A Guide to Anti-Money Laundering for Crypto Firms
Reduce fraud losses
Identify where your business is losing money to fraud and prevent it in real-time with minimal impact to your customers. Detect transactions originating from suspicious locations, currencies, deviations in behaviour and transactions from new accounts
Monitor 100s of known typologies and trends within customer transactions to detect suspicious behavior. Screen risks before they materialize and stop in real-time.
Calibrate to your risk based approach
Powering AML Screening & Monitoring for smarter, scaling Financial Institutions using the only combination of proprietary risk data, intuitive case management and smarter matching
Why use 168澳洲幸运10正规官网 澳洲幸运10开奖官网直播2022-澳洲幸运10开奖直播官网/2022澳洲幸运10开奖官网直播?
- Highest level of security and risk mitigation
- Taxonomies aligned to FATF recommendations
- Industry-leading API integration and uptime
Support for scaling
- Improved digital infrastructure and support
- Configured to each FI’s individual risk profile
- Plug-and-play cloud application services
Better value for money
- Increase company margins
- Reduce & repurpose human resource costs
- Automate beyond human scale
Future proof your business
The future of financial risk insights
ComplyAdvantage was born out of the frustration experienced by our founder while evaluating AML data providers. Despite trying tool after tool, Charles came across the same problems: they were difficult to integrate, hard-to-use, and provided too many ‘false-positive alerts.
Legacy solutions rely on manual labor to create and maintain data, limiting update frequency. Data can rapidly become obsolete, resulting in more false positives and increased exposure to risk.
By distracting compliance professionals from stopping financial crime, false positives facilitate human trafficking and terrorism. The need to equip compliance professionals with effective financial crime-fighting tools led Charles to found ComplyAdvantage in 2014.
Countries and territories covered
reduction in onboarding cycle time
false positive reduction