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Cybercrime, and more specifically payment fraud, are an ongoing issue for any organization managing digital transactions. A successful fraud prevention strategy requires a system to correlate many different data points and accept good transactions, or deny bad ones, in less than a second. And, if you run a growing business, you need that response time to stay constant even when you support millions of concurrent transactions.
That kind of performance and scale is tough to achieve on legacy relational databases. This is why so many IT teams have turned to NoSQL to support mission-critical systems.
For more than 40 years, businesses have turned to ACI to provide electronic and digital payments with fraud processing. ACI processes upwards of $14 trillion in payments and securities a day. To support this massive volume and retain millisecond response times, the team at ACI Worldwide built a solution using DataStax Enterprise, Apache Kafka, and Hadoop. At DataStax Accelerate 2019, Ken Chenis, chief architect at ACI Worldwide explained how ACI is using DataStax, machine learning, and AI to detect fraud in real-time.
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