Big Data Trends in the Financial Industry

Big Data Trends in the Financial Industry

Banks, brokerages and other financial institutions are all looking for ways to put big data to work these days. According to a study by the IBM Institute for Business Value, more than 70% of financial companies that use big data analytics say it creates a competitive advantage for their organization.  

Financial organizations tend to have a lot of data, and mining that data can help them find a way to maintain their edge with customers. “The key is making sure you use big data for what it is, a signal of how people have responded to a set of past circumstances,” says Eric Nalbone, head of performance marketing for Kabbage, which provides funding to small businesses.

Here’s a look at the biggest trends in how financial firms are using big data in their organizations.

Applying It to Risk Management

Financial institutions and companies that want to protect themselves and their customers have found big data to be a strong tool. On the consumer side, for example, trended credit data can support mortgage credit assessment, says Steve Solomon, an independent consultant. “This approach takes a view over time of a borrower’s credit patterns to better understand how they manage credit,” he says. “For example, do they carry a balance every month on credit cards, or pay off their balance in full? Are outstanding balances increasing or decreasing?” This information can provide a clearer picture than a traditional credit report, which just shows one moment in time, he says.

Advances in data science, artificial intelligence and big data management have also made it possible to identify and evaluate threats such as money laundering, says David McLaughlin, CEO of QuantaVerse, which provides data-powered risk reduction analyses. “Financial institutions have begun working smarter through the use of new technologies such as AI and machine learning,” he says. This has dramatically improved the effectiveness of money laundering investigations and made it possible to efficiently identify all money laundering transactions, regardless of the dollar amount.

Using It to Improve Financial Planning

Big data analytics can help investors and financial planners make better decisions, experts say. Larry Miles, principal at investment adviser firm AdvicePeriod, says data science will “completely revolutionize the financial advice industry in less than five years.”

Using data science in investing can help take out any of the biases, emotion or preconceptions that humans introduce into the process, he says. Making an analytical decision about where to invest savings or how to plan for retirement will be much easier for consumers with the tools that will be available, and the decisions will likely be better. “Companies who embrace data will get ahead, while those who do not will die,” Miles says.

Digging In to Better Target Marketing Efforts

Data analytics can be used in other departments, as well. Using big data principles on your marketing results, for example, makes it possible to get a clearer picture than ever before of what your customers are interested in, and what kinds of approaches work best for them.

For Kabbage, that means using big data to build “lookalike models” or marketing personas of their customers to shape their digital marketing purposes, Nalbone says. In addition, the company uses big data analysis to understand the effects of one marketing channel on another. “We’re constantly finding ways to find not just the most customers but also the best customers,” he says. “We make changes and iterate based on insights from the data, but then you need to test those changes as you generate more data to make sure that your predicted outcome really does manifest itself.”

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