Survey: Fraud Teams Grow Despite Universal AI Adoption
A 2026 report from SEON surveying over 1,000 global fraud and compliance leaders found that despite near-universal use of AI, fraud prevention teams are still growing in size. The data suggests that while AI is a critical tool, it is augmenting rather than replacing human expertise, leading to rising headcounts and bigger budgets to manage increasingly complex fraud vectors and fragmented systems.
- A late 2025 TransUnion report highlights the growing financial imperative, finding that U.S. companies lost an average of 9.8% of their revenue to fraud over the past year, a 46% increase from 2024. - The complexity of threats has escalated with fraudsters using generative AI to create convincing deepfakes, voice clones, and phishing content, leading to a 1,210% rise in AI-driven attacks against major US companies last year. - A primary challenge hindering AI effectiveness is internal data infrastructure; 87% of banks cite fragmented data sources and the difficulty of integrating with legacy systems as their biggest hurdle to AI adoption. - Emerging agentic AI systems are shifting the paradigm from passive monitoring to autonomous investigation, with AI agents designed to independently follow leads, connect disparate data points, and make decisions on threats. - Regulatory pressure and the "black box" nature of some AI models are a key reason for human oversight, with 89% of banks prioritizing explainability and transparency in their AI systems to meet compliance and governance standards. - Venture capital is actively funding startups to address these evolving threats; recent examples include Resistant AI raising $25 million to combat generative AI-driven fraud and Resemble AI securing $13 million to detect deepfakes.
