AI Case Study
Danish Danske Bank increases payment fraud detection by 60% and reduces false positives by 50% with machine learning
Danish Danske Bank had a problem with false positive that was approaching 99.5%. Using advanced machine learning they were able to increases fraud detection in real-time by 60% and reduce false positives by 50% .
Industry
Financial Services
Banking
Project Overview
'For online transactions, credit cards and mobile payments, banks need a real-time solution - the state of the art AI-driven fraud platform we have developed in collaboration with Danske Bank scores incoming transactions in less than 300 milliseconds. It means that when customers are standing in the supermarket and buying groceries, the system can score the transaction in real-time and provide immediately actionable insight.'"
"The engine uses machine leaning to analyze tens of thousands of latent features, scoring millions of online banking transactions in real-time to provide actionable insight regarding true, and false, fraudulent activity."
Reported Results
"The team has managed to take the false positives from the models and reduce them by 50 percent. By significantly reducing the cost of investigating false-positives, Danske Bank increases its overall efficiency and is now poised for substantial savings. At the same time, they are able to catch more fraud - actually upping the detection rate by around 60 percent."
Technology
"The engine uses machine leaning to analyze tens of thousands of latent features, scoring millions of online banking transactions in real-time to provide actionable insight regarding true, and false, fraudulent activity."
Function
Risk
Audit
Background
"Danske Bank’s original fraud detection system was largely based on handcrafted rules that had been proactively applied by the business over time. With record numbers of false positives - at times reaching 99.5 percent of all transactions - the costs and time associated with investigation had become significant, with the bank’s large fraud detection team feeling overworked, yet not effectively utilized."
Benefits
Data
"[T]ens of thousands of latent features, scoring millions of online banking transactions in real-time to provide actionable insight regarding true".