Big Data and Big Banks: What’s the Big Deal?

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Big data is big news, as businesses of all stripes rush to mine the treasure troves of consumer information that will make targeting their specific products so much easier and more profitable. Big banks are looking to cash in on this new marketing tool, as well -- but the fruits of such a revolution may be a very long way off.

Information right at their fingertips
For banks, the idea of big data seems like a no-brainer. Not only do they have much sensitive personal information obtained through the account-opening process, but they also have access to so much more. If you want to know what a customer's shopping proclivities are, where better to look than at their credit card, debit card, and checking account statements?

So far, however, it has not been so easy. Although banks generate boatloads of data about their customers, they seem at a loss as for how to use it. A recent study by Celent notes that banks should start with their own reams of data before attempting to parse information gathered by outside entities. For example, why not parse data gathered through the aforementioned bank accounts before trying to make marketing sense of social media chatter?

A hefty investment is needed to utilize big data
Another thing that may have held banks back is cost. As many big banks have cut expenses and streamlined operations, that sort of investment may have been seen as too high. Analysts note that it is not inexpensive to collect, store, and scrutinize the type of data that banks typically collect. The technology investment can be sizable, which is probably why the trend is starting with the biggest banks.

The Wall Street Journal reports that Bank of America (NYSE: BAC  ) , Citigroup (NYSE: C  ) , JPMorgan Chase (NYSE: JPM  ) , and Wells Fargo (NYSE: WFC  ) are leading the way in the use of big data, crunching consumer information to discover which of their customers will make the best consumer of additional banking products. JPMorgan is also using analyzed credit card information in conjunction with government statistics to create reports on consumer behavior for some of their clients.

Bank of America, meanwhile, admits to using only about 1% of the 65 petabytes -- each unit of which is equal to 1,000 terabytes -- of information it has on its customers. The bank recently used at least some of this vast amount of data to rejigger its cash management offerings to better suit customers. For its part, Citi has used big data to help its international clients better assess which emerging markets to move into.

Will Big Data help plump the bottom line?
The marketing potential seems endless here, but it will obviously take some time for banks to see some real profits from Big Data analytics. Big banks have already begun, however, and new products to aid them in their quest for more structured data are on the way.

One such platform, Looop, should be available soon. The product, which was created by banking IT specialists, promises to help banks see "granular detail," of customers' credit card use. Once they learn how to use it effectively, banks may find that they need look no further for data than their own backyard. 

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  • Report this Comment On February 18, 2013, at 10:43 AM, HeatherFicarra wrote:

    One such company providing these solutions is my company, Xerox. Our data scientists developed an early warning system for consumer loans using big data technologies and predictive analytics. The technology is able to identify “at-risk” borrowers before they go delinquent so that proactive measures can be taken to prevent delinquency and default, thus significantly reducing delinquency rates.

    Getting back to the topic of the article, there are many sources of big data – traditional sources like transactions and payment history and new sources like social media, weblogs, geolocation, biometric sensors, etc. Using financial services as an example, data is often siloed by financial products (e.g. mortgage, credit cards, student loans, banking, brokerage), and often with separate IT departments and systems, or it’s outsourced. The solution is a holistic modeling approach to analyzing big data (i.e. using all available information – internal and public – to generate predictions).

    Heather R. Ficarra

    Group President

    Financial Services Group

    Xerox Services--

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