I know it sounds ludicrous, but there are banks which indeed process several thousand transactions per second! Blink. The counter notched up another 5,000 transactions. Oh wait, that’s an additional 20,000 in the time you took to read this sentence.
Welcome to the reality of Big Data, which is growing at a scale that is almost unreal. Being part of a highly information intensive business, banking institutions are among Big Data’s biggest stakeholders. So the fact that most banks process the bulk of their Big Data offline, outside of real time, by which time another million events have gone by, is most perplexing.
Sure, there are “good” reasons for this, including systemic inadequacy and the seeming impossibility of mopping up data as it occurs, from a myriad of channels. But they don’t matter. What does matter is that the lack of online real time intelligence is denying banks several advantages – agility to respond faster to changes in customer behavior; deeper insights into operational, customer and counterparty risks; the ability to test and fine-tune marketing campaigns; optimized mapping of customer type and communication channel; proactive fraud management; and higher operating efficiency.
A few banks have seized the initiative by deploying high-performance analytics solutions, which act in real time on their Big Data. There’s a Minneapolis-based bank, which uses analytics extensively to identify changes in customer behavior, and leverages that insight to sell more or prevent attrition. First Tennessee Bank uses customer analytics to test assumptions and build product propensity models. It also uses predictive analysis to forecast revenue and Return on Investment on marketing campaigns before putting them out to market. A retail bank in South Africa uses customer analytics to improve debt management and collection. And another U.S. institution has dramatically reduced fraud at its branches with the help of facial recognition technology and video/ customer data analytics. Way to go!
