)
- Data source: RBI Payment System Indicators
- Period: Sep 2022 – Sep 2025
- Fraud metric: FTS (Fraud value / total payment value × 10,000)
- Chart note: Illustrative risk index, not RBI projection
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