Summary: | As new digital channels emerge for monetary transactions, financial crime continues to soar. The good news is that recently developed AI-based crime-fighting systems are already having a positive impact. In this report, Atif Kureishy (Think Big Analytics) and Simon Moss (Teradata) examine online criminal activity and describe the benefits and challenges of deploying AI models for fighting digital crime. Roughly two-thirds of all businesses around the globe experienced financial criminal activity in 2017--up 58% from the year before. Legacy practices and traditional rules engines simply can't keep up. This report delves into research on the current state of AI adoption worldwide and discusses the advantages of AI models as well as the difficulties of putting them into practice. With this report, you'll explore: Different types of financial crime, including sophisticated fraud schemes, cybercrime, and money laundering The fallout that successful criminal schemes have on financial services firms Challenges to staying ahead of financial crime, such as regulatory complexity, real-time transactions, and pressure to innovate The state of today's anticrime measures in financial institutions and the benefits of AI-based models Challenges that crop up when deploying AI models for fighting financial crime
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