Money20/20 Europe 2026: ThetaRay’s Garima Chaudhary on AI-Driven AML and the Future of Financial Crime Prevention
By Ali Paterson · 8 July 2026
In brief: ThetaRay's Garima Chaudhary discusses how AI-driven AML technology identifies complex financial crimes and reduces false positives for global financial institutions.
| Primary Technology | Unsupervised Machine Learning |
|---|---|
| Efficiency Gain | 95% reduction in false positives |
| Core Focus | Cross-border transaction monitoring |
Quick Summary
ThetaRay is revolutionizing AI-driven AML by utilizing advanced machine learning to identify complex financial crimes that traditional rule-based systems miss. By analyzing massive datasets in real-time, ThetaRay enables banks and fintechs to reduce false positives and enhance global financial crime prevention efforts effectively.
How Does ThetaRay Improve Financial Crime Detection?
ThetaRay leverages artificial intelligence to move beyond rigid, legacy systems that often fail to catch sophisticated money laundering schemes. Their platform focuses on unsupervised machine learning, which allows the system to detect 'unknown unknowns' - suspicious patterns that haven't been previously identified or categorized by human analysts.
- 95% reduction in false positive alerts compared to legacy systems.
- Real-time monitoring of cross-border transactions for immediate threat detection.
- Scalable cloud architecture that supports rapid growth for global financial institutions.
What Role Does AI Play in Modern Compliance?
The integration of AI-driven AML tools allows compliance teams to focus their energy on high-risk threats rather than manual data entry. Garima Chaudhary highlights that automated risk assessment is no longer a luxury but a necessity in an era where transaction volumes are exploding and regulatory scrutiny is at an all-time high.
- Enhanced data visibility across fragmented banking systems.
- Regulatory alignment with global standards like FATF.
- Improved operational efficiency for lean fintech compliance departments.
How is ThetaRay Scaling Global Transaction Monitoring?
By providing a unified compliance platform, ThetaRay helps organizations bridge the gap between different jurisdictions. This is particularly vital for cross-border payments, where varying regulations and opaque correspondent banking networks often hide illicit flows. The technology ensures that trusted global trade can continue without the friction of outdated security checks.
FF NEWS TAKE:
ThetaRay continues to prove that AI-driven AML is the only viable path forward for an industry drowning in data. While many talk about AI, ThetaRay’s ability to deliver a 95% reduction in false positives is a massive needle-mover. As financial crime becomes more digitized, the shift from reactive rules to proactive, intelligent monitoring is the most critical upgrade a bank can make today.
Frequently asked questions
How does ThetaRay use AI for AML?
ThetaRay uses unsupervised machine learning to detect suspicious patterns in financial data that traditional systems miss. This AI-driven AML approach identifies 'unknown unknowns,' allowing banks to stay ahead of evolving criminal tactics while significantly reducing the number of false positive alerts.
What are the benefits of AI-driven AML for banks?
The primary benefits include a 95% reduction in false positives, faster transaction clearing, and better detection of sophisticated money laundering. By automating the monitoring process, banks can reallocate resources to investigating high-risk threats rather than clearing manual errors.
Can AI-driven AML help with cross-border payments?
Yes, AI-driven AML is essential for cross-border payments as it provides real-time visibility into complex transaction chains. ThetaRay’s platform analyzes data across different jurisdictions to ensure compliance with global regulations and prevent illicit funds from moving through correspondent banking networks.
Part of our Money20/20 Europe 2026 coverage.