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AI Use Case

Detect potentially fraudulent or nefarious users

Detect potentially fraudulent or nefarious users (e.g. individuals under sanctions, investigation etc) through pattern matching of structured and unstructured data on transactions from different sources, such as phone numbers, addresses, company directors and news reports (HSBC, Quantexa, Silent Eight)



Cost - Fraud reduction,Risk reduction - Reduced legal exposure,Risk reduction - Reduced compliance risk

Case Studies

HSBC~HSBC to implement Quantexa's AI software to aid with compliance in identifying illegal and fraudulent customer profiles ,Earthport~Earthport Payment Network reduces false positives of automated suspicious transaction detection using AML risk data in real-time ,Holvi Payment Services~Holvi reduces time spent investigating false positives for customer risk using AI platform ComplyAdvantage,Bank of the West~Bank of the West announced implementation of Pindrop's machine learning fraud detection software in its call centres,Chime~Chime decreases basis point loss by 40% using a machine learning fraud detection platform,Government of the United Kingdom~The UK government identifies welfare and state benefits fraud with artificial intelligence ,US Department of Homeland Security~The identifies impostors at airports with facial recognition technology ,Soter Technologies~US and Canada schools achieve a 70% decrease in students vaping at bathrooms with the use of machine learning,Spanish National Police~Spanish National Police identifies false robbery reports with over 80% accuracy using machine learning and natural language processing,Danske Bank~Danske Bank prevents card fraud with the use of machine learning

Potential Vendors



Financial Services


Data Sets

Structured / Semi-structured,Time series

AI Technologies

Machine Learning (ML),ML Task - Grouping - Anomaly Detection,Product Type - Natural Language Processing (NLP)

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