Fujitsu and LARUS Leverage Power of Graph Database and Graph Explainable AI Technologies to Strengthen Detection of Credit Card Fraud

Fujitsu and LARUS have jointly verified that credit card payment fraud can be detected with high accuracy by integrating Deep Tensor, an explainable graph AI technology developed by Fujitsu into the LARUS platform for graph databases. Fujitsu and LARUS achieved this by linking the LARUS platform for graph databases with Fujitsu’s graph AI technology. Compared with previous, rule-based approaches created manually by data analysts, the fraud detection rate improved from 72% to 89%, while the false detection rate was successfully reduced by 63%.

READ  Mitsubishi Electric Develops AI Technology that Enables Industrial Robots to Optimize Motions in Real Time even as objects move

Additionally, it was confirmed that the creation of rules for fraud detection could be supported by presenting the decision factors of fraud cases detected with graph AI technology. Going forward, both companies will verify the effectiveness of this technology in other industries with the objective of delivering practical uses for graph databases and graph AI. Detailed results of this verification trial will be demonstrated at the AI & Big Data Expo Europe 2020 conference, to be held online.

READ  Fujitsu PRIMEHPC FX10 supercomputer system for Taiwan's Central Weather Bureau