Shield, a global communications risk management company purpose-built for financial institutions, has commissioned research showing that more than 90% of banks remain trapped in alert-heavy surveillance environments, even as investment in AI-driven monitoring accelerates across the sector.
The study, carried out by 1LoD, reveals that the industry’s core surveillance challenges have barely shifted since 2024. False positives continue to rank as the most significant obstacle facing compliance teams, with no measurable progress recorded over the past two years. The research points to a growing gap between ambition and execution, with many banks still held back by outdated technology, disconnected data sources and operating structures built for an earlier era of compliance.
The findings stem from a report titled “The Future of Surveillance: Turning AI Ambition into Operational Reality,” produced by 1LoD, a specialist conference and intelligence provider covering non-financial risk and compliance within banking.
Responses were gathered from senior surveillance and compliance figures at financial institutions, with results benchmarked against 1LoD’s 2024 survey to chart how industry pain points have developed.
False positives were flagged as highly significant by 52% of participating firms, ahead of budget and staffing pressures (41%), poor access to quality data (37%) and legacy technology (37%). Notably, just 7% of respondents viewed regulatory pressure as a major concern, reinforcing the report’s conclusion that operational execution, rather than regulatory ambiguity, is now the primary obstacle for most institutions.
Shield’s own deployment figures, referenced within the report and compiled from analysis covering millions of communications, indicate a roughly threefold cut in alert noise relative to legacy monitoring tools.
Where direct comparisons were made, this translated into accuracy gains of up to 44% and roughly triple the volume of actionable escalations, suggesting that a smaller number of sharper, better-calibrated alerts can materially strengthen risk detection.
Shield describes itself as a global communications risk management provider built specifically for the needs of financial institutions, while 1LoD operates as a specialist intelligence and conference business focused on non-financial risk and compliance across the banking industry.
The report also sets out what distinguishes compliance functions that are successfully embedding AI from those still struggling to convert investment into tangible surveillance improvements and stronger regulatory preparedness. Leading firms, it finds, are shifting away from static, rules-based detection towards adaptive models capable of learning from behavioural patterns, consolidating fragmented data and workflows into unified platforms, and linking surveillance spending directly to measurable cuts in manual review work.
According to the report, this operational transformation, rather than technology adoption alone, is what ultimately determines whether AI investment improves detection outcomes. Looking ahead, the report concludes that surveillance is shifting toward a model built on integrated data, context-led detection, lower operational noise and measurable results, with institutions that close the gap between available tools and actual practice positioned to cut costs while sharpening genuine risk detection.
Shield co-founder and CEO Shiran Weitzman said, “AI ambition is everywhere right now. What’s missing is execution. Investment is accelerating, but the fundamentals still matter. AI cannot deliver its full potential when surveillance is constrained by fragmented data, legacy infrastructure, and alert-heavy operating models. Closing that gap is what will separate firms that simply deploy AI from those that fundamentally improve how risk is detected and understood.”
Copyright © 2026 RegTech Analyst
Copyright © 2026 RegTech Analyst
