A majority of organizations (58%) in the financial services industry are using in-memory technologies, which provide the level of processing power often essential for real-time analytic applications, according to a survey of about 200 IT decisions makers by GridGain Systems, a provider of open source and commercial in-memory data fabric products.

Some 28% of the survey respondents said they are using in-memory technologies in a “mission-critical capacity.”

For the report, “A Cautious Revolution: Financial Services’ Prudent Embrace of Real-Time Analytics,” GridGain asked IT professionals in the finance sector about their companies’ attitudes, practices and challenges around data technology, with a focus on the state of the industry’s adoption of real-time analytics technologies.

         “The number of IT professionals reporting that in-memory is mission-critical isn’t too surprising,” Max Herrmann, executive vice president of marketing at GridGain, said in a statement. “Financial services is on the leading edge of adopting technologies that enable hyper-scale processing around functions like risk analysis and high-volume transactions, which involve processing and analyzing increasingly massive and diverse datasets in real time.”

         Forty two percent of the respondents reported risk analysis as the area to which real-time analytics technologies offer the most value, with cyber-theft and fraud prevention applications next at 31%.

         While only 22% of respondents said accessing the necessary data streams was the biggest obstacle to real-time decision-making, processing speed (40%) and integrating diverse data streams to form a single picture (38%) were reported as more significant challenges.

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