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Big Data in Financial Services Industry: Market Trends, Challenges, and Prospects 2013 - 2018

Financial services big data market set to expand rapidly as profit margins are squeezed in 2014


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2014-01-09 05:31:01 - Big Data in Financial Services Industry: Market Trends, Challenges, and Prospects 2013 - 2018 - a new market research report on companiesandmarkets.com

The financial services big data market is set to expand rapidly over the next few years as companies opt to efficiently analyse their large databases to improve processes, reduce costs and become more competitive. The industry is currently lacking the availability of talent and as a result, it is anticipated that big data analytics companies will benefit from this, with the number of these specialist companies tripling over the next three years.

Recent big data market studies from IDC and IIA have estimated that the big data services market be worth US$16.1 billion in 2014 as the sector reports significant growth over recent years. The growth rate of the big data services market is set to be six times greater than

 

 

any other IT market sector. The financial services market is set to follow the ther leading industries adopting big data analytics programmes. Healthcare, industrial and retail sectors have already adopted big data practices and the increased pressure on profit margins within the financial services market is set to drive the rapid adoption of big data analytics solutions over recent years.

Big Data is making a big impact already in certain industries such as the healthcare, industrial, and retail sectors. With the exception of the government sector, no other industry has more to gain from leveraging Big Data than the financial services sector. Big Data technology will help financial institutions maximize the value of data and gain competitive advantage, minimize costs, convert challenges to opportunities, and minimize risk in real-time.

Big Data technologies provide financial services firms with the capability to capture and analyze data, build predictive models, back-test and simulate scenarios. Through iteration, firms will determine the most important variables and also key predictive models.

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