core_#5_Big Data_Analytics_DIGITAL

FINANCIAL SERVICES
FUTURE: BIG DATA & ANALYTICS
CASES & FACES
DATA ANALYTICS
Make actual money with data
IT INFRASTRUCTURE
No more excuses

It’s not a hype,
but the future of banking
DATA ANALYTICS HAS BECOME PART OF DAILY LIFE
Customers appreciate digital convenience. The success of all the “Googles” and “Amazons”
has proven it: customers are willing to pay for it with their data.
TECHNICAL SOLUTIONS ARE EASILY ACCESSIBLE
Cloud services provide almost unlimited storage capacity and offer analytics modules as
well as compute capacity. This is one of the reasons why IT is no longer the limiting factor.
BIG DATA NEEDS STRATEGY AND GOALS
Comprehensive knowledge, reasonable usage scenarios and effective approaches matter:
data analytics does not make things automatically better, just different.
FORM FOLLOWS FUNCTION
Define the strategy first, then identify requirements and finally select the appropriate tools.
The analytics strategy is a closed loop.
THINK BIG, START SMALL
The starting point is a structured approach including a status quo analysis, a target image
and individual use cases. Thus, the long-term vision (“think big”) is broken down to exploratory
prototypes (“start small”).

Welcome
to core
During the Cold War, American banks and authorities were good
customers of Mosler Safe Company. The Ohio-based enterprise
built gigantic steel doors for vaults—said to be ”ready to
withstand nuclear bombing” as several Mosler safes at Mitsui
Bank had resisted the attack on Hiroshima.
In recent years, financial services providers have been faced with
the dilemma of not only fulfilling high security standards but also
meeting the customers’ wishes for transparency, convenience,
openness and service. After all, people have swapped their hard
currency for cards and online banking in cashless payment
transactions.
wishes who entrust a financial services provider with their entire
financial and personal time line. They do not only demand
security, but a holistic service in particular. The image of a
locked safe as the synonym for banks is fading. Networking is
the new paradigm.
We hope you will enjoy the read.
When payment instruments and investments are transformed
into data, we need financial services providers who aggregate
useful services for all aspects of customer data and use them
intelligently, individually and at the right time.
Professional processing of different data is the key to generating
new values, since it is the basis for innovative technologies such
as distributed ledger, mobile payments, augmented reality,
financial platforms and artificial intelligence.
Big data & analytics is not a necessary evil for banks, but gains
a footing for their economic future. The “21st century oil” needs
to be discovered, extracted and refined—the value chain will be
reforged.
In this Core issue, you will find answers to the most important
questions on big data & analytics as well as the latest case
study of an established financial services provider in this area.
Between the lines, the constant appeal resonates to take
customer needs very seriously.
Carsten Werner, Senior Manager
carsten.werner@zeb-consulting.com
Sebastian Brecht, Senior Manager
sbrecht@zeb.de
FUTURE: BIG DATA & ANALYTICS
Mosler Safe Company also had to learn a lesson: Bank safes are
no longer a unique selling point—today, the focus is on people’s
3

The future of banking
Big data & analytics is a real challenge—and also the way into the
future of banks. The focus is on customer loyalty, sales optimization,
process efficiency and risk control. With the right solution approach
and a proven method, successes can be achieved step by step without
losing sight of the strategic goals.
FUTURE: BIG DATA & ANALYTICS
4
fter ten years, the impact of the financial and
economic crisis can still be perceived: regulatory
requirements, balance sheet and stress tests, a
heterogeneous global economic situation and the low
yields of central banks put institutions under pressure. New
competitors, changed requirements in retail banking and short
technological innovation cycles add up to the situation. The
industry has been in defensive mode for years.
“What is the object of defense? To preserve. To preserve is easier
than to acquire,” the Prussian general Carl von Clausewitz once
wrote. A credo that no longer applies to today’s banks. The wind
of change is blowing so strong that banks require a strategic
redesign rather than preservation.
One reason is the requirement for European banks to increase
the capital base and to sustainably improve profitability. zeb
analyses have shown in this context that efficiency measures
alone are not sufficient to meet regulatory requirements under
current market conditions—let alone the shareholders’ wishes.
Another reason is the bank’s requirement to redesign the interface
to the customer: They demand “digital proximity”—virtually
intimacy—with relevant services anywhere and anytime.
The use of big data & analytics combines both requirements
and leverages desired potentials. The functional scope ranges
from customer interface and process optimization to improved
risk management. Algorithms model the new appearance of the
bank to process customer requirements in real time, to make
services understandable and to monetize offers in terms of
sustainable profitability.
The digital world seems like the land of milk and honey: Map
services navigate us through Castile and also save the address
and price category of the hotel almost in passing. Facebook reminds
us of important events, birthdays and offers of our favorite

