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Every year enterprises and governments are losing hundreds of billions of dollars due to fraud. As more and more transactions are conducted over the internet, online fraud detection, anti-money laundering and decision makings have become a necessity. Traditional RDBMS or Big-data-n-AI based fraud-detection or decision-making systems are not capable of online real-time fraud detection or decision making.

Significance

For the first time ever, the bank’s IT department sees a complete card transactional behavior network with all supernodes included, and no backlog is piled up when tons of transactions are rushing in during peak hours as they would experience otherwise with Spark or Neo4j. The ROI and performance gain is in the range of 100s to 1,000 of times, if you zoom into each transaction’s decision-making, each model takes only 0.1 millisecond (100 microseconds), that’s the beauty of real-time graph computing, only from Ultipa.

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