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The Future of Fraud Prevention: Predictions for 2026

Explore expert predictions on the future of fraud prevention in 2026 and how financial institutions can stay ahead. Download the report.

Turn AML Compliance into Competitive Advantage with AI

For years, AML programs were built to satisfy regulators by completing a checklist of expectations. Today, it’s not enough to check a box. Regulators now expect proof that AML controls work as expected. Learn how to modernize your AML program with AI today.

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The State of Scams in Spain 2024

Spanish citizens lost €7.75 billion to scams last year Exclusive Insights for Spanish Banking Leaders Spanish citizens lost nearly €8 […]

The State of Scams in the Netherlands 2024

Exclusive Insights for Banking Leaders Every month, 43% of Dutch citizens are targeted by scams. Perhaps what’s most chilling about […]

15 Things to Know About APP Fraud

15 Things to Know About APP Fraud

Authorized push payment (APP) fraud has become one of the most common types of fraud thanks to the expansion of […]

With the emergence of authorized push payment (APP) fraud, banks need to apply greater focus on incoming payments that go directly to the criminal’s accounts. This is where money mules come into play, enabling criminals to move illicit funds to accounts they control. In the UK, new regulations require banks to extend fraud monitoring to both inbound and outbound payments. Other countries, including the US and Australia, are considering similar measures. Understanding the intricate dance between mule risk modeling and fraud detection becomes paramount as banks navigate this transformative phase. Learn how Feedzai delivers state-of-the-art, AI-driven tools for inbound payment fraud prevention capabilities and empowers banks to stay one step ahead of shifting regulations. Key Benefits: Regulatory Compliance: Ensure your bank remains at the forefront of the latest fraud prevention regulatory frameworks. Inbound Payment Focus: Transition from traditional methods to a comprehensive inbound monitoring approach. Mule Account Detection: Leverage AI and machine learning to counteract money mule operations effectively. Inbound-Payment-Fraud-Detection

Inbound Payment Fraud Detection & Mule Risk Modeling: Protect Your Reputation and Minimize Losses

Proactively combat authorized payment fraud, outsmart money mules, and safeguard your institution’s bottom line. Banks are losing the fight against […]

Inbound Payment Fraud Detection and Mule Risk Modelling: Prepare for Upcoming Reimbursement Regulation

With the emergence of authorized push payment (APP) fraud, banks need to apply greater focus on incoming payments that go […]

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Inbound Payment Fraud Detection and Mule Risk Modelling: Addressing the Upcoming PSR Reimbursement Regulation

The UK is taking bold steps to counteract the complexities of financial fraud. With the introduction of PSR 23/3, the […]

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How it Works: Digital Trust

Banks need to protect customers and build trust from login to logout, and at every transaction that occurs in between. […]

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How Can Banks Adopt a FRAML (Fraud & AML) Solution?

FRAML is shaking up the way financial institutions combat risk. While fraud and anti-money laundering has typically been housed in […]

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Account Takeover Fraud: Becoming Preventative vs. Reactionary

Account takeover (ATO) fraud attacks used to be about bad actors using stolen credentials to take over a victim’s bank […]

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Using Digital Trust to Stop Impersonation and Manipulation Attacks

Account takeover (ATO) fraud is on the rise. Total consumer losses from ATO fraud rose by 90% in 2021. Impersonation […]

How European Banks Can Benefit from Cloud Migration

Cloud Technology is Critical to Navigating Regulatory Sea Changes The UK’s PSR directive and the EU’s forthcoming PSD3 are changing […]

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What Is Behavioral Biometric Analysis?

Physical biometrics refer to parts of the human body that can act as unique identifiers, e.g., fingerprints and retina scans. […]

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