Aside from traditional master data and transaction history, modern customer data
also includes location history, Facebook likes or wish lists for online shopping.
Integrating numerous platforms allows for bundling this data and for accessing and
processing high volumes of data with a great level of heterogeneity (variety) almost
in real time (velocity). Here is an example: 400 hours of video footage are uploaded
to YouTube every minute and more than half of the videos are accessed via smartphone.
brands. Amazon makes book recommendations based on our
reading behaviors and those of 100,000 other customers—for
free, anywhere, anytime, without asking.
Perfectly knowing the customers and understanding their
individual needs is the key to income potential—not only for
banks. With every year that passes unused, web companies
set new standards at the interface to the customer and financial
services providers are increasingly under pressure to take
action.
Big data & analytics as a field of work related to collecting,
preparing, analyzing and interpreting (customer) data will be the
core driver for the transformation of banks. Only a comprehensive
understanding of the customer and their wishes enables direct
approaches using personalized offers. Individual marketing,
which is about tailored offers with a high level of efficiency, is the
future of banking.
Potentials are tapped, for example, by cross- or up-selling, optimizing
pricing and regaining migrated customers. Including
data from social media and other online data in the determination
of creditworthiness is also possible and reasonable.
In addition, big data & analytics can be used to collect and
process feedback to optimize products and services. All bank
customers will benefit from these lessons learned—and from
these insights the financial services providers can directly
derive the demand for their offers to specifically allocate
resources.
The development in big data & analytics is a great opportunity
for banks: customers nowadays expect simple, transparent and
secure digital services that add value. In return, they voluntarily
disclose personal information—the seed for the new digital harvest.
Financial services providers only need to plant, water and
use fertilizer as necessary. This applies to the culture, processes
and IT.
FUTURE: BIG DATA & ANALYTICS
5

TRANSFORMATION MILESTONES
As part of digital transformation, banks face five core challenges:
They need to foster the dialog and
interaction with customers and set
incentives so that required information
will be provided.
It is not necessarily the amount of
data that defines the value—it is
about the right questions.
Focusing on actual needs and
priorities of customers is essential
for banks.
FUTURE: BIG DATA & ANALYTICS
6
THINK BIG, START SMALL
As opposed to the high tech pioneers, banks and insurance
companies already have usable information on a large scale and
there is no need to explicitly compile, collect or purchase them.
Besides, IT is no longer a limiting factor despite other common
beliefs. The constantly growing cloud services alone open
up new ways that can also increasingly be taken by financial
services providers. Many institutions have identified the topic,
react and want to face competition. Awareness among top
management has released budgets—ideal conditions to become
a success story.
The challenges of digital transformation often caused first initiatives
to fail or they did not bring about the desired effects.
Implementing isolated technological innovations for their own
sake has never proven to be a success formula. Even a fully digitalized
process not embedded in the environment (goals, infrastructure,
culture) does not create value but effort and frustration
instead. A high level of uncertainty among banks and customers
regarding legal topics such as GDPR adds up to the situation.
Considering the numerous options, many banks cannot see
the forest for the trees and are therefore not able to realize the
desired potential benefits—provided that they had been clearly
defined in the first place. Although it is true that digitalization is
a comprehensive and powerful toolkit, the following still applies:
“Form follows function”. First requirements have to be developed
and then the right tools have to be selected next. Otherwise a
lane is cut through the wrong forest.
A sensible approach therefore requires analyzing the status quo
of the digital maturity level and identifying relevant use cases and
their dependencies for the institution. For example, this could
be achieved by applying integrative approaches such as design
thinking: It can be used to determine which customer data is
actually needed—or which is not—as well as the resulting need for
adaptation of systems, processes and customer interaction.
It is necessary to develop a structured approach including status
quo analysis, target image and specific use cases tailored to the
individual business and strategy. The decisive question is: What

