1. The evolution of risk management in a
digitally transforming landscape

2. The evolution of risk management in a digitally transforming landscape
As organisations are increasingly
digitalising business processes, they
fundamentally change the way they
operate, interact with outside stakeholders
and are offering their products and
services to their customer. What is visible
to the end-user, the digital front end, is
only just the tip of the iceberg. Less
visible for the user, but arguably even
more critical are changes to their
operating model and the way they
conduct risk management.
What is significantly different in online
digital business is the amount of data
available and the speed and timing of the
interaction with the customer.
Data is a game changer
The transformation to digital processes
is a catalyst for fundamental change
as much more data becomes available
about the customer which the
organisation can utilise. There are several
reasons for this, but the most important
are the ability to combine datasets
more effectively, creating a customer
centric view compared to a traditional
transaction centric perspective. Another
change agent is the collection of machine
or contextual data. The digital footprint
users leave behind, such as IP address,
time of transaction and device used,
when interacting with an organisation
creates a much more holistic view of the
customer which enables an organisation
to offer more tailored services. At the
same time this provides huge potential
for a data driven risk management
approach. For example, Capgemini
Consulting have recently worked with
a major Central Government agency to
build an in-transaction risking capability
drawing from a massive data repository.
In this case a data lake with terabytes of
user log data which is constantly fed with
new data, some of it highly confidential,
showing citizen use of the new online
tax return system. By using powerful
analytics tools the client is able to create
user profiles and dynamic risk rules that
allow the analytics team to anticipate
certain behaviours.
Timing is everything
Where a risk assessment for a
transaction or an individual client was
traditionally done after submission of
information (downstream) the availability
of more data and new technologies
enable risking in real-time (upstream).
A significant benefit of risking in real
time is that additional information can
be requested while interacting with the
user, and all information can be captured
in-session. This drastically reduces
throughput time and inconvenience for
the user, while again maximising the
revenue potential for the organisation.
Going digital enables
organisations to
move from a post
transaction risking
approach to a real-
time quantitative
risking capability.
22

3. The evolution of risk management in a digitally transforming landscape
Why is this new way of
risking relevant?
The new form of risk management (risk
management 2.0) is data driven and in
real-time. This data driven approach
provides a more objective way of risk
management, is more efficient, less
sensitive to error and less subjective. At
the same time real time risking reduces
costs significantly because a transaction
can be investigated before a final
decision, an insurance claim pay out, for
example, is made.
3
How risk management
is changing
There are several obvious differences
between the old way of risk management
and the new way of risking. Where the
organisation used to collect data mainly
via manual processes, data is now being
collectedautomatically.RiskManagement
2.0 happens during transaction and
visualised in interactive dashboards. Also,
because data is captured automatically,
focus is on data analysis rather than
data collection. And finally decisions are
made using probability based risk scores
instead of expert opinions and implicit
decision making.
Data Collection
Data Type
Timing
Visualisation
Supporting Software
Focus Effort
Basis of Decision
Manual
Mostly Qualitative
Post-transaction (downstream)
Static Graphs
Microsoft Excel
Collection of Data
Implicit, Opinion based
Automatic
Mostly Quantitative
Real-time (upstream)
Interactive Dashboards
Analytics Software
Data Analytics
Explicit, Probability based
Manual Automatic
Traditional Risk Management Risk Management 2.0

4. 4
The evolution of risk management in a digitally transforming landscape
What organisations need to
evolve to this new way
of risking
We have worked with several
organisations to help them transform
from a traditional risk management
approach to the new way of risking. The
following points are key takeaways:
1. Start by defining risking
capabilities needed from a
business perspective. In many
organisations the technology is
leading the transformation as new
technologies enable new use cases.
However risk management needs
to be business driven. The preferred
approach is to start with capabilities
and identify what technology is
available to support this.
2. Early involvement of the end
users. To truly understand the
processes organisations need to
bring together the end users, risking
specialists and technology experts.
Capgemini worked with a
Government Department to help
them understand their current
transaction risking capabilities, help
them identify best practices and
build the roadmap to expand these
risking capabilities. Capgemini
helped the Department build a
vision and identify the priorities
aligned with the ambition level. Key
learnings were to agree a common
understanding of key concepts from
the start and let the ambition level
and business case drive activities
and technology investment.
3. Start with non-critical services
first. To test the processes and
technology an organisation needs
to work with actual customers and
data to learn and improve. Starting
with non-critical services will identify
errors and enable the organisation
to resolved these before scaling to
large and critical volumes.
4. Take an agile approach. Iteration
and the application of quick learning
cycles are essential in successfully
developing new risking approaches.
A planned, but often rigid approach
will not work if the risking model
needs to be tweaked quickly based
on new information.
5. Learn from others. Many
organisations are moving large
parts of their business to digital and
turning towards data driven risk
management. As a consequence,
adoption of risk management 2.0
principles is on the rise. Sometimes
solutions and best practices are
available to quickly process ones
capabilities.
Jelger Groenland is a Cyber and
Digital Risk Management Consultant in
Capgemini Consulting’s BTI practice and
based in London, UK.
Jan-Wilhelm Leverenz is a Technology
Strategy Consultant in Capgemini
Consulting’s BTI practice and based in
London, UK.

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