Archive · 25 Sep 2026
V-KYC Flags 10 Indian Districts as Emerging Mule-Account Hotspots
IDfy studied video identity checks used when people open financial accounts.
It found 10 districts where applications were rejected more often than expected.
Most of these districts are in Uttar Pradesh, while others are in Haryana and Rajasthan.
Lakhimpur Kheri had the highest rejection rate, followed by Bareilly and Varanasi.
Applications may be rejected because of impersonation, changed documents, prompting by another person, or suspicious behavior.
These patterns can give banks an early warning about possible mule-account networks.
A mule account can be used to receive or move illegal money.
Fraud risks can shift to nearby districts and old hotspots can become active again.
However, a high rejection rate does not prove that every person or account in a district is fraudulent.
IDfy identified 10 districts showing elevated V-KYC rejection rates and potential mule-account or fraud risks.
Eight flagged districts are in Uttar Pradesh, with one each in Haryana and Rajasthan.
Lakhimpur Kheri had the highest rejection rate at 14.03%, followed by Bareilly at 13.37% and Varanasi at 12.32%.
The analysis covered onboarding data from about 130 districts between April 2025 and June 2026, using statistical thresholds and Z-scores.
IDfy said about 85–90% of roughly 16 hotspots identified each quarter during FY26 were later corroborated, while risk spikes often lasted only one month.
- Who
- IDfy, a fraud-prevention firm, analyzed V-KYC onboarding data relevant to banks and other financial institutions.
- What
- The analysis identified 10 districts with elevated V-KYC rejection rates and possible emerging or established mule-account and fraud clusters.
- When
- The underlying data covered April 2025 through June 2026; IDfy said signals appeared up to two months before some public reporting.
- Where
- The flagged districts were in Uttar Pradesh, Haryana and Rajasthan; the analysis also described shifts involving neighboring districts, Nuh, and parts of Gujarat.
- Why
- The findings are intended to help financial institutions detect emerging fraud clusters earlier by combining V-KYC signals with transaction monitoring and other checks.
Early-Warning Benefits
Caution and Verification
Using V-KYC rejection patterns
Early-Warning Benefits
Banks can combine elevated rejection rates with transaction monitoring to identify and investigate emerging mule-account clusters sooner.
Caution and Verification
A high rejection rate is only a risk indicator and does not establish that every applicant or account in a district is fraudulent.
Predictive performance
Early-Warning Benefits
IDfy said 85–90% of the hotspots it identified each quarter were later corroborated, with signals appearing up to two months before public reporting in verified cases.
Caution and Verification
The reported corroboration still requires independent verification, and IDfy acknowledged that its earlier warning was not universal across all regions.
Monitoring geographic shifts
Early-Warning Benefits
Tracking neighboring districts could help financial institutions respond when fraud risk moves away from an existing hotspot.
Caution and Verification
A shift in the location of risk shows where suspicious activity emerges, but does not prove that the same fraud operators physically moved.
- Flagged districts
- Lakhimpur Kheri, Bareilly, Varanasi, Saharanpur, Muzaffarnagar, Panipat, Firozabad, Jodhpur, Lucknow and Ghaziabad.
- State distribution
- Eight districts were in Uttar Pradesh, one in Haryana and one in Rajasthan.
- Highest rejection rate
- Lakhimpur Kheri recorded a 14.03% V-KYC rejection rate.
- Other leading rates
- Bareilly recorded 13.37%, Varanasi 12.32% and Saharanpur 10.32%.
- Data coverage
- The study examined V-KYC onboarding data from approximately 130 districts between April 2025 and June 2026.
- Hotspot persistence
- Risk spikes lasted one month in 81% of cases, while 6.5% continued for three months or longer.
- Early-warning results
- IDfy identified about 16 hotspots per quarter during FY26 and said 85–90% were later corroborated by law-enforcement action or news reports.
- Methodology
- Districts had to meet minimum fraud-volume and statistical-validity thresholds, including at least 30 rejected calls in a month, before Z-score ranking.
