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Why It’s So Hard for Challenger Banks to Fight Financial Crime

Challenger banks must protect their customer experience, yet, they also need to prevent fraud and be compliant. How can they accomplish this? With a risk strategy that enables customer-centricity.

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Casting Deep Nets on Financial Crime

  • Tech Tuesdays

Can deep learning improve fraud detection models? Read about our exploration into recurrent neural networks and how they can be used to help prevent financial crime.

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How to detect fraud in less than three milliseconds

Ever wonder how a financial transaction is evaluated for risk when a machine learning platform is used? Wonder no more; we’ll show you! Watch the video to gain insight on how machine learning scores financial transactions for risk. 

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Anti-Money Laundering (AML): 5 Steps to Avoid Fines

  • AML

What could your firm do with over $2.9 billion? That’s the total amount of fines global regulators imposed on financial institutions in 2018 for non-compliance of anti-money laundering regulations. Learn 5 steps to avoid AML fines and increased regulatory scrutiny.

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Key Takeaways from the Financial Crime and Technology Summit

    Key takeaways from the 2019 Financial Crime and Technology Summit at Money 20/20 Europe. Topics covered include AI, privacy, the future of fighting financial fraud, and integrity.

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    Fighting Fraud and Financial Crime with a Single Customer View

    The number of companies who’ve reported fraudulent occurrences has surged once again — this time from 36% of banks in 2016 to an astounding 49% in 2018. This massive increase in economic fraudulent activity has occurred in parallel with digital transformation efforts at companies globally.

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    The Ethics of AI, and Why We Should All Care

    Recently, I was proud to speak at the Harvard Business School’s Machine Learning Conference, Applied AI, regarding the real-world ethical application of AI at Feedzai. I was joined by other industry experts like David Ferrucci, who built and led the IBM

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