Post on 13-May-2018
How Data Fuels Banking’s Digital TransformationData is the crude oil of the digital economy. When refined with predictive analytics and modeling techniques, data can power personalized offers that boost customer loyalty, create upsell and cross-sell opportunities, and generate greater share of wallet.
2 KEEP CHALLENGING February 2016
Digital is reconfiguring the world. From
the advent of the commercial Internet,
technology advancements have made our
day-to-day lives more virtual and global.
Smart, always-connected devices and
anytime/anywhere communications and
interactions are now a given, particularly
among millennials, who expect such
conveniences in their banking and financial
services relationships.
Data underpins digital’s disruptive promise.
Combined with predictive analytics, hardware
and connectivity, data opens the door to
breakthrough insights through Code Halo™
thinking, which uses the digital persona of
customers to develop new offerings, guide
them to relevant and enabling information,
improve service and anticipate future customer
needs.1
An example is JPMorgan Chase & Co., which
analyzed 12.4 billion debit and credit card
transactions to explore the factors shaping local
consumer commerce. The research revealed a
dramatic slowdown in the growth of everyday
consumer spending from 2014 to 2015, a
valuable insight for shaping financial services
strategies and offerings.2
Companies large and small can gain distinct
advantage by using analytics to look at the
same data as their competitors do, in order
to uncover new patterns and insights. They
can then develop differentiating business
propositions that lead to disruptive products
and services. Consumers can also get into
the insights game by selling their anonymous
data through Datacoup, which analyzes it
and provides the insights to companies.3
Data provides not only customer intelligence
but also insights into the workforce. Credit
Suisse Group and Walmart Stores, Inc. are
among the companies that are analyzing
factors such as job tenure, performance
reviews and communication patterns to
identify employees with a high likelihood of
leaving for another job.4
More Tailored Offerings Across industries, organizations have always
collected and stored data on customers,
suppliers, products and services. Today,
traditional enterprise and market data is being
combined with big data (i.e., interactional
data) and third-party-supplied data that, for
example, adds demographic and geospatial
inputs. In addition, an emerging trend is
the push for “fast” data – making the most
pertinent information available in real time at
the point of engagement or interaction.
Using smart algorithms, analytical tools and
frameworks, businesses can uncover insights
from these disparate data sources, providing
the basis for action. When a large global bank
built a “propensity to save” model to predict
customer interest in savings-related offerings
and increase cross-selling, for example, the
model pilot produced a tenfold increase in
branch sales and 200% growth in conversion
rate over a two-month period.
HOW DATA FUELS BANKING’S DIGITAL TRANSFORMATION 3
Uncovering the meaning in data patterns sets
the stage for conducting predictive analytics.
The ability to influence behavior in a way that
it becomes predictable or can be anticipated
before it happens can inform the development
and configuration of products and services.
Like Facebook and
Google, financial
institutions can
create constructs
that tap the
i m a g i n a t i o n
of millions of
people, leveraging
the power of
information, algorithms and technologies to create
contextualized and personalized experiences.
Data can help point the way to decisions and
actions in various situations, such as pitching a
particular product to a customer at a certain time
in a specific contextual situation.
A pioneering global financial services company
harnessed the anonymous transactional data
of its charge card customers and developed
personas based on their buying habits and
interests. In partnership with merchants,
the company feeds the real-time analytics
into dynamic predictive models and pairs it
with geolocation and mobile data to create
merchant-funded personalized offers to
customers.
In-market signals can help drive bank strategies,
too. Within data privacy limitations, an institution
can comb the Web, the social Web, apps and
other online and offline data sources for
information, such as who is browsing for a home
or car. Mapping this group to its customer base,
the bank can make targeted offers to customers
who could be in the home or auto market in the
next 30 to 90 days.
Armed with this information, the institution
can work proactively to not only offer the right
financial product at the right time in the right
place, but also reinforce customer loyalty by
delivering a meaningful experience. Taking a
“next best action” – presenting a compelling
offering even if the customer hasn’t asked
for it – can lead to additional upsell and cross-
sell opportunities that fuel greater wallet and
market share.
In addition to uncovering what customers
want, data and analytics can help determine
whether a financial services provider wants
an individual or organization as a customer.
