Some common ways criminals may recruit unsuspecting mules is by way of seemingly genuine job advertisements, lottery win messages, or overseas vacations and jobs.
Over the last decade, the accessibility of banking and financial services has grown by leaps and bounds. However, there has also been a growing incidence of financial frauds. One such scam that has been on the rise is the money mule scam.
A money mule is essentially a person who is used as a conduit to transfer money illegally. Criminals target victims to get their money transferred using the latter’s bank accounts. While many of the victims (or “money mules”) may be unaware of their role in the scam, some of them may be voluntarily complicit as they receive a part of the money transferred.
Some common ways criminals may recruit unsuspecting mules is by way of seemingly genuine job advertisements, lottery win messages, or overseas vacations and jobs. Regardless of the means, the purpose of the scam is always to exfiltrate stolen money to criminal benefactors through the mule’s account.
The recently unearthed robocall scam perpetrated by an Indian call centre defrauded seniors in the US of $8 million. This is an example of how unsuspecting elderly victims were used as mules.
In India, since the Jan Dhan Yojana was announced, many of the zero balance savings accounts have also been made easy targets by cybercriminals, many of whom were used mules to convert illegitimate money to white money, and vice versa.
Key Pain Points for Banks
The biggest challenge for banks to avert the money mule scam is its very nature. In most cases, these transactions go under the radar as they appear to be normal transactions occurring in unsuspected accounts. Further, small transactions are not even a red flag from the income tax perspective, and are, therefore, not traced. Moreover, it is very difficult to identify these frauds as banks cannot easily ascertain if someone is acting on the criminal.
Considering these factors, money mule transactions have a high probability of slipping under the general risk controls in place currently. Nevertheless, these transactions pose a high compliance risk for banking and financial institutions.
How Artificial Intelligence can help prevent the Money Mule Scam
While banks and financial institutions have a risk grading system for each account, wherein the probability of accounts being used for illicit activities is assessed, a mule can even be a low-risk account holder with verified KYC and genuine records.
Companies such as Karza Technologies work with industry stakeholders to devise solutions that automate the early detection of such accounts. Such AI-based solutions focus on alternate data points and characteristics such as the typical money mule profile, monetary thresholds for various profiles, etc.
The solutions employ algorithms that help identify patterns and flag any anomalous transactions as well as factor in typical cases where the probability of an account being used as a mule is high. For example, the income levels, the permanent and temporary address of the account holder and their proximity to the branch, and frequency and size of the transaction can be used as data points to trace any abnormal activity for a said account. Such solutions use unique algorithms to create a model that gauges the probability of an account being a mule.
by, Omkar Shirhatti, Co-founder and CEO, Karza Technologies