Banks Use Big Data To Understand Customers Across Channels

Several large U.S. banks are using big data primarily to understand how customers use their different channels, such as branches, online, mobile, call centers and ATMs, according to a recent study by Thomas Davenport and Jill Dyché at the International Institute for Analytics working with SAS Institute.

Entitled “Big Data in Big Companies,” it included looks at health insurance, retailers like Sears and Macy’s  and industrial firms such as GE, UPS and Schneider trucking. In finance, the firm interviewed Wells Fargo WFC -0.10%, Bank of America BAC -0.34% and Discover.

Those finance firms are “using big data to understand aspects of the customer relationship that they couldn’t previously get at. In that industry as well as several others, including retail the big challenge is to understand multi-channel customer relationships,” the report noted.

“They are monitoring customer ‘journeys’ through the tangle of websites, call

centers, tellers, and other branch personnel to understand the paths that customers follow through the bank, and how those paths affect attrition or the purchase of particular financial services.”

The data they are looking at is structured and semi-structured and include website clicks, transaction records, bankers’ notes and voice recordings from call centers. The study said that the banks are getting better at understanding common journeys, monitoring for quality of service and identifying reasons for attrition.

Before big data was tamed by technology, Bank of America took the usual approach to understanding customers — it relied on sample. Now, “with big data technology, it can increasingly process and analyze data from its full customer set.”

The bank is using transaction and propensity models to determine which customers have a credit card or mortgage that could benefit from refinancing at a competitor and then makes an offer when the customer contacts the bank through online, call center or branch channels.

“The various sales channels can also communicate with each other, so a customer who starts an application online but doesn’t complete it, could get a follow-up offer in the mail, or an email to set up an appointment at a physical branch location.”

Bankers have been talking about this for a long time. Some of the problems have been amassing the data, but some have also been in the bank’s organizations of people and technology. Internet channels didn’t necessarily share information with the call center or branch personnel, for example, and the technology silos both reflected and entrenched fiefdoms. (See my recent story on KeyBank which created a central analytics organization and had direction from the CEO down to break through fiefdoms.

Bank of America has also modified its structure to make big data more effective, the report said.

“The bank has historically employed a number of quantitative analysts, but for the big data era they have been consolidated and restructured, with matrixed reporting lines to both the a central analytics group and to business functions and units. The consumer banking analytics group, for example, made up of the quantitative analysts and data scientists, reports to Aditya Bhasin, who also heads Consumer Marketing and Digital Banking. It is working more closely with business line executives than ever before.”

Bank of America can now run BankAmeriDeals with cash-back offers to holders of credit and debit cards bases on analyses of where they have made payments in the past.

Interesting that while a lot of big data talk is about unstructured data or social media analysis, banks seems to have plenty of work just to understand the mostly structured data they already have and generate daily.

資料來源：Forbes