Three Ways Big Data Analytics in Finance Helps Banks
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.
