4 Banking Analytics Trends Driving the Financial Industry

By: Kaylie Gyarmathy on July 17, 2020

For many organizations, data has become their most valuable resource. In the financial services industry, in particular, big data has opened up a world of opportunities and delivered a number of clear benefits to customers. To better understand how banking analytics are driving the industry, it’s important to first understand a bit more about how big data works in practice.

What Are Banking Analytics?

In the simplest terms, banking analytics refers to any technologies used to gather, process, and analyze complex data sets that consist of both structured and unstructured data. This information consists of data gathered from a variety of sources and can potentially contain a wealth of valuable insights. Analytics software can sort through this “big data” to identify trends and other patterns that might influence key business decisions.

Any one piece of data, then, is less valuable than what a large number of data points can collectively tell an organization about the market and consumers. Processing big data is very resource intensive, requiring powerful servers capable of running the machine learning analytics software that has the capacity to adapt to trends and draw connections between unstructured, messy datasets.

How the Financial Industry Uses Big Data

It should hardly be a surprise that the financial services industry was quick to adopt big data analytics as part of its strategic planning efforts. Being able to identify trends in the market before the competition provides firms with an obvious advantage, allowing them to move faster and plan farther ahead.

The banking industry, in particular, is awash with customer data. Thanks to ATMs, mobile banking apps, payment processing services, and online banking portals, banks have been gathering massive amounts of data that goes back several years. If anything, the industry has been struggling to manage all of that information and derive useful benefits from it.

That’s why the banking industry has made massive investments in big data over the last decade. There are a few key areas where analytics trends are changing the way banks position themselves in the marketplace.

4 Banking Analytics Trends Worth Watching

1. Improved Sales and Marketing

Banking analytics have already shown incredible value when it comes to directing marketing and sales efforts more accurately. They can show which strategies generate the greatest ROI and make it possible to segment the marketplace into much more manageable categories that are easier to manage. Banks often have data that shows where to best reach certain demographics (such as people who use mobile apps or frequent certain stores), and they can use predictive analytics to determine when those people can be best reached with marketing campaigns. Once prospects transition to the sales team, big data makes it much easier to identify which sales tactics are effective and which ones are likely to push certain leads away. Data can also make cross-sell and up-sell opportunities more apparent, allowing banks to bundle services and provide greater benefits to customers to keep them coming back.

2. Better Customer Support

Nobody likes being on hold for long periods of time waiting to be transferred to someone who can actually address their problem. By gathering data on what types of issues customers are encountering and what they need when they contact customer support, banks can create a more effective user experience that resolves problems quickly and with minimal friction. Data might show, for instance, that a large percentage of calls to customer support could be handled by an automated system or a new feature on a mobile banking app. Cultivating a better user experience when it comes to customer support will improve retention and help people resolve their problems faster so they can get back to using the banking services that support their business or lifestyle.

3. Enhanced Security

Fraud and identity theft are always major concerns for banking customers. They want to know that their bank is doing everything possible to identify unauthorized spending and detect potential fraud. Big data analytics allow banks to create a profile of typical customer behavior, which allows them to identify and flag unusual activity that could be an indication their account is compromised. For instance, a series of big-ticket purchases could trigger a notification or even lock down an account until the bank can verify that the customer did, in fact, make those purchases. Enhanced security backed by banking analytics protects both customers and the banks themselves since dealing with chargebacks and fraud claims is often a complicated and time-consuming process that leaves everyone frustrated.

4. Improved Products and Services

Gathering information on how customers are using banking products and services is incredibly helpful for improving those offerings. Thanks to mobile apps, website portals, and devices that can be continuously updated, banks can analyze data to determine whether or not those applications are meeting people’s needs. Smartphone banking apps, for example, have undergone a great deal of change since they initially debuted. While early incarnations of these tools were often clunky, unintuitive, and designed according to what banking professionals and engineers thought people needed, years of data have show how people actually want to use them. Certain features that were seen as essential turned out to be unimportant for customers, while the functionality they actually wanted was buried beneath a series of unintuitive menus. Identifying these trends in the data with banking analytics helped financial service organizations to create more user-friendly products that people actually want to use.

Making the Most of Banking Analytics with a Data Center

The main challenge of leveraging big data, of course, is securing access to the computing power necessary to process it and identify meaningful trends. While major banks typically have substantial computing resources, many smaller financial institutions don’t have the enterprise-grade infrastructure capable of handling the demands of big data analytics software.

Fortunately, colocation data centers can provide both the scalable storage needed to gather and manage big data and access to the processing power needed to analyze it effectively. Thanks to direct cloud on-ramps, colocation customers can rapidly scale their processing needs by connecting to the expansive power of public cloud providers. Essential data can be kept safely on private servers, while a hybrid IT environment can be used to securely connect that data to big data applications running in public cloud instances.

As an award-winning colocation provider, vXchnge delivers rock-solid, reliable infrastructure and provides ready access to the world’s leading cloud providers through low-latency interconnections. For organizations in the financial services industry, that means being able to meet their compliance and storage needs without sacrificing the expansive power of cloud computing used for banking analytics. To learn more about how vXchnge can help financial services companies leverage the power of colocation, talk to one of our data center experts today.

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