What problem does Transaction Monitoring solve?

Transaction Monitoring leverages AI to detect suspicious transaction patterns.

Our innovative approach delivers complete risk coverage, with typologies curated by a global network of AML experts. This enables high-quality alert generation, reduces false positives and drives efficiency in compliance – especially when it comes to meeting local AML regulations.

It also enables financial institutions to reduce high maintenance costs by automating threshold tuning and scenario testing processes. Plug into Transaction Monitoring to make your compliance more thorough, efficient and cost-effective.

Learn more about Transaction Monitoring

Transaction Monitoring with Thunes: key benefits

Complete risk coverage

Leading insight from a team you can trust. Our financial crime typologies are curated by a global community of AML experts

Fewer and high-quality alerts

Monitoring that does the hard work for you. Drive efficiency in your monitoring, with better reporting and a reduction in false positives

Faster expansion

Reach new customers, more quickly. Deploy new typologies in days instead of months with an automated simulation mode

Transaction Monitoring features

Powerful Detection Engine

Advanced detection engine that automatically generates risk indicators from typologies and accurately detects hidden suspicious transactions.

Built-in simulation mode

Powerful sandbox functionality that fully automates test/retest of new scenarios and threshold tuning.

Machine learning-based alert prioritisation

Advanced ensemble machine learning that learns from historical data and accurately classifies alerts into high, medium and low-risk levels, reducing false positives.

Self-learning mechanism

Built-in champion challenger framework that learns from changing customer data and investigator feedback to provide consistent and accurate results.

Glass-box AI model for complete transparency of alert results

Our proprietary Explainable AI (XAI) framework provides multi-level visibility and clearly explains the output of the machine learning model, to help investigators and auditors.

Automated STR reports that supports goAML reporting

Automated reporting using customisable STR templates that meet local regulations and goAML standards.

Talk to an expert

Would you like to learn more? Get in touch and one of our Tookitaki experts will be in touch with you shortly.