For customers, the information
gathered has to be transformed
into convenient services and thus
stands for flexibility, freedom or
reduced complexity.
Technical support for collecting,
preparing, processing and using
data needs to be ensured.
is the strategic directive? Is it about sales, risk control or process
efficiency? The long-term vision (“think big”) needs to be broken
down to manageable small modules (“start small”) in order to
be able to test them and to control their benefit.
need.” Without the help of big data & analytics, there is no
holistic answer to this question today.
The target image reflects the strategy and includes the service
portfolio’s cornerstones, processes and the basis of the organization,
governance, technical architecture and IT infrastructure.
Only in a next step does the actual implementation and application
begin with prototyping and the rollout of use cases while
customer feedback has to be used for optimization.
The advantages of this approach are both the transparency
and the early achievement of initial results. An early involvement
of customers and joint testing also ensures resource efficiency
in development and implementation. This engenders trust
within the organization for digital transformation, because here
as well it is key that the guiding principle is established in the
employees’ minds: “To be able to think from the customers’
perspective, you really need to understand what they want and
Your contacts
Carsten Werner, Senior Manager
carsten.werner@zeb-consulting.com
Sebastian Brecht, Senior Manager
sbrecht@zeb.de
FUTURE: BIG DATA & ANALYTICS
7

Check-up of data analytics:
“Make actual money with your data”
Data analytics is a key instrument to compete in customer loyalty and market shares.
Sparkassen-Finanzgruppe recognized this trend early on and offered banks a powerful
data analytics platform through FI and S-Rating. For example, more than 30 use cases
were provided in 2018. Conversion rates increased while efforts were reduced as a
result. Still, many potentials remained untapped. zeb experts Christian Schäfer and
Carsten Werner know why banks should integrate data analytics into their entire value
chain and how to do this efficiently.
What is the current implementation status in banks?
CHRISTIAN SCHÄFER: One has to admit: The initial euphoria has vanished due to high expectations
and implementation challenges. About 70 percent of savings banks have meanwhile subscribed to
the use cases, but only few have integrated data analytics into the value chain correctly. Better
models fizzle out if data analytics is not holistically implemented. The desired sales automation can
be realized only in part—solutions for the “next best action” are being developed at the moment.
However, it is essential to make the key success factors and the individual maturity level transparent
early on.
FUTURE: BIG DATA & ANALYTICS
8
What is decisive for successfully using data analytics?
CARSTEN WERNER: Fundamentally, the focus is on orienting the entire value chain towards new
opportunities. Starting with the integration into the business strategy, the task also includes the
definition of the ambition level to be able to measure if data analytics actually achieved the desired
success in the end. In addition, organizational questions need to be clarified regarding employee
skills and, in this case, the suitability of processes in sales management: Do I use CRM and campaign
management in a suitable way? Are my controlling activities aligned accordingly and is my
sales staff able to bring the horsepower to the road? Finally, you need to define the data quality as
the basis and the legal framework.
What does that mean for a savings bank in concrete terms? How would you describe the zeb approach?
CHRISTIAN SCHÄFER: We analyze the entire value chain with a readiness check and determine the
maturity level for each topic field using best practices. Depending on these findings, we derive and
prioritize specific measures together with the client. We definitely benefit from new perspectives that
we can contribute from our data analytics projects and from our long-standing project experience for
the entire field of success factors. The combination of these aspects enables us to provide an objec-

LEARN
ANCHORING IN BUSINESS STRATEGY
INTEGRATION OF BDA INTO
SALES MANAGEMENT
LEGAL REQUIREMENTS
AND ADVERTISEMENT CONSENT
RATIO
EVALUATION OF USE CASES
AND DEFINITION OF THE
LEVEL OF AMBITION
STRINGENT
DATA QUALITY MANAGEMENT AND
USE OF CRM
ESTABLISH SKILLS AND
EMPOWER SALES
DEVELOP
Assessment of the maturity level along the success factors
tive, market-oriented assessment and specific solutions. Through implementing prioritized fields of action
at an early stage, the necessary acceptance and professionalism for data analytics is generated
from the very beginning.
CARSTEN WERNER: Of course, there are many options—the different topic areas should, however,
always be deliberately considered and defined. The desired potentials can only be leveraged if all
pieces of the puzzle fit together. Here as well, the following applies: “Think big—start small.” Banks
should have a vision, but should start with selected use cases. Thus they can specifically learn to
align the organization, convert employees’ reservations into acceptance and then broaden their experience
in the area of data analytics step by step.
FUTURE: BIG DATA & ANALYTICS
Your contacts
Carsten Werner, Senior Manager
carsten.werner@zeb-consulting.com
Christian Schäfer, Manager
christian.schaefer@zeb.de
9

