Big Data is More Than a Buzzword…So Treat it Accordingly

“Big data” and “big data analytics.” For the past few years, both terms have appeared frequently in business and consumer media alike. And while some people may consider the two to be just buzzwords, nothing could be further from the truth when it comes to payments. Here is a “crash course” in big data and big data analytics—and their impact on the payments landscape.

Big Data Defined

Simply put, big data is a vast set of individual pieces (millions or trillions of pieces) of information. According to Talend, a provider of data integration and governance platforms, it is also a “catch-all term used to describe a gathering, analyzing, and storing massive amounts of digital information to improve operations.” Big data analytics, meanwhile, is the process of evaluating that information—which typically resides in disparate databases and log files as well as in proprietary systems (for example, account management or accounting)  and turning it into business intelligence.

Companies possess big data even when that does not seem possible. For example, suppose a company accepts 10,000 payments a month. Those payments represent far more than 10,000 data points—millions, in fact—when data points pertaining to how each payment was made (i.e., by credit card, debit card, ACH, etc.), via what device, at what time and date, and the like are factored into the equation.

Big Data Analytics and Payments

It is important to note that big data is most valuable when disparate data sources are consolidated in a single place—a data warehouse. This enables different people to query and analyze the data in different ways for different purposes. When it comes to payments, this could mean the ability to:

  • Identify the cause(s) of transaction processing problems and eliminate their after-effects. For example, merchants can typically see payment dates, amounts paid, and customer account numbers for their transactions. However, there is no data pertaining to the web browsers, devices, or operating systems used to complete these transactions. This and other data resides in server log files and is sometimes used by IT departments to troubleshoot technology issues. But for the most part, it is stored separately from usable business data.

With a data warehouse in place, merchants can keep all this information together in one location. They can then perform big data analysis to identify trends such as the fact that a significant number of failed payments occurred on the same type of device and/or at a certain time. In turn, they have the opportunity to identify and address the root cause(s) of failed payments, potentially boosting payment authorization rates and increasing customer satisfaction.

  • Use payment data to spark business improvements. Merchants can harness their data warehouse in tandem with business intelligence tools like Microsoft BI to create real-time dashboards aimed at making positive changes based on insights gleaned from data. For example, one such dashboard could allow near-instant monitoring of payments, so anomalies can be identified before they become real problems.
  • Personalize the payment experience. Big data analysis can be used to determine which payment methods are preferable or work best for individual customers—an opportunity that may contribute to customer “stickiness.”
  • Shore up security. Fraudsters are becoming increasingly sophisticated in and adept at infiltrating, breaching, and abusing account and other financial data; even experienced security professionals have difficulty fighting back against them. Big data paves the way for real-time collection and analysis of streams of information, like login attempts and port access. Perpetrators can then be detected, and their activities mitigated, in timely fashion. The same is true of other anomalies.

E-Complish will continue to monitor developments in business and data analytics as they relate to payments. To learn more about E-Complish’s menu of payment solutions, or schedule a consultation, click here.