By Bismark SAKYI The promise of artificial intelligence (AI) and machine learning (ML) to revolutionise anti-money laundering (AML) programmes has dominated headlines in recent years. From reducing ...

Interested in understanding how AI and machine learning are being used to prevent bot-based fraud attempts, I attended a few recent webinars with Kount's 3 Key Elements Needed For Successful Bot ...

The Vancouver Police Department is implementing a city-wide "predictive policing" system that uses machine learning to prevent break-ins by predicting where they will occur before they happen ...

A study by PwC found that 67% of financial crime professionals believe AI enhances rather than replaces human intelligence in fraud detection, ensuring that ethical oversight and contextual ...

AI and Machine Learning in AML Compliance. AI and ML are revolutionizing the boundaries of AML compliance by bringing about solutions that are intelligent, adaptive, and far more effective than ...

A real strength of machine learning is that it enables humans to predict and proactively address potential dangers instead of dealing with them when the damage has occurred. As we’ve seen, machine ...

Use of third-party models that rely on market-wide transfer learning in risk detection (i.e. leveraging pre-existing models trained on large financial datasets) may exacerbate this problem.

Related: Fraud Detection In Fintech: How To Detect And Prevent Frauds In the Lending Industry Fishing out identity thieves before they penetrate a server. Identity theft is common, but with the ...