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Home » Signicat: 42.5% of fraud attempts are now driven by AI: financial institutions rush to strengthen their defenses – FF News
AI in Finance

Signicat: 42.5% of fraud attempts are now driven by AI: financial institutions rush to strengthen their defenses – FF News

3 Mins Read
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As cybercriminals increasingly turn to artificial intelligence to implement complex fraud schemes, the financial industry finds itself engaged in a high-stakes battle to protect its customers and assets. New data from the 2024 report Fighting AI-powered identity fraud by Significance reveals that AI-based fraud now constitutes 42.5% of all fraud attempts detected in the financial and payments industry, marking a critical turning point for cybersecurity in the financial sector. Additionally, an estimated 29% of these attempts are considered successful.

This report highlights the growing threat posed by AI-enhanced fraud tactics, which include the use of deepfakes, synthetic identities, and sophisticated phishing campaigns. These advanced techniques allow fraudsters to operate at an unprecedented scale and level of sophistication.

Current Trends in AI-Based Fraud

  • 42.5% of detected frauds involve AI: Nearly half of all fraud attempts are now AI-based, reflecting the growing sophistication and prevalence of these attacks.
  • 80% increase in total fraud attempts: The financial industry has seen an 80% increase in fraud attempts over the past three years, driven in part by fraudsters’ adoption of AI.
  • Only 22% of companies have implemented AI defenses: despite the increased risk, less than a quarter of financial institutions have taken steps to deploy AI-based fraud prevention measures, thus exposing a significant vulnerability.

A weak response: Financial institutions are lagging behind in defending against AI

Faced with this evolving threat landscape, financial institutions are increasingly aware that traditional defenses are insufficient against AI-based attacks. The report, developed in collaboration with Consult Hyperion, urges companies to adopt AI-based detection systems, improve cybersecurity frameworks and foster greater industry collaboration to stay ahead of the evolution of fraud techniques.

According to Kasada State of Robot Mitigation in 2024 report, 87% of respondents say their leadership team is concerned about bot attacks and AI-based fraud. Nonetheless, Signicat’s report reveals that three-quarters of respondents say they lack the expertise, resources and budget to combat AI-based identity fraud. This suggests that companies in the financial sector are not prepared for this threat.

The expertise gap: financial institutions struggle to keep up

“Companies are of course putting in place defenses against AI-based identity fraud, but the threat is growing. The acceleration of digitalization that we are seeing in recent years has also made attacks more sophisticated and executed at scale. The mechanisms that worked a few years ago are no longer enough and there is an urgent need for businesses to consider a multi-layered approach, for example combining electronic identities with risk analysis and, where necessary, improvements. Only then can they strike the right balance between letting legitimate users through with less friction and introducing additional security measures in case of risk. states Pinar Alpay, product and marketing director at Signicat. “With account takeover one of the most common forms of identity fraud, secure and robust digital identity solutions also protect end users and their accounts when they log in or accept documents.”

The report highlights the need for a proactive, multi-layered cybersecurity approach that integrates AI with traditional security measures. It further highlights the importance of educating employees and customers about the new threats that AI poses in the evolving cybercrime landscape.

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The Openenvoy AI platform achieves 90% automation in finance and expands the leadership team.

September 16, 2025

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September 16, 2025

The Saudi fintech startup Tamara secured $2.4 billion in funding.

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