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Cybersecurity reports and statistics published by Fingerprint

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Research Reports

Reports and publications from Fingerprint

Recent Statistics & Reports

49% describe a moderate increase in investigation time due to AI-powered attacks.

Only 7% report minimal impact on team workload due to AI-powered attacks.

52% of fintechs are evaluating AI-powered fraud detection tools.

51% of payment platforms are evaluating AI-powered fraud detection tools.

41% of fraud attacks targeting surveyed organizations are now AI-driven.

99% of organizations surveyed have experienced measurable fraud losses linked to AI-powered attacks in the past 12 months.

25% of traditional banks rate their fraud prevention as significantly ahead of competitors..

62% of B2B SaaS respondents indicate their fraud teams spend significantly more time on manual processes due to AI-powered attacks.

Over 44% of respondents report that their teams now spend significantly more time on manual triage and investigation due to AI-powered attacks.

51% of payment platforms are hiring specialized fraud prevention talent.

The average loss due to AI-driven fraud is $414,000 per organization.

34% of respondents say their organization sees up to $1 million in annual fraud losses from AI-powered attacks.

Nearly half (48%) of organizations report annual losses between 100,000–500,000 due to AI-powered fraud

17% of organizations report annual losses under $100,000 due to AI-powered fraud.

93% of fraud teams report noticeable operational impacts from AI-driven threats.

44% of banking respondents indicate their fraud teams spend significantly more time on manual processes due to AI-powered attacks.

32% of fintech respondents indicate their fraud teams spend significantly more time on manual processes due to AI-powered attacks.

27% of respondents report that privacy-first technologies severely impact their fraud detection capabilities.

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

49% describe moderate impacts of privacy-first technologies on fraud detection capabilities.

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