Tag: Payment fraud

APP scams, instant payments and the future of SAR reporting

Rethinking SAR thresholds in 2026 has become unavoidable as APP scams surge alongside the rapid expansion of instant payments across Europe. According to Flagright, as...

EPC launches FRIDA RFI as EU rules push tougher fraud sharing

The European Payments Council (EPC) has opened a request for information (RFI) to find organisations that could provide, operate and support a central platform...

How fraud detection rules are evolving in 2026

In 2024, consumers and businesses reported losses of more than $12.5bn to fraud, representing a 25% year-on-year increase. According to AiPrise, the scale of this...

Payment fraud hits €4.2bn as criminals adapt to SCA

The EBA and the ECB have published the 2025 edition of their joint report on payment fraud, offering a detailed assessment of fraud trends...

How account farms fuel money laundering networks

The world of financial crime is evolving rapidly, and one of the most troubling developments is the rise of money mule networks powered by...

How AI is reshaping financial crime prevention

Payment fraud has become one of the toughest challenges facing financial institutions. Attack volumes are rising, criminals are using increasingly sophisticated methods, and the...

SymphonyAI uses GenAI to tackle payment fraud

SymphonyAI’s NetReveal Payment Fraud solution is redefining how financial institutions combat payment fraud, using AI-driven technology to deliver rapid, accurate fraud detection with minimal...

Fighting APP fraud: Secure onboarding to AI tools

Payment fraud continues to rise in 2025, with platforms like Cash App under scrutiny after its parent company, Block, agreed to pay up to...

How FinTechs can stop payment fraud before it starts

Payment fraud remains one of the most persistent threats to financial institutions and payment platforms in 2025. According to Resistant AI, earlier this year, Cash...

Stopping payment fraud with behavioural analytics

As digital payments continue to expand, financial institutions face the urgent challenge of preventing fraud before it occurs while maintaining seamless customer experiences. Traditional fraud detection methods, whether rules-based systems or machine learning models, are often too rigid or slow to identify today’s rapidly evolving fraud tactics, leading to either missed threats or excessive false positives that inconvenience genuine customers.

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