Delhi Police Cracks Down on Online Investment Scam Worth ₹33.83 Lakh, 4 Arrested

Post Views: 9

A Major Online Investment Scam Busted in Delhi, Four Suspects Held

A complex cybercrime racket operating under the guise of online investment schemes has been dismantled in the Indian capital, resulting in the arrest of four individuals accused of cheating a victim out of ₹33.83 lakh.

The operation involved an interstate network spanning Delhi, Punjab, and Rajasthan, targeting individuals through fake investment platforms promising unusually high returns.
The scheme came to light after a complainant reported being lured into investing ₹33,83,588 in an online trading platform.
Initially, the perpetrators established trust by showcasing fabricated profits, before pressuring the victim to transfer additional funds to “unlock” their previous investments.

According to experts, online investment scams often involve initial gains being showcased to build trust, followed by pressure to invest larger sums.

The four arrested suspects, identified as Mohammad Khalid, Atiur Rahman, Ramandeep Singh, and Tanish alias Heera Ram, had varying roles within the network.

Khalid provided his bank account and SIM card for a commission of ₹5,000.
Ramandeep Singh shared his bank details for ₹15,000.
Tanish served as a key intermediary, coordinating mule accounts and facilitating financial transactions.

Technical analysis was instrumental in cracking the case, involving the examination of over 100 Call Detail Records (CDRs), IMEI data, Customer Application Forms (CAF), and IP logs related to financial activities.

This digital evidence enabled investigators to connect the suspects and map the structure of the syndicate.

Experts Warn of Sophisticated Online Investment Scams

Online investment scams are becoming increasingly sophisticated, utilizing messaging platforms like WhatsApp and Telegram to manipulate victims.

Experts urge citizens to exercise caution when receiving unsolicited investment offers and to verify any investment opportunities thoroughly before committing resources.