Why we started
ComplyAdvantage was born out of frustration experienced first-hand by our founder, Charles Delingpole. Despite trying tool after tool to manage his responsibilities as an MLRO, they all had the same issues: being difficult to integrate, hard-to-use, and poor at providing relevant alerts.
‘False-positives’ impair the ability of compliance professionals from stopping financial crime and the activities it facilitates such as human trafficking and terrorism.
The importance of addressing this issue ultimately led Charles to found ComplyAdvantage in 2014.
What we’ve done
Existing solutions rely on manual labour to input and update data. Unfortunately, there is a limit to how frequently this can be done, resulting in data that can be months out of date. This results in false-positives and also allows recently sanctioned entities to slip through the net.
We have set up a radically different technical architecture, leveraging data science and machine learning to understand risk computationally. While we still review data manually, our approach results in data being updated in minutes rather than months.
This new approach, along with our commitment to making it as easy as possible to integrate our solutions and proactive customer support, has paid dividends. We have won multiple awards, including ‘Best onboarding’ for Santander, and has led to rapid growth – currently we have over 500 customers across 75 countries with over 200 employees.
Where we’re going
While we’re proud of the success we’ve achieved up till now, we know there is still a lot of work to do. We still have the same burning ambition to solve financial crime that motivated Charlie to start the company back in 2014.
To achieve this vision, we’re partnering with regulators around the globe and hiring hundreds of developers, data scientists, and financial crime professionals to push the boundaries of financial crime-fighting technology.
We’re also backed by some of the world’s most well-known investors and industry experts. They’ve invested in household names like Dropbox, Slack and Robinhood, and have held leadership positions at companies including Thomson Reuters and HSBC.
”Policy application will benefit from NLP and AI, resulting in officers becoming owners of models and rulesets rather than policy wording and quality controls