CORE CASE
Getting to the point faster
Hackathons are a proven means to experience practical use cases
within a short time for all stakeholders.
t these programming events that usually take 24 to
48 hours (hack and marathon), different teams try to
find the best solution for a problem, e.g. for
forecasting the amount of damage based on contract
data in the area of car insurances.
Can you turn ideas into complex innovations in just one weekend?
zeb hosted a hackathon for a German insurance company
to evaluate the business potential of new technologies. The
focus was on data analytics—data was available for the use
case, the level of complexity was manageable and the business
relevance was high.
33 percent for liability insurances and 21 percent for fully
comprehensive insurances.
As the ambitions did not remain a mere declaration of intent,
but were turned into tangible results in the end, both the
participants and the members of the boards were captivated by
the success of the hackathon. The event also served as a proof
of concept that members of specialist departments are able to
beat established claim models using data analytics tools in a
short time. In addition, the event clearly underlined the economic
potential of data analytics for portfolio data.
FUTURE: BIG DATA & ANALYTICS
10
As part of the zeb hackathon, three interdisciplinary teams
with six members each competed against each other on the
premises of the insurance company. The core task was to find
appropriate data sources and to develop and parameterize
algorithms. The three teams were each supported and coached
by a zeb expert who was experienced in data analytics models
and the data basis.
After 48 hours, all teams had found ways to compare historical
claims with the forecast of the algorithms on single
contract level. Thus, the existing models could be significantly
optimized: Damage forecasts could be enhanced by at least
20 percent for liability insurances and by eight percent for
fully comprehensive insurances. A reference model developed
by zeb in advance was able to achieve an improvement of
Your contacts
Jörg Bischoff, Senior Manager
jbischoff@zeb.de
Tomas Sebastian Hätälä, Manager
shaetaelae@zeb.de

“Banks can no longer hide
behind IT complexity”
IT organization and culture: business informatics specialist Prof. Dr. Nils Urbach
from the University of Bayreuth about the changes banks need to
implement for all aspects of the digital customer interface.
Prof. Urbach, what are the key IT tasks that banks need to solve as part of
digital transformation?
NILS URBACH: The biggest challenges to me are not technological issues, but rather the organization
and culture. Strongly regulated banks are required to reconcile their traditional world and shining
innovations. At the same time, business and IT need to work much more closely together and resolve
borders in the line. This takes time and requires a different culture with new ways of thinking: one has
to learn that the previously unpopular IT is what makes a difference nowadays—and not traditional
banking.
What is the problem of the cooperation between business and IT?
NILS URBACH: IT is a crucial differentiator, but you need to actually bring the technological horsepower
on the road and develop promising innovations. Many institutions are only aware of the threat and
meanwhile fail to look for new opportunities, to analyze, to implement and to integrate them into their
service portfolio.
Data analytics in particular is where hopes are pinned in digital transformation.
What is the potential behind it?
NILS URBACH: With data analytics, current business models can be optimized, as there surely still is
substantial room for improvements. But each bank needs to think about ways to reasonably expand
the existing business model based on available data and new technologies. The goal is to defend
or even win back the interface to the customer. Today, this can only work out if you understand the
customer and service them individually to increase their level of convenience. After all, digital markets
are characterized by the small number of players with a large market share: “The winner takes it all.”
The rest acts as an infrastructure provider.
One reason for the rather moderate speed of transformation is the high level of
technical challenges caused by IT legacy issues and the lack of skills.
NILS URBACH: Banks can no longer hide behind IT complexity. In the past, only large banks could
afford the latest technologies and skills while nowadays I can start AWS and a Hadoop cluster within
hours. This also empowers small and medium-sized banks and IT is thus no longer the limiting factor.
We have advanced technologically and can do much more than we currently use. In the area of mobile
payment new competitors are already getting ready. Therefore, digitalization initiatives in the labs
finally need to be consistently launched on the market.
FUTURE: BIG DATA & ANALYTICS
11

It’s not a hype,
but the future of
banking.
LINK TO E-PAPER
WWW.ZEB.EU/CORE/BIG_DATA
Publisher zeb.rolfes.schierenbeck.associates gmbh, Hammer Str. 165, 48153 Münster, Germany, www.zeb.eu
Contacts Carsten Werner, e-mail: carsten.werner@zeb-consulting.com, Sebastian Brecht, e-mail: sbrecht@zeb.de,
Editor Andrea Rothländer-Busch, Marketing & Communications, e-mail: publications@zeb.de
This publication has been prepared for general guidance only and does not take into account the reader‘s individual investment objectives or risk tolerance. The reader should not act
according to any information provided in this publication without receiving specific professional advice. zeb rsa GmbH shall not be liable for any damages resulting from any use of the
information in the publication. No part of this document may be reproduced, copied, distributed or transmitted in any form or by any means without written permission from zeb.
© zeb rsa GmbH 2019. ALL RIGHTS RESERVED.