Disrupting the Banking Industry with Big Data and Data Analytics

Banks have lost their way in the current deflationary, low interest rate environment worldwide. What could save the industry is Big Data and Data Analytics. Can yesterday's bankers make the transition or will a new crop of bankers emerge?
 
 
- Is Data worth more than Cash to Banks? -
- Is Data worth more than Cash to Banks? -
NEW YORK - Nov. 15, 2013 - PRLog -- Bankers seen sipping away the hours over client martini lunches at upscale restaurants and posh clubs are rare these days. The slump in credit demand from the global economic crisis is part to blame but so to is the absence of 'live' clients. Branch offices that were once community hangouts on payday look more like empty office spaces for lease. Today bank clients 'hangout' virtually, while doing most of their banking online. They lurk in and out web-based services unwittingly leaving behind hundreds of data points (like footprints) that when reconstructed using data analytics algorithms can accurately reveal the client’s real identity.

At a first-of-its-kind event in Atlanta,Georgia titled, Customer Insights & Analytics in Banking Summit 2013, representatives from various forward-thinking banks and data-analytics service companies presented their combined views to a packed room of financial professionals. Organized by Data-Driven Business (datadrivenbiz.com), a US arm of FC Business Intelligence (a London-based events company), the Summit personified the past, present, and future of banking.  First, it exposed the ugly truths characteristic of a complacent banking culture mindset.  Then it highlighted the extraordinary accomplishments from early-adaptor banks, and, finally, it unveiled a fantastic prediction on how banking could potentially hold the keys to unlocking the value of social media feeds from Twitter, Facebook, and other similar web-based services.

With off-the-shelf, data analytics, software tools, bankers can gain an accurate 360 degree view of their customers on an individual basis just by matching a customer's banking data (i.e. loans, credit card purchases, investments) with their behavioral patterns online. The technology used to integrate data sets to match behaviors with individual names has advanced remarkably, so much so, that bankers can calculate with reasonable accuracy the 'lifetime value' of each customer. This magical step has been demystified by over 150 vendors who specialize in the science of Digital Data Integration or DDI. DDI connects numerous disparate data sets both structured and unstructured using assigned ID numbers. Expert companies in this area include Aster (asterdata.com (http://www.asterdata.com/), a TeraData Company), Actian (actian.com (http://www.actian.com/)), PrecisionDemand (precisiondemand.com (http://www.precisiondemand.com/)), Convergence Consulting Group (convergenceconsultinggroup.com (http://www.convergenceconsultinggroup.com/)) and Actuate (actuate.com (http://www.actuate.com/), a BIRT company). The principle reason bankers want to segment their customers by their future income potential is to allocate their limited resources more efficiently.

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Tom Kadala
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Tags:Banking, Big Data, Data Analytics, Unstructured Data, Transactional Data
Industry:Banking, Research
Location:New York City - New York - United States
Subject:Reports
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