Resources

Insights for financial crime teams

Customer stories, white papers and blog posts on AI-native risk decisioning, from the teams running financial crime compliance at scale.

  • FX leader cuts customer wait times 81% with Ray

    Customer story

    AI investigation

    FX leader cuts customer wait times 81% with Ray

    By unifying a multi-vendor compliance stack under Ray, the institution cut automated investigations from 8 minutes to 91 seconds, so customers wait 81% less for a compliance decision.

    Global FX · 3 min read
  • UK banking and fintech trust report 2026

    Report

    Transaction monitoring

    UK banking and fintech trust report 2026

    88% of 1,023 UK consumers would consider switching after an AML failure, and 96% expect clear onboarding. Survey data on the friction and communication that drive retention.

    31 min read
  • Re-engineering transaction monitoring economics

    White paper

    Transaction monitoring

    Re-engineering transaction monitoring economics

    An economic, technical and regulatory blueprint for moving Tier 1 banks from static rules to unsupervised machine learning detection and agentic AI investigation.

    21 min read
  • Scaling AML monitoring across $200B+ volume

    Customer story

    Transaction monitoring

    Scaling AML monitoring across $200B+ volume

    How Shift4 slashed false positives by 86% and reclaimed analyst bandwidth across $200B+ in annual volume.

    Shift4 · 4 min read
  • The $442 Billion Money Mule Problem No One Is Solving Alone

    Blog

    Transaction monitoring

    The $442 Billion Money Mule Problem No One Is Solving Alone

    INTERPOL puts global fraud losses at $442 billion, and AI-driven recruitment is feeding mule networks. Why mules sit across fraud, AML and sanctions, and how agentic AI helps investigators.

    3 min read
  • AI-based AML tools and EU AML reform

    Report

    Regulation

    AI-based AML tools and EU AML reform

    A legal analysis arguing AI and ML are becoming a required part of AML internal governance, weighing the benefits against explainability and accountability demands under the AMLR and AI Act.

    44 min read
  • AI customer due diligence cuts EDD 60%

    Customer story

    Customer due diligence

    AI customer due diligence cuts EDD 60%

    AirPak replaced static country risk matrices with ThetaRay's AI customer risk assessment, cutting unnecessary EDD cases and onboarding friction across Latin America.

    AirPak · 2 min read
  • Why 80% of Enterprise AI Projects Fail (And How to Fix It)

    Engineering blog

    Transaction monitoring

    Why 80% of Enterprise AI Projects Fail (And How to Fix It)

    The obstacle is an execution gap, not the technology. Why it is most dangerous in real-time financial crime compliance, and why systems must be explainable, observable and audit-ready.

    5 min read
  • Testing sanctions screening systems for blind spots

    White paper

    Sanctions screening

    Testing sanctions screening systems for blind spots

    A framework spanning data flows, matching rules, hit rates, latency and ongoing reviews, to catch false negatives, cut false positives and keep screening audit-ready.

    25 min read
  • Scaling transaction monitoring for 10x growth

    Customer story

    Transaction monitoring

    Scaling transaction monitoring for 10x growth

    How ClearBank slashed investigation times from months to minutes and eliminated operational noise with ThetaRay's AI.

    ClearBank · 3 min read
  • How U.S. consumers judge financial crime risk

    Report

    Regulation

    How U.S. consumers judge financial crime risk

    How consumers perceive financial crime risk, and how that perception translates into loyalty, advocacy and brand value for banks and fintechs.

    15 min read
  • Moving from Pilot to Production: 5 Lessons for Scaling AI

    Blog

    Transaction monitoring

    Moving from Pilot to Production: 5 Lessons for Scaling AI

    Why AI pilots stall: set baseline metrics before launch, build governance from day one, and expect messy production data. Takeaways from a Crowe and ThetaRay webinar.

    4 min read

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