Traditional monitoring systems can’t handle the scale

Existing transaction monitoring systems produce thousands of false positives so your team has to manually process paperwork to uncover real risk.

Money laundering fuels horrendous crimes

Trade-based money laundering is more than evading import duties or currency restrictions. It’s used to move corrupt funds, enable human and wildlife trafficking, and smuggle weapons.

False positives are hiding the real risks

Rules-based transaction monitoring systems are not effectively detecting risk. The result: too many alerts—up to 99% of which are false positives—and mounting costs.

Criminals are becoming more sophisticated

Criminals are hiding their footprints in complex networks of transactions and using electronic trading to take advantage of pitfalls in technology. Without context, money laundering is impossible identify automatically.

Current transaction monitoring investigations use a tick-box approach

Your investigators are dealing with unmanageable amounts of false positives. There’s only so much they can do without the right data.

The cost of compliance is rising

Adding more people to investigation teams will continue to get more expensive. But existing AI models aren’t delivering results or meeting regulatory requirements.