If you ask banks, big data analytics in finance is a big deal. In a recent IDC survey, 28 percent of banks listed big data and analytics as their top investment priority for the coming year. The top reason for that investment focus is to better understand and target customers.
Like retailers, banks and credit unions recognize the importance of customer retention and loyalty. By using big data analytics in finance, these institutions are taking a more proactive approach to gain a deeper understanding of their customers. Here are three ways financial organizations are using big data and analytics to know their clientele better and to protect their financial assets.
One bank customer may have both a personal account and a business account. The same customer may be looking to refinance a mortgage and also open up a business line of credit. This one individual may also be exploring how to pay for a child’s college education as well as preparing for their own retirement. In far too many financial institutions, the customer data gathered about these different activities lives in silos. Separated data and siloed customer information means the bank holds multiple views of a customer, and not one of them is coherent or paints a complete picture. With the right underlying big data architecture, banks, credit unions, and other financial institutions can form a single view of their customers.
When data silos are eradicated, a more complete picture forms, and every single interaction the customer has with the organization is indicated. The purpose of this view is to reduce friction. Your customer should have a seamless experience, no matter where or when an interaction takes place. When employees access customer information, they should see the entire history of that customer relationship. This conveys a sense of customer care that resonates. This is how customer loyalty and retention is fostered.
Banks and other finance sector businesses are taking cues from the retail sector when it comes to refining the customer experience. Consider just a few of the retail innovations sparked by digitization and big data: offers based on geolocation data, tap-and-go payments, and product suggestions based on purchase history. Retailers recognized the inherent value of data early on. They have applied that knowledge to personalize customer offers and to predict future steps in their customers’ buying journey.
Consumers expect the retail outlets they patronize to work this way, and many now want a similar level of service from their banks. This infographic highlights that shift. Survey data shows that 45 percent of bank customers want their bank to show them deals and discounts, 40 percent want more personalized service, and 63 percent will share information about themselves so they can receive information about products and services that are relevant to them.
Banks and their customers appreciate the digitization of financial transactions, while also recognizing that it opens up new opportunities for fraud. Fortunately, the finance sector has information at its fingertips that plays a huge role in fighting financial crimes: customer transaction data. Banks know a lot about how, where, and when customers access their accounts. They know which devices they use. They know the shops they frequent. They can tell how quickly they input account passwords. Empowered by big data architecture, these data points create a “signature” unique to the individual customer. That signature makes anomalies easier to spot. Through the use of big data analytics, companies can dramatically improve their financial fraud prevention. These capabilities offer multifold benefits: Customers are happier their assets stay protected, banks are happier to stop crime, and shareholders are happier supporting brands that don’t appear in headlines about data breaches.
Banks, credit unions, and other finance sector businesses hold a treasure trove of consumer data. Investing in big data and analytics capabilities can help make the most of every customer interaction by using that knowledge to better serve their customer base.
To learn more about the use of big data analytics in finance, download this white paper.