A 74-year-old Bengaluru teacher was coerced into transferring ₹24 crore in a “digital arrest” scam. Bank staff flagged suspicious transactions; six arrests followed. Investigators traced funds through 23 mule accounts across states and recovered part of the money.

Six Arrested After Elderly Victim Loses ₹24 Crore in Psychological Cyber Fraud

The420.in Staff
4 Min Read

In a shocking case of cyber fraud, a 74-year-old retired teacher was allegedly held under a so-called “digital arrest” for nearly four months and cheated out of ₹24 crore. The case came to light after a private bank manager noticed suspicious transactions and alerted authorities in time, preventing further financial loss.

According to officials, the accused impersonated senior officers of the Central Bureau of Investigation (CBI) and the Enforcement Directorate (ED), falsely claiming that the victim was involved in a money laundering case and was under constant surveillance. Under intense psychological pressure, the elderly woman was coerced into complying with their instructions.

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How the Scam Worked

Investigators found that between February 10 and March 24, the victim transferred ₹24 crore in 26 separate transactions. The money was routed through 23 mule bank accounts spread across nearly 10 banks across different states, indicating a well-organised inter-state network.

The fraudsters allegedly continued demanding more money and even pressured the victim to pledge around 1.3 kilograms of gold jewellery kept at her home. The unusual banking activity and behavioural changes eventually raised suspicion with the bank manager, who promptly informed law enforcement agencies.

Bank Alert and Arrests

Following the alert, police launched an investigation and uncovered a structured cybercrime syndicate operating across multiple states. Based on technical analysis and money trail tracking, six accused have been arrested.

Police said the gang operated in a highly coordinated manner, first collecting detailed information about the victim’s financial background and recent land sale, and then using it to build targeted psychological pressure.

Authorities have frozen several mule accounts and successfully blocked around ₹4 crore, while ₹1.46 crore has been recovered so far. The remaining funds are believed to have been layered through multiple transactions to obscure their trail.

Expert View and Precautions

Cyber experts describe “digital arrest” as a rapidly evolving fraud model in which criminals impersonate government agencies and keep victims under continuous fear through video calls, messages, and fabricated legal threats, forcing them into compliance.

Commenting on the case, renowned cybercrime expert and former IPS officer Professor Triveni Singh said such scams rely heavily on “authority impersonation” and “emotional engineering.” He noted that fraudsters do not rely on technical hacking but instead exploit fear, trust, and psychological manipulation to control victims for extended periods.

Officials added that one of the biggest challenges in such cases is that victims are unable to distinguish between real and fake law enforcement communications due to the use of official-sounding language and staged legal scenarios.

Police are now analysing mobile data, call detail records, and banking transactions to map the wider network and identify additional suspects involved in routing and laundering the funds.

Preliminary findings suggest the syndicate may have interstate links and could involve several more individuals. Authorities have indicated that further arrests are likely once digital forensic analysis is completed.

Officials have urged citizens to remain cautious and avoid responding to any unknown calls, video calls, or messages claiming to be from government agencies. They have advised verifying all financial or legal claims through official channels before taking any action.

The case once again highlights how cybercriminals are increasingly relying more on psychological manipulation than technical intrusion, making such frauds harder to detect and prevent.

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