Wikibon’s Big Data Vendor Revenue and Market Forecast noted several factors that contributed to the growth of Big Data in 2012. One factor was that of “an increase in awareness of the benefits of Big Data as applied to…financial services.” What makes the financial services and Big Data such a good marriage?

To start, we have to consider exactly what Big Data is in this context. The report states:

“Wikibon defines Big Data as those data sets whose size, type and speed of creation make them impractical to process and analyze with traditional database technologies and related tools in a cost- or time-effective way.”

It goes further to say that practitioners need to have a mindset that “replaces gut instinct with data-driven decision-making.”  This definition of Big Data immediately lends itself to the world of financial services. Not only does the financial service industry have a large volume of varying data types, it also has a large amount of decision-making that occurs.

Not only are there internal decisions for a financial enterprise to make, but also decisions made external to the enterprise by its customers or patrons. Since these are financial decisions, one would want to make the most educated and beneficial decision possible, which would go well with dropping the “gut instinct,” and adopting more data-driven decisions.

Let’s look at some ways Big Data can affect the financial services industry both internally for a financial enterprise and externally with patrons and customers.

Smarter business, better banking

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Internally a financial enterprise is concerned about making money. If it’s involved in investing, then that business is also concerned about the ever-changing factors used to determine sound investments. One trend noted in relation to Big Data and financial services is that “companies require larger market data sets and deeper granularity to feed predictive models, forecasts and trading throughout the day.”

Depending on what is being considered, there are numerous streams of data coming from the stock market and other sources for which a Big Data approach would be perfect. To handle this influx of information it was also pointed out that the data warehouses that are currently in existence would need to be re-engineered with Big Data technologies.

Smarter customers, better business

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As consumers we see the growth of mobile applications that allow us to do transactions and all sorts of things related to our personal finances. This trend is leading to yet more structured and unstructured data flows from a wide variety of sources that a financial enterprise would have to manage. With the information that consumers add to the mix, a financial enterprise will have a wealth of data that they can use in relation to their customers.  As one report points out, “predictive credit risk models that tap into large amounts of payment data are being adopted in consumer and commercial collections practices to help prioritize collections activities.”

With this data it was mentioned that a financial enterprise will also be able to “implement Big Data solutions with use cases specific to increase conversion rates and address customer retention issues by delivering increasingly more individually-customized services.” The same article mentioned that financial institutions will be able to prevent cybercriminals from striking so easily due to the information they have in relation to their customers’ behavior. This same concept was brought out by IBM’s Jeff Jonas at last year’s IOD conference.

Wikibon’s forecast says that “increasingly sophisticated professional services practices that assist enterprises in practically applying Big Data hardware and software to business use cases” is a growth driver for Big Data. This is surely the case in the financial services industry. As these enterprises recognize the many business use cases that Big Data can fit into, financial decision-making processes will not only see more efficiencies operationally, but we will also see more and more consumer tools and apps that will also leverage the same Big Data technology to alter how we make decisions and manage our own finances.

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