The financial landscape has changed greatly over the years, as the digital revolution has enabled online payments, cryptocurrency, digital loans, and more. These changes brought with them new ways of interacting with customers and other financial institutions, and skyrocketed competition by narrowing barriers to entry. The digital transformation in finance also produced never-before-seen volumes of data growing at an unprecedented rate.

Along with great potential, the openness and accessibility of the new landscape increase challenges around fraud detection, risk management, and customer retention, which compound the strain of fulfilling ever-changing regulatory requirements. Facing a data boom, financial services companies – from the Fortune 500s to the local city banks – understand the value of their growing data, and seek to exploit it to answer critical business questions: What is our competitive advantage?  How can we better need the needs of our customers through product and services? Where can we optimize processes for increased performance?

While data has become a best friend to the financial services industry, it has also become its greatest challenge. Although financial institutions were among the pioneers of data analytics, their data infrastructures have over time become increasingly complex, built on legacy systems that were designed for much smaller volumes of data. The result is extremely long-running queries, time wasted on data preparation, and analytics restrictions that stand in the way of game-changing business insights.

As organizations are increasingly realizing, timely insights are crucial to achieving sustainable business, but require continual organizational analysis and updated infrastructures in order to be achieved. For those ill-equipped to handle the new reality, the data boom can in fact mean a data ‘bust.’

The new use case brochure, ‘Data Boom or Data Bust? Analytics Challenges and Solutions in the Financial Sector explores how massive data growth has impacted the financial industry, and how SQream empowers financial services companies to meet data analytics challenges head-on to exploit the full value of their data stores. The brochure explores use cases in which the SQream data analytics acceleration platform has been used to achieve cost-efficiencies, deeper customer insights, operational improvements, risk reduction, and adherence to standards, among others. The brochure is available for download here.