Attempted misuse cases caught by financial institutions increase by 26.8%.

78% of financial institutions make improving mule account detection a high or top priority over the next 12 months.

Over 50% of fraud prevention, risk, and compliance professionals say account handover fraud, where control of a verified account shifts to someone else without authorization, is more difficult to detect than other types of fraud.

More than 80% of fraud prevention, risk, and compliance professionals report that mule activity is detected reactively rather than prevented before suspicious transactions occur.

Currently, 32% of senior corporate security leaders say real-time fraud detection is largely run with agentic AI; this is expected to rise to 58% in two years.

SMBs plan to use AI in 2026 for threat detection (39%), incident response (34%), fraud detection (34%), and automated phishing detection (31%).

38% of internal audit functions test or strengthen fraud prevention and detection.

23% of UK consumers cite fraud detection and prevention as the most positive impact of AI in banking in 2025.

66% of B2B SaaS respondents express high confidence in current fraud prevention tools to detect AI-powered attacks.

44% of respondents in sectors other than B2B SaaS/overall average are very confident in current fraud prevention tools to detect AI-powered attacks.

42% of UK CFOs surveyed identified fraud detection and prevention as an area of their finance operations they would most like to improve through automation.

More than 43% of Americans say AI-powered fraud detection would increase their confidence in their financial institution.

Nearly 72% of Americans are either “somewhat,” “very,” or “extremely” interested in AI-powered fraud detection tools.