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The State of Real-time Analytics in Financial Services By @GridGain [#BigData]

Financial Services' Prudent Embrace of Real-Time Analytics

The State of Real-time Analytics in Financial Services

My company, GridGain, recently announced the results of a survey that asked close to 200 IT decision-makers - including project managers, network managers, software and business analysts, and other technology professionals working in the financial services industry - 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. Here's what we found:

In the report - A Cautious Revolution: Financial Services' Prudent Embrace of Real-Time Analytics - respondents described an industry that is largely familiar with, and increasingly adopting and seeing the value of real-time computing technologies. A majority - 58% of respondents - reported that their company uses in-memory technologies, which provide the level of processing power often indispensable for real-time analytic applications, and 28% reported that they are used in a "mission-critical capacity."

Deriving Mission-Critical Value from Real-Time Analytics

"The number of IT professionals reporting that in-memory is mission-critical isn't too surprising," said Max Herrmann, Executive Vice President of Marketing at GridGain. "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."

42% 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 reported second (31%), offering a view of a landscape that GridGain believes may yield forthcoming changes. "Currently, people in financial services are approaching real-time technologies mostly from an analytics-focused perspective," said Herrmann. "But areas like cyber theft and fraud detection will require expanding the view of real-time's role to include a more integrated picture of analytical and operational processing, allowing companies to dramatically shorten the time between when actionable data is discovered and when relevant action can be taken."

Obstacles to Real-Time Decision-Making

While only 22% of respondents reported "accessing the necessary data streams" as 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. "The data is there, and there's little problem accessing it," said Herrmann. "However, the decision-making pipeline is slowed by reliance on traditional disk-based processing as well as the variety of data structures and data sources organizations are trying to make sense of in their decision-making process. This problem is only likely to worsen until the traditional approach of processing different data within their own silos is addressed, as organizations will only be taking in more and more data."

A Need for Speed and Scalability

39% of respondents identified scalability and speed as the areas they would most like to see the next data technology upgrade, outstripping security (19%), cloud-based analytic tools (22%), and improved uptime (18%).

"Despite the industry's prudent conservatism, we see confirmation that Financial Services continues to be at the forefront of adopting many of these real-time technologies; the nature of the business demands it," said Herrmann. "In these findings, we see an industry facing some growing pains, but we also see that it is clearly poised to continue taking the lead in adopting data processing innovations."

More Stories By Nikita Ivanov

Nikita Ivanov is founder and CEO of GridGain Systems, started in 2007 and funded by RTP Ventures and Almaz Capital. Nikita has led GridGain to develop advanced and distributed in-memory data processing technologies – the top Java in-memory computing platform starting every 10 seconds around the world today.

Nikita has over 20 years of experience in software application development, building HPC and middleware platforms, contributing to the efforts of other startups and notable companies including Adaptec, Visa and BEA Systems. Nikita was one of the pioneers in using Java technology for server side middleware development while working for one of Europe’s largest system integrators in 1996.

He is an active member of Java middleware community, contributor to the Java specification, and holds a Master’s degree in Electro Mechanics from Baltic State Technical University, Saint Petersburg, Russia.

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