CITY UNIVERSITY OF LONDON PARTNERS WITH KINDRED AND BETBUDDY TO EXPLORE USE OF ARTIFICIAL INTELLIGENCE IN AML INITIATIVES

On 3rd July, City University of London reported that a collaboration between City, University of London’s Research Centre for Machine Learning, the online gambling operator Kindred, and BetBuddy, Playtech’s responsible gambling data analytics company, has produced a White Paper: “Raising Standards in Compliance: Application of artificial intelligence to online data to identify anomalous behaviours”.  It represents the first findings from a 3-year project which will explore how artificial intelligence can be used in AML initiatives.  This initial research focused on analysing areas requiring improvement for artificial intelligence (AI) to be deployed.  The next phase of research will use real-world online gambling data to detect signs of money laundering.  As well as providing a summary of the main discussions taken from the expert and stakeholder interviews – which included experts from national crime agencies, regulators, trade associations, suppliers, and operators – the paper identifies a number of challenges to the online gambling industry and makes key technical recommendations, some of which should be tackled at industry level, and others which will form the basis of later phases of technical research.  The recommendations included –

  • development of a single format or technical protocol for submitting Suspicious Transaction Reports (STRs), Suspicious Activity Reports (SARs), and Defence Against Money Laundering (DAML) across jurisdictions that enable operators to submit cases using a consistent system while also providing feedback on submission quality;
  • continuation of efforts to develop a single central database for customers flagged for suspicious gambling activity, to enable enhanced monitoring of flagged customers across industry;
  • developing more sophisticated and cost-efficient methods to improve ongoing monitoring, with techniques that analyse player’s behaviour below the minimum threshold levels required by regulators, whilst not relying on increased staff numbers to broaden monitoring scope;
  • using data to develop more sophisticated behavioural checks and customer affordability segments to support ongoing enhanced source of wealth and source of funds checks for higher spenders, and not just at specific points required by regulators; and
  • investing in the modernisation and simplification of KYC and source of funds processes, and not viewing these as an administrative or ‘check box’ compliance process.

The report is available at –

https://www.city.ac.uk/__data/assets/pdf_file/0014/421106/City-collaborative-Whitepaper-Anti-Money-Laundering-and-Artificial-Intelligence-02July2018.pdf

Author: raytodd2017

Chartered Legal Executive and former senior manager with Isle of Man Customs and Excise, where I was (amongst other things) Sanctions Officer (for UN/EU sanctions), Export Licensing Officer and Manager of the Legal-Library & Collectorate Support Section

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