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Combatting Fraudsters with AI and ML

Jack Henry™byJack Henry™
November 2, 2023
in Strategy
Reading Time: 2 mins read
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In recent years, community and regional banks have been under increasing obligation to discover and report money laundering and tamp down on fraud losses. And this trend shows no sign of slowing down.

Many of the newest and most common fraud and laundering techniques have developed as an unintended consequence of the massive and permanent shift in demand for online services for virtually everything, from banking and retail to groceries. Over the last few years, many banks have found themselves struggling to acclimate to the burgeoning digital demand of today’s consumers. Meanwhile, fraudsters and launderers have been expanding into a newly discovered “Wild West,” hastily pioneering new strategies that are able to evade status quo monitoring efforts.

Countless banks are now learning how critical it is to develop innovative solutions to meet these new challenges – and quickly. Older automated systems and manual approaches that may have served you well for many years are now leaving you exposed in ways that can no longer be ignored.

One of the most interesting and promising solutions emerging on the financial crimes scene is the development of software solutions featuring artificial intelligence (AI) and machine learning (ML). Together, AI and ML offer the best opportunity for overcoming the limitations of rules-based systems and recalibrating the attitudes and mindsets of our financial institutions – from a defensive posture to an offensive one.

The nature of AI and ML models is their ability to quickly establish patterns, incorporate and consider a constant flow of new data, adapt to changes, and detect meaningful events and anomalies. This means that system admins are largely relieved of the guesswork previously associated with parameter selection, as well as the frustration of periodically trying to refine systems they do not feel adequately knowledgeable about.

The methodologies and strategies developed by fraudsters and launderers will only grow more nuanced, subtle, and diversified as online/digital banking and payment systems expand to include more users. To combat the new technologies and opportunities being discovered by criminals and bad actors, banks will have to adopt new technologies to stop them. Now is the time to seriously consider the crucial role AI/ML can play in your AML and fraud detection efforts.

Are you prepared to combat fraudsters in the real-time digital world? Learn how.

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