Six suspects have been arrested in Maharashtra after police uncovered an alleged mule-account network involving Rs. 57.25 crore in fraudulent transactions, highlighting the infrastructure increasingly used to move proceeds from cybercrime.
Acting on a tip-off, Crime Branch Unit 4 raided a location in Mohol, Solapur district. Police seized three laptops, 29 mobile phones, 23 SIM cards, 155 ATM cards, 105 bank passbooks and chequebooks, and Rs. 74,350 in cash, indicating an operation managing numerous banking identities and accounts.
Key Highlights
● Rs. 57.25 crore in suspected fraudulent transactions.
● Six suspects arrested in the crackdown.
● 155 ATM cards and 105 passbooks/chequebooks seized.
● Accounts linked to 96 cybercrime complaints across multiple states.
● Continuous behavioral and transaction monitoring can help banks identify mule accounts earlier.
Investigators allege that the suspects opened or arranged bank accounts that were subsequently supplied to cybercriminals. These “mule accounts” allowed fraud proceeds to be received, temporarily held and transferred, making it harder for investigators to trace money back to the perpetrators.
The scale extended well beyond Maharashtra. Police reportedly linked the accounts to 96 cybercrime complaints on the National Cyber Crime Reporting Portal, with cases largely originating from Delhi, Punjab, Odisha and Maharashtra. Victims were primarily targeted through illegal online betting and gaming platforms.
The case exposes a larger weakness in India's fight against financial cybercrime. Mule accounts have become a critical enabling layer for scams ranging from digital arrests and investment fraud to gaming and betting schemes. Disrupting these networks can therefore potentially interrupt multiple fraud operations simultaneously.
For banks, the lesson is to move beyond onboarding KYC toward continuous account-risk monitoring. Unusual transaction velocity, rapid movement of funds, multiple accounts linked to common devices or identities, abnormal ATM activity and transactions inconsistent with customer profiles can provide early warning signals before stolen money disappears.
