Outlier Detection technology has long been used to combat credit card fraud. Algorithms stand watch over individual credit card payments and if the algorithm identifies anything out of the ordinary, i.e. an outlier, it flags the transaction.
Citigroup has expanded the use of outlier technology to corporate banking. Algorithms now peruse commercial transactions in search of an anomaly which might mean a mistake made or an attempt at fraud.
Penny Crossman filed this report for American Banker:
“Corporate clients need help in the fight against fraud,” said Patricial Hines, head of corporate banking at Celent, citing the 2018 Association for Financial Professionals Payments Fraud and Control Survey: 78% of organizations experienced attempted or actual payments fraud in 2017. Another study the same group conducted last year found that 24% of finance professionals are using AI to manage risk within treasury and finance operations; 76% say they are currently evaluating the use of such technology.
Other large banks use AI and machine learning models for fraud prevention, but no others have publicly announced this technology for treasury services clients. “Some banks are using analytics to identify suspicious activity there, but they haven’t made a formal product out of it as Citi has done,” said Shirley Inscoe, senior analyst at Aite Group. “This may change rapidly since better protecting commercial accounts will likely become a competitive advantage in the market.”
Fraud executives Inscoe has spoken with say they are achieving strong results with the use of AI in fraud detection, “and the regulators to date have been more accepting of machine learning models used to combat fraud than to detect money laundering,” she said.
Rules-based systems do not do a good job of detecting large companies’ outlier transactions, Kohli said. “The problem with rules-based systems is by the time you write the rules, they’re already outdated as the client’s business model has changed, the suppliers they’re dealing with have changed, the composition of their flows has changed,” Kohli explained. “Every corporate client is different from the next corporate client. You can’t say that about consumers and their card behavior.”