Lending Club, for example, looks at diverse
factors when it assesses whether a customer
is risk-worthy, including how fast and at what
time of day loan seekers fill out an online
application and the makeup of their social
media friends list.5
Contending with Data’s Dark Side
When fraud occurs, a bank can expect to put
considerable effort and resources into bringing
the perpetrators to justice and recovering the
funds, sometimes to no avail. Predicting and
preventing fraud — rather than acting after it
happens — can potentially mean big savings for
The ability to
influence behavior in
a way that it becomes
predictable can inform
the development
and configuration of
products and services.
a bank. Leveraging the power of data and using
the right tools, analytics and algorithms, banks
can do just that in some situations. HSBC has
improved fraud detection, false positive rates
and fraud case handling by monitoring the use
of millions of cards in the U.S.
Fraud can be attempted from both inside
and outside the institution. To address the
internal threats, a bank can establish data and
algorithmic mechanisms to monitor employees’
on-the-job activities for compliance with its
code of conduct, policies and procedures.
Steps to Capture the Power of Data
Banks can take several actions to capitalize on
the wealth of data available to them:
• Use data to support high-impact, top-down
initiatives that drive change, break down
silos, create more information-sharing and
ultimately evolve to “capture one and done.”
• Enhance data management and decision-
making by investing in smart algorithms,
predictive analytics and advanced tools,
such as speech analytics.
• Explore organizational redesign and new
operating models, including establishing
or strengthening the role of the chief data
officer.
• Strengthen the organization’s data science
proficiencies and commit to creating a data
scientist function. Such a function could be
filled by a team of behavioral scientists who
can help convert raw data to information,
insights and foresights that inform next-best-
action activities and strategies.
Data’s Vast Opportunities
Banks are uniquely positioned to apply Code
Halo thinking because they already own data on
enormous numbers of transactions and track
the money movements of their customers. This
powerful advantage can help create an institu-
tion for the future by leveraging data’s power
through the application of smart algorithms
and predictive analytics. This will enable a bank
to quickly and effectively transition from just
“doing digital” to being a digital organization.
For more on this topic, please view our video
https://www.youtube.com/watch?v=MZicWFx5H_k
4 KEEP CHALLENGING February 2016
About the Author
Footnotes
Prasad Chintamaneni is President of Banking and Financial Services, leading Cognizant’s largest industry business unit globally. As global lead since 2011, he is responsible for the business unit’s global P&L, including sales, business development, consulting, client relationship management and delivery. Prasad joined Cognizant in 1999 and established key relationships with many of the company’s largest banking and financial services clients, while leading the U.S. Eastern Region Banking and Financial Services Practice through
2006. Prior to joining Cognizant, he spent seven years in investment banking and financial services, including the last five years with Merrill Lynch as an investment banker and as a member of Merrill’s business strategy committee in India. He earned his postgraduate diploma in business management from XLRI School of Management in India, following his bachelor of technology degree in chemical engineering from the Indian Institute of Technology, Kanpur, India. He can be reached at cprasad@cognizant.com.
HOW DATA FUELS BANKING’S DIGITAL TRANSFORMATION 5
1 Code Halos are the digital information that surrounds people, organizations and devices. By making meaning from this data, businesses can create unprecedented insights and improve their competitive edge. For more on Code Halos, see our website, https://latestthinking.cognizant.com/code-halos.
2 “Profiles of Local Consumer Commerce,” JPMorgan Chase & Co., December 2015, https://www.jpmorganchase.com/corporate/institute/document/jpmc-institute-local-commerce-report.pdf.
3 Datacoup website: https://datacoup.com/.
4 Rachel Emma Silverman and Nikki Waller, “The Algorithm That Tells the Boss Who Might Quit,” The Wall Street Journal, March 13, 2015, http://www.wsj.com/articles/the-algorithm-that-tells-the-boss-who-might-quit-1426287935.
5 Jonathan Marino, “Here’s How Online Lenders Figure Out Whether You’re a Good Borrower,” Business Insider, Oct. 20, 2015, http://www.businessinsider.in/Heres-how-online-lenders-figure-out-whether-youre-a-good-borrower/articleshow/49473967.cms?r=US&IR=T
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