New artificial intelligence research aims to transform the fight against financial crime

The service could be used by clients ranging from private equity firms carrying out pre-investment checks to banks and institutions that need to comply with anti-money laundering (AML) rules or the Senior Managers & Certification Regime (SMCR).

The project aims to streamline the screening process and automatically identify warning signs using artificial intelligence, so it can consider the context of words or images found by the software.

Neotas will work with natural language processing expert Professor Ansgar Scherp and a data scientist on the project.

Vipul Mishra, chief executive officer at Neotas, said: “We’ve been working on our proprietary AI-driven platform for almost three years and have been building in machine learning technology to help pinpoint and mitigate risk, but this partnership with the University of Essex will take that to the next level.

“We believe this could be a gamechanger for the financial services sector in terms of preventing money laundering, financing of terrorism, fraud and other crime and helping companies reduce reputational risks through enhanced due diligence processes.”

Professor Scherp said: “The Knowledge Transfer Partnership with Neotas will focus on the utilisation of a novel combination of natural language processing (NLP) and image analysis to accelerate and automate the collection of Open Source Intelligence (OSINT), providing end users with advanced insight into individuals without invading individual privacy.”

The project grant was awarded by Innovate UK, a government body that works to find and drive the science and technology innovations that will grow the UK economy.

Since 2007, it has invested more than £1.5 billion in innovations, matched by equal funding from business.

It estimates its support for innovation projects has added £7.5 billion to the UK economy and created 35,000 new jobs.

PICTURED: Vipul Mishra, chief executive officer of Neotas (right), with the Neotas and University of Sussex teams.