Union Bank of the Philippines (UnionBank) recently conducted a study to test a new method that uses
artificial intelligence (AI) and graph analytics to detect fraudulent transactions more efficiently,
leveraging the Bank’s capabilities to better safeguard its customers.
Developed by UnionBank’s Artificial Intelligence and Innovation Center of Excellence team, the new
method provided nuanced insights into fraud which can potentially improve systems to effectively
mitigate financial risks and enhance decision-making processes, making them more accurate, faster, and
efficient.
UnionBank used graph analytics to scrutinize the intricate relationships between transactions. For
instance, fraudsters often involve intermediary accounts to secretly facilitate money laundering across a
network. By expanding their analysis to three degrees of connection instead of just the first degree, the
Bank was able to gain a more comprehensive understanding of the risks associated with different
fraudulent activities.
“Examining the influence of an account within a network is one pattern we seek to identify. The
technique we employed to assess this is by measuring its centrality,” said UnionBank Data Scientist,
Abigail Antenor.
This approach allowed the Bank to quantify the number of connections associated with each account,
identify those acting as middlemen, and evaluate their proximity to other accounts to determine the
speed of fund transfers. Subsequently, they studied how these measures correlate with fraud in
different degrees of connection previously mentioned, to determine which indicator is most relevant in
those scenarios.
Tailoring fraud indicators to each degree proved effective, as results showed that 19% more fraudulent
transactions were detected by applying fraud indicators to include second and third degrees, with 80%
saved for the turnaround time.
This breakthrough is timely, as fraudsters are continuously becoming more innovative in executing
attacks, especially those directed at banking systems and their customers.
“With this, we have further proven that AI can significantly augment our ability to spot patterns in
transaction flows, detect malicious activities, and prioritize suspicious accounts for further
investigation,” said Dr. Adrienne Heinreich, UnionBank Head of AI Center of Excellence, Data and AI
Group.