Page 17 - Banking Outlook 2014 - An Industry at a Pivot Point

Banking Outlook 2014: An Industry at a Pivot Point | 15

An ocean of water, but not a drop to drink. That image of a lost-at-sea sailor is an extreme,
but not wholly unfair, analogy for banks, which have oceans of data about their customers
but shockingly few insights into what to do with it. Of course, banks use data to manage
risk, but as they pivot from risk-mitigating defense to revenue-generating offense, banks
must make better use of data to understand their customers and provide to them the
products and services they want via the channels they want to use. Yes, most banks
already use customer data from time to time to decide which products to market to which
buyers—products like checking accounts, investment products, credit cards, mortgage
refinancings, and home equity loans. But far too infrequently are they using customer
data to create truly new products or services that leverage the information banks have on
file about their customers, either individually or collectively.

Improve Data Analytics

Partly this is a problem of history; banks are accustomed to viewing data as a cost center; something to
be saved, but seldom used. Partly it is a problem of priorities; especially over the past several years, much
of the analysis banks have engaged in has been targeted at meeting risk-management imperatives. But it
is partly a problem of capabilities also. With so much customer information available—in the bank’s own
records (credit and debit card data, demand deposit data, loan data), in credit reports, from social media,
and from an array of resources that seem to be growing exponentially—banks have simply struggled with
where to begin. As one of our colleagues recently wrote, faced with big data, banks need big knowledge
and big perspective. They need the clarity that comes from an organizational capability to leverage data
in many forms, from many places, through many methods and for a variety of purposes. Yet in one of
16
The KPMG name, logo and “cutting through complexity” are registered trademarks or trademarks of KPMG International. NDPPS 227982
KPMG LLP’s (KPMG) recent surveys, only a third of respondents said their banks had a high degree of data
17
© 2014 KPMG LLP, a Delaware limited liability partnership and the U.S. member firm of the KPMG network of independent member
firms affiliated with KPMG International Cooperative (“KPMG International”), a Swiss entity. All rights reserved. Printed in the U.S.A.
and analytic literacy. Not surprisingly, they also said they need to get better if they want to make progress on
growing revenues.
Indeed. But front-line analysts won’t be able to pull this off on their own. For banks to make real progress
in data analytics, executive leadership will have to make it a priority, champion its benefits, and, most
importantly, allocate the necessary resources. To drive best results, executive leaders should make sure
their teams hew to these principles:
• Focus on business outcomes and critical goals, and then determine the information needed to achieve
them.
• Locate, access, and improve data quality so that it can be trusted and useful.

• Develop systems and capabilities that aggregate data across business lines to create a single view of the
customer. 18
• Overcome internal obstacles by managing, measuring, and compensating employees, at least in part, on
how well they use data to make decisions and drive business outcomes.
Banks that develop an infrastructure allowing them to analyze data quickly, that staff up to do that work, and
that make revenue-oriented analytics part of their culture, are the banks most likely to grow their top lines.

16 “Big Data + Big Analytics = Big Opportunity,” by Jeanne E. Johnson, KPMG, in Financial Executive magazine, July/Aug 2012.
17 KPMG 2013 Banking Outlook Survey
18 “The Trouble with Banks’ Risk Models: Q&A with the Chief of SAS,” by Penny Crossman, American Banker magazine, 3/28/13