Are there limits to machine learning in trade surveillance?

Nick Wallis says that blending rules-based, machine learning and automation techniques can help overcome trade surveillance challenges.

Compliance professionals face the daunting task of making sense of mounds of data, alerts, and shifting regulations. The power of AI and machine learning (ML), as evidenced by the text-generating software ChatGPT, has ignited imaginations as to how new tools can empower teams to achieve more accurate results more quickly. For compliance officers, the allure of ML is that it can address the problems inherent in most surveillance systems: They generate too many alerts and false positives, leading

Only users who have a paid subscription or are part of a corporate subscription are able to print or copy content.

To access these options, along with all other subscription benefits, please contact info@waterstechnology.com or view our subscription options here: http://subscriptions.waterstechnology.com/subscribe

You are currently unable to copy this content. Please contact info@waterstechnology.com to find out more.

Sorry, our subscription options are not loading right now

Please try again later. Get in touch with our customer services team if this issue persists.

New to Waterstechnology? View our subscription options