Following this announcement, the solution has been implemented in the Philippines’ Real-Time Payment network, aiming to provide holistic intelligence that will enable businesses to trace financial crime across the payment network.
In addition, the company will continue to focus on meeting the needs, preferences, and demands of clients and users in an ever-evolving market, while prioritising the process of remaining compliant with the regulatory requirements and laws of the local industries as well.
TRACE was developed as a solution for RTP systems in order to proactively identify money mules and trace the dispersion of funds. TRACE is network-agnostic and can be quickly and effectively implemented within the payment networks across the region, aiming to enhance the manner in which companies and institutions protect customers from fraud and scams, as well as supporting regulatory obligations.
Financial institutions have recently largely relied on semi-manual methods or in-house AI solutions in order to detect illicit patterns, but these typically rely on their own data and lack the holistic, network-level perspective needed to trace far-reaching criminal activity. In order to address these challenges, Mastercard developed TRACE, a solution that leverages data science techniques to trace potentially fraudulent transaction patterns across a payments network, as well as provide alerts to banks about suspicious accounts. At the same time, TRACE incorporates critical data points across an entire domestic network in order to identify money mules involved in financial crime.
In addition, the solution was developed to allow participating financial institutions to quickly and extensively trace dispersed illicit funds across the RTP system, identify money mule activity throughout the network, as well as proactively highlight suspected money laundering accounts. These processes are expected to allow them to better adhere to the country’s new Anti-Financial Account Scamming Act (AFASA) and further develop in the landscape.
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