Leveraging Big Data for Community Banks
For some community bankers, big data brings to mind stacks of customer data pasted together like a kindergarten art project. Yes, your customer relationship management (CRM) system captures lots of information, but that information oftentimes sits unused. Is it important that you know Mary Smith comes into the bank at least once a week to deposit a check? Yes. Does it help to know that she uses mobile banking to check her balance? Yes. Is it valuable to know that she is carrying a high interest rate auto loan with your competitor? This is invaluable.
Forbes defined big data as “a collection of data from traditional and digital sources inside and outside your company that represents a source for ongoing discovery and analysis.” Sounds downright pleasant, right? For banks, the ongoing discovery centers around the options to get to know account holders better through their information, build long-lasting relationships and improve bank profitability. And it turns out that the key to this could be the information housed within personal financial management (PFM) platforms.
Whether it is confusion surrounding its definition or one of the myriad of other misconceptions around big data that is keeping the financial industry from tapping into this game-changing resource, this is the time for banks to begin effectively leveraging big data for big results. Here are three areas where community banks should focus in order to use data to improve customer relationships, build wallet share and better compete with larger institutions:
Data Access. The first step is understanding that the information community banks need for success is already available to them. With advances in today’s technology, many community institutions now have the same resources to access and interpret data as the mega banks do. The key is finding a way to efficiently access and utilize account holder data that will benefit the bank.
One way to get essential customer data is by using a PFM platform to access data from users’ internal and held-away accounts through aggregation. A PFM platform provides a convenient place for customers to link all of their financial information both from the bank offering the solution and from outside sources. Analytics software, working with PFM data, then allows the financial institution to mine the applicable data to gather insight and draw actionable conclusions from the most important elements of a customer’s financial life.
Data Management. Not only are technology advancements in PFM and other areas providing a convenient way to access data, they are also offering an efficient way to manage it. Though big data isn’t as intimidating as some might think, it can be housed in formats, systems and infrastructure that can make it difficult to summarize and manage. Also, the sheer volume of information can make it difficult to handle — a trend that won’t be slowing down anytime soon with a CSC study predicting that data production will be 44 times greater in 2020 than it was in 2009. To manage the vast amount of data efficiently, it is vital to integrate PFM technology with back-end analytics software that enables users to cut and slice data without elaborate IT departments or complex equations. With the right partners, community banks can crack the big data code through technology that enables them to quickly access, visualize, filter, control and store customer-specific data sets.
Using the Data. The back-end analytics software is just as important as an easy-to-use interface that helps bankers translate and use the information. Big data will continue to be underutilized if a PhD in statistics is needed to analyze it. The correct approach is a simple interface that enables any executive to access, interpret and leverage available data in advancing the bank’s overall goals.
Along with presenting data in simple interfaces and data visualizations, the user experience should provide means for executives to customize data sets in order to quickly act on available information. This is especially valuable when it comes to marketing efforts, where the right interface will allow bank marketers to use data analytics in creating customized marketing messages and offers that can be targeted and sent directly to specific customer groups.
Once executives are armed with customer data analytics from the PFM, they can then target account holders with customized marketing messages and offers that will allow them to both strengthen relationships with customers and build wallet share. For example, say an institution has a customer that currently uses its PFM and holds a low balance checking account with them, but does not use the bank for any other financial services. Through access to all of the account holder’s financial data in the PFM, the institution can see that the customer maintains an auto loan with a competing institution and is paying an excessive interest rate. The bank can then help the customer save money by offering a lower auto loan rate and solidify the relationship.
Big data has promised huge potential to the financial industry, but lack of research within the industry and misconceptions surrounding its usefulness have created a hesitancy to give it a chance. When used correctly big data can revolutionize marketing within the financial industry.