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TIBCO Spotfire's Business Intelligence Blog


Big Data for Better, Faster Retail Banking Decisions

As more retail banking companies embrace the challenge of applying data analytics to their internal processes, they see more clearly the immediate and long-term benefits worth pursuing.

shutterstock 9203965 300x222 Big Data for Better, Faster Retail Banking DecisionsIf you’re in the retail banking industry here are some reasons you should get into the big data game, if you haven’t already.

Ninety-six percent of executives in the C-suites of leading Wall Street firms report having big data initiative planned or in progress, with 80% reporting they have at least one initiative completed, according to a survey by NewVantage Partners.

And 87% of executives report that accelerating time-to-answer (TTA) and the need for better analytics are the main reasons they’ve turned to big data investments, according to the NewVantage survey.

As a retail banker, your TTA statistics and getting data into the hands of business analysts immediately can have profound effects on the health of your customer service and financial service offerings.

Don’t quite see the applications yet? Imagine being able to analyze risk data in three hours rather than three months, or pricing calculations in 20 minutes rather than 48 hours.

When it comes to fraud and sanctions management, what if you could analyze behavioral analytics in 20 minutes instead of 72 hours? This increased access to data and the speed of that access will offer unprecedented improvements to the retail banking industry.

Specifically, big data and big data analytics can help retail bankers move away from the one-size-fits all approach to the customer experience, according to Dean Nicolacakis, a partner at PwC’s banking and capital markets practice.

“Of course, you need a foundation based on good maintenance, not making mistakes in customers’ accounts, etc. But once you provide that minimal level you need to provide some nuance to the experience. You need to ask what differences there are in what customers want?” Nicolacakis notes.

And big data is the key to understanding what different customers want from their banks, according to Nicolacakis.

“By collecting and analyzing all of the data that banks have available about their customers, they can then group those customers into different segments based on their expectations and banking needs,” so they can take a more segment-oriented approach to the customer experience, he says.

Next Steps:

  • Please join us on Wednesday, March 26, 2014 at 11 a.m. EDT for our complimentary webcast, “Retail Banking & Insurance: Customer Data Analysis.” In this webcast you will learn how leading financial institutions are using customer data to drive superior decisions, improve the customer experience and make the most of their marketing budgets.

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