Volt Active Data Fast Data Platform Now Features User Defined Functions to Empower Financial Organizations to Detect and Prevent Fraud Before it Occurs
BEDFORD, Mass. – August 24, 2017 – Volt Active Data, the enterprise-class database that powers mission-critical applications, today introduced the industry’s first database to enable real-time predictive fraud detection and prevention. With User Defined Function (UDF) support for SQL, Volt Active Data v7.6 enables enterprises to accelerate the identification and prevention of fraud before a transaction is complete, drastically reducing risk and enhancing the customer’s overall brand experience.
With advancing technologies, increased complexity and the growing popularity of e-commerce platforms, the risk of fraud has escalated dramatically. Despite this increased risk, most solutions in today’s market aim to detect fraud after it occurs, which can cost financial organizations millions of dollars annually. In fact, a Nilson Report estimates that losses due to credit card fraud alone could top $27.69 billion in 2017, worldwide.
As criminals become more advanced, fraudulent behavior patterns change more quickly, up to multiple times a day, which is why most applications identify fraudulent activity after a transaction is processed. With UDF, Volt Active Data now enables financial organizations to deploy new fraud prevention algorithms immediately into the data stream, improving the accuracy, intelligence and effectiveness of fraud detection logic. User Defined Functions within the Volt Active Data data platform can be updated more quickly and frequently, removing latency when defining fraudulent transactions.
“The only way to negate the impact of fraud is to catch it before a transaction is processed,” said David Flower, president and CEO of Volt Active Data. “With User Defined Function, Volt Active Data is empowering financial organizations across the globe to move to real-time fraud detection with absolutely no latency. By constantly updating fraud logic and deploying it directly into the Volt Active Data data platform, organizations can become smarter in how they identify and stop fraud, accepting only genuine transactions and stopping fraudulent ones before they happen.”
Volt Active Data v7.6 enables organizations to use User Defined Functions on Apache Kafka data streams, helping accelerate the impact of new fraud detection algorithms. Volt Active Data powers fraud detection solutions at leading financial institutions across the globe. For a live demonstration of Volt Active Data’s new User Defined Functions capabilities for real-time fraud detection, come visit the Volt Active Data booth (#113) at Kafka Summit in San Francisco on August 28th.
Volt Active Data v7.6 will be generally available at the end of the month. The latest version of Volt Active Data is currently available for immediate download here. For more information or to request a quote, please contact email@example.com.
About Volt Active Data
Volt Active Data provides the only in-memory transactional database for applications that require an unprecedented combination of data scale, volume, and accuracy. Unlike other databases, including OLTP, Big Data, and NoSQL, only Volt Active Data supports all three modern application data requirements: Volt Active Data processes data points from millions of users and sources; ingests, analyzes, and acts on data in milliseconds; and data managed by Volt Active Data is accurate all the time, for all decisions. Telecommunications, financial services, advertising, gaming and other industries rely on Volt Active Data to modernize their applications. Volt Active Data was founded by a team of world-class database experts, including Dr. Michael Stonebraker, winner of the coveted ACM Turing award.
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