The Delhi Police have arrested a 24-year-old man from Punjab for allegedly being part of a cyber fraud syndicate that secured fraudulent loans worth nearly Rs 1.6 crore by misusing the Aadhaar and PAN details of around 50 persons, officials said on Saturday.

The accused, identified as Ajay Kumar, was arrested on Friday. Police seized a mobile phone allegedly used to facilitate the fraud.

The investigation began after a Delhi resident filed a complaint on June 25, stating that he had received repeated calls from a loan recovery agent demanding the repayment of the EMIs for a personal loan of Rs 4.5 lakh that he had never applied for.

A subsequent inquiry revealed that a loan had been fraudulently obtained in the complainant’s name from a private finance company using his PAN details. Investigators also found that the mobile number linked to his Aadhaar had been changed without his knowledge, enabling the accused to complete the loan application process.

During the investigation, the police traced the loan proceeds to a bank account allegedly operated by Kumar. “Technical surveillance and human intelligence led to his arrest. Analysis of his mobile phone revealed exchanges of the complainant’s personal details with his associates before the loan was fraudulently obtained,” a senior police officer said.

According to the police, Kumar disclosed during interrogation that he was part of a larger network that diverted fraudulently obtained loan amounts into bank accounts of individuals who allowed their accounts to be used in exchange for a commission. The syndicate allegedly changed victims’ Aadhaar-linked mobile numbers before using their Aadhaar and PAN credentials to secure loans from private non-banking financial companies (NBFCs).

Investigators have so far identified nearly 50 victims whose identity documents were allegedly misused to obtain loans amounting to about Rs 1.6 crore from private NBFCs.

Cops said efforts are underway to identify other members of the syndicate, trace additional mule accounts and determine the full scale of the fraud.