Principal Investigator: Dr. Shruti Mantri

Co-Investigator: Professor Manish Gangwar, Executive Director, IIDS

Team: Pranay Pandhre, Intern

Project Start Date: June 2023

Status: Ongoing

Project Sponsor: Telangana State Police Centre of Excellence for Cyber Safety


Mule accounts are critical links in the fraud supply chain infrastructure as they are vital in transferring cash from the victim's account and in the money laundering process. Recently, there has been a surge in the money mule accounts. Cybercriminals employ different methods to launder funds, including using stolen or synthetic identities to open fraudulent accounts, recruiting individuals to serve as money mules, and taking over genuine accounts without the victim's knowledge. Five mule personas make the mule account detection complex:

  • The victim of credential theft,

  • The deceiver opens an account to perpetrate the fraud,

  • The Peddler sells a genuine account to a cybercriminal,

  • The Chump executes the transaction believing the money is clean,

  • The accomplice willing participated chasing 'easy money' opportunity.

To ensure comprehensive protection against all types of mule scenarios, it is necessary to analyze a user's physical and cognitive behavior throughout the account opening process and beyond using machine learning models.

In the current study, the researcher has analyzed the account opening process for saving and current accounts for Indian banks as per the RBI guidelines; identify whether the account opening pattern determines behavior displayed belongs to a genuine user or cybercriminal by identifying patterns of knowledge with data, familiarity with the process, and other patterns resulting in lower false rejections and enhanced detection.

The results from the study will be used to improve the account opening procedures and curtail mule accounts.