Bureau introduces ‘Money Mule Score’ to tackle rising identity theft in the BFSI segment

Bureau, a fraud and identity decisioning platform, has introduced ‘Money Mule Score‘ to empower financial institutions, NBFCs, and fintech companies in detecting potential money mules during user onboarding. The solution provides a holistic risk assessment, which goes beyond traditional KYC processes to detect and prevent mule accounts, thereby protecting businesses and their customers.

Money mule fraud has become a critical threat to global financial security. As per NASDAQ’s Global Financial Crime Report 2024, among anti-financial crime professionals surveyed, 47% listed money mule activity as a major concern, placing it second only to real-time payments fraud. The traditional KYC-AML processes prove ineffective, as they are static in nature, creating gaps that sophisticated criminals can exploit.

Money Mule Score is built on Bureau’s proprietary Link Analysis that utilises advanced machine learning and analytics to assess user’s risk indicators, beyond the traditional KYC process. It incorporates Bureau’s domain expertise across email, phone, social media, and device intelligence which analyses users’ legitimacy through device fingerprints, behavioral patterns and historical data, flagging potential high-risk users right at the onboarding stage. The solution integrates seamlessly into companies’ existing onboarding processes, ensuring a smooth experience for legitimate users.

Ranjan R Reddy, Founder & CEO, Bureau said in a statement,“Fraud and online financial crime is a growing menace in India, which puts trust between digital platforms, their customers, and regulators in jeopardy. Money mule accounts and activity is the fastest growing fraud trend, and Bureau is uniquely placed to help with our proprietary technology, data, and insights. Our money mule score identifies potential mule accounts in real-time at onboarding, as well as detect existing accounts and activity that are suspicious. We have seen great success in deploying industry specific machine learning models, and link analysis that have led to detecting over 500k mule accounts, protecting over $100m of financial activity.”

Bureau’s partnership with a leading Indian bank for the deployment of Money Mule Score led to a 60% uplift in money mule detection as compared to the bank’s existing KYC process. These early mule detections enabled the bank to prevent the potential fraud losses of over $43 million within the first six months of using the solution.


This website uses cookies. By continuing to use this site, you accept our use of cookies.