Tackling AML Compliance & Positives

Platforms

Web, Mobile App

Turning Compliance from a Cost Center into a Competitive Advantage

Challenge

A mid-sized bank in Southeast Asia was under constant pressure from regulators to comply with strict Anti-Money Laundering (AML) rules. Every transaction above a certain threshold was being flagged by their legacy system. On paper, this looked like the bank was being thorough. In reality, 99% of the alerts were false positives.

The compliance team was drowning in meaningless alerts. Each flagged case had to be reviewed manually within seven days, or the bank faced heavy daily penalties. This meant skilled staff were spending their time sifting through noise, while real threats risked being overlooked.

Solution

The bank needed a smarter way to separate genuine risks from routine transactions. Instead of replacing their entire AML system, we proposed layering intelligence on top of it. By combining rule-based checks with anomaly detection models, the system could learn what “normal” looked like for different types of customers - such as high-value corporate clients with frequent large transfers versus individual account holders.

How Innovify Helped

Developed an AI anomaly detection framework using Python, TensorFlow, and scikit-learn.
Automated repetitive tasks with UiPath RPA bots.
Built Power BI dashboards with strict access controls.
Delivered solution in less than 5 months, without disrupting existing AML processes.