Discover Aboitiz Data Innovation’s Mule Accounts Detection Solution: Delivering 86% Predictive Accuracy Rate to UnionBank
Aboitiz Data Innovation (ADI) has announced its latest artificial intelligence (AI)-powered solution, Mule Accounts Detection, in collaboration with the Union Bank of the Philippines (UnionBank). It is designed to help financial institutions strengthen their risk management strategies.
“This AI solution is a proactive risk hunting approach that enables the bank to detect and prevent money laundering activity and fraud through early identification of mule accounts. This detection model assesses a combination of customer information and behavior that predicts the likelihood of an account on being a mule,” said Christopher Go, UnionBank Senior Vice President – Enterprise Fraud Management Head.
Leveraging ADI and UnionBank’s collective expertise and exceptional talent, the companies worked together under a shared mission of countering financial crimes such as money laundering and fraud to protect its customers.
The Mules Account Detection solution uses a two-level approach. The first at onboarding, where the AI model identifies the probability of a falsely set up mule account, and the second when the account is flagged, to further assess account behavior and the likelihood of it being a mule. The AI-driven anomaly detection model continuously learns and improves, to generate scored alerts of mule activity. The solution encompasses workflow, alert and case management for ease of deployment and has configurable detection, with an 86% accuracy rate in predicting risk of mule accounts.
ADI is also proud to announce that its Mule Accounts Detection solution has also won at the Pitch! Regtech under the Fraud & Financial Crime category hosted by Regulation Asia. Having won the Pitch!, ADI will make its debut at this year’s Singapore FinTech Festival to present the solution to a larger audience.
“This marks an exciting time for us at ADI as this is important industry validation to an approach that has proven effective in improving detection rates whilst ensuring alert levels remain operationally practical,” said ADI Chief Operating Officer for Financial Services Guy Sheppard. “Our team, alongside those from UnionBank, have worked tirelessly to develop a solution that can transform the industry by tackling an extremely challenging niche and we are proud to be at the forefront of this transformation.”
As Southeast Asia continues on its path of rapid economic growth, the region is increasingly becoming a hub for financial crime, including money laundering, posing a significant threat to the stability of its financial institutions and systems. The Mule Accounts Detection solves a challenging and prevalent problem using advanced machine learning algorithms to detect and investigate mule accounts prior to when it is first reported.
