Mumbai (Maharashtra) [India], April 17: Bureau, a pioneering fraud and identity decisioning platform, has introduced ‘Money Mule Score,’ a cutting-edge solution that empowers financial institutions, NBFCs, and fintech companies to proactively detect 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 extensive domain expertise across email, phone, social media, and device intelligence which analyses users’ legitimacy through device fingerprints, behavioral patterns, and historical data, and 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 – “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 Money mule score is a significant step towards eliminating cyber fraud, and enabling safe and secure financial access.”
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.
With this success, Bureau has officially launched the solution for companies across the spectrum of digital banking, to detect and block potential money mules before they can cause damage. Financial services providers are encouraged to contact Bureau for a demo to learn how Money Mule Score can bolster their fraud prevention strategies.
To schedule a demo of Money Mule Score and learn more about Bureau’s industry-leading fraud prevention capabilities, please visit www.bureau.id.
Bureau is a modern no-code decisioning platform. It delivers absolute conclusions about digital identity trustworthiness to prevent fraud, ease compliance, and make it easy for consumers to transact online. The single AI-architected platform provides banks, fintech, gaming, gig economy and e-commerce companies with a complete range of risk, compliance, fraud prevention and detection, and onboarding solutions. Its Identity Bureau network supplies customers with insights derived from an identity graph and feedback loop about digital identities based on contextualised linkages. Backed by tier-one investors like GMO Venture Partners, Okta Ventures, Commerce Ventures, Quona Capital, Blume Ventures, EMVC, and Village Global, Bureau is headquartered in San Francisco, CA, with offices in India and Singapore.
(ADVERTORIAL DISCLAIMER: The above press release has been provided by NewsVoir. will not be responsible in any way for the content of the same)
