AML Artificial Intelligence Software
Machine Learning Scenarios Enhance
our AML AI Solutions
BAM+ AML AI Software
BSA/AML professionals are forced to wear a lot of hats to ensure their programs are staying compliant. Abrigo’s machine learning scenarios are designed to be another financial crime-fighting tool that allows you to spend more time on the things that matter.
AML AI no longer needs to be a mystery. Our scenarios identify abnormalities, provide easy-to-understand alerts, and give you all the information you’ll need to make a decision about the outlier.TALK TO A SPECIALIST
Advantages of BAM+ AML AI Solution
Automating anomaly detection allows you to spend your time where it matters most.
Tailor your machine learning scenarios to fit your institution's individual risk profile. You can select the confidence level you want the scenarios to reach to trigger alerts, allowing you to hone in on specific trends and patterns for your team to investigate.
Getting alerts without details on why they triggered could result in a flawed BSA program come exam time. Our transparent AI shows exactly what triggered your alerts so you can get a more accurate picture of the suspicious activity at your institution.
The longer you use these scenarios, the smarter they get. As the scenario gains more transaction data to process, it begins to “learn,” increasing accuracy and making it more capable to predict your customers’ habits and patterns.
Your institution is unique. Your BSA/AML software should be too.
We know your financial institution and risk profile are unique and you deserve a powerful anti-money laundering software that matches that. BAM+ was made to fit your specific needs to better detect, manage, and resolve suspicious financial activity. Don’t settle for out of the box. Think bigger.LEARN MORE
AI and Machine Learning Resources
Learn what’s new with machine learning and automated intelligence in the banking industry.
Dive deep into the technology and learn how it will impact your BSA program and institution as a whole.