Big Data in Finance: Why You Need an Enterprise-Wide Strategy

Big Data in Finance: Why You Need an Enterprise-Wide Strategy

In a desire to remain competitive, companies have begun to rethink the role of big data in finance. Many are formulating enterprise-wide big data strategies that works hand in hand with their other digital transformation initiatives.

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According to an IDC survey, 28.5 percent of banks say that over half of their new IT initiatives are driven by digital transformation. This move toward embracing technology allows organizations to adopt new ways of doing business, and to then outpace their competitors by improving their operations and driving customer loyalty. In particular, many banks and other financial institutions have started to rethink the role of big data in finance, and have formulated an enterprise-wide big data strategy that works hand in hand with their other digital transformation initiatives.

Does your company have a strategy in place? If not, here’s why you should consider developing one.

Your Organization’s Success Depends on Mastering Data Flow

Financial transactions, customer interactions, and market decisions are all driven by data. The more digital transformation takes hold, the more success will depend on financial institutions learning to control the flow of data and knowing how to act quickly on the insights they derive from that data.

Klarna is one finance company that has mastered data collection and embraced an enterprise-wide data strategy. The leading e-payment platform in Europe helps create frictionless transactions between merchants and their buyers. The company acts as a type of mediator at the point of sale, taking on the responsibility for payment claims on behalf of the merchant, and buyer payments on behalf of the consumer.

“For them to have as frictionless and smooth an experience as possible, we need to base our decisions and our services on a lot of data,” explains Max Fischer, vice president of engineering for data, finance, and IT operations. With the help of a big data platform, Klarna has seen 60 percent growth year over year, and has been able to take on new markets and new merchants.

Data Can Help Lower Risk and Maximize Opportunity

Big data in finance serves as the grounding force to inform the positive interaction between institutions and their customers. For the financial sector, however, it must also serve as a source of truth used to uncover anomalies and irregularities that may point to financial crimes. An enterprise-wide big data strategy can help banks and other finance companies lower their risk and prevent fraud.

Bad actors are constantly looking to take advantage of any easy opportunity in the financial sector. The increasingly connected world has made financial transactions much easier, but it’s also opened up more avenues for criminal activity. The 2018 Global Economic Crime and Fraud Survey from PwC reported that economic crime hit its highest rate in 20 years of the survey’s history. The survey found that in the U.S., 37 percent of organizations reported financial losses greater than $1 million.

For the financial sector, fighting fraud is a balancing act. Companies have to prevent as much fraud as they can, while still keeping customer and merchant transactions as effortless as possible. Big data operations can help maintain that successful balance by helping to reveal which anomalies are attributable to specific customer behavior, and which truly stand out as abnormalities that require investigation.

Implementing big data in finance is no longer optional. To make the most of every customer interaction and to reduce risk to an acceptable level, big data initiatives must take priority. An enterprise-wide big data strategy is the competitive advantage that financial institutions need to make the most of their digital transformation.

To learn more about the current IT opportunities and challenges for banks and other financial institutions, read this white paper.

Ronda Swaney
Freelance author and journalist
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