The Evolution of Big Data in Financial Service

Banks and financial institutions of all sizes are now using Big Data to improve their daily operations while providing more customized solutions to their client base. According to a study conducted by IBM Institute for Business Value and Said Business School at the University of Oxford, 71% of the country's leading financial service institutions rely on the use of data and analytics to create a “competitive advantage” for their respective organization, whereas only 63% of respondents across all industries use data for this purpose.

Accessibility of Large Pools of Data

Big Data isn't a new phenomenon among financial institutions, but the landscape is changing thanks to advancements in processing power, cloud computing and data storage. No longer are institutions forced to rummage through structured data that's spread across multiple departments. Technological advancements now allow greater accessibility of large pools of structures and unstructured data, regardless of where it's located.

Compatibility with Varying Data Platforms and Models

Another notable trend with Big Data in the financial services industry is greater compatibility with varying data platforms and models. As noted in the fs viewpoint report published by PwC, Big Data frameworks are designed to work with a variety of data platforms and data models. Financial institutions no longer have to worry about compatibility errors that once plagued the industry, as new frameworks have virtually eliminated this problem by allowing for greater compatibility across different platforms.

Machine Learning

Many industry analysts are predicting the growth of machine learning in financial service. Of course, some banks already used advanced computer algorithms to identify patterns in Big Data, but this something that will likely become even more commonplace in the years to come. Machine learning can be used to identify and “tag” points of interest within huge pools of data.

Risk Assessments

Big Data allows financial institutions to conduct more meaningful and thorough risk assessments of their operations. From cyber attacks and unintentional disclosure of clients' personal information to fraud and identify theft, financial institutions face a wide range of threats. The good news is that Big Data allows these institutions to identify potential risks and weaknesses before they can be exploited.

There's no denying the fact that Big Data will only grow larger and more applicable in the financial services industry. As institutions seek new ways to differentiate themselves from their competitors and maximize profits, they look towards large pools of data for answers. Using this data, they can streamline their services, conduct more thorough risk assessments, uncover untapped markets, and lay the groundwork for future growth and expansion.

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