First National Bank (FNB) needed to accelerate the creation and processing of business rules to drive faster decision making as it expanded. It deployed IBM Operational Decision Manager on its IBM mainframe, reducing the time to adapt rules from 40 days to near real-time. This enabled FNB to respond faster to changing regulations and make smarter decisions consistently across its operations. The new system provided a 40x performance increase over its previous fragmented rules architecture.

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Avsharn Bachoo
Development Manager responsible
for Dynamic Decisioning
First National Bank
Established in 1838, First National Bank (FNB) is the oldest bank in
South Africa and one of the region’s largest financial institutions. FNB provides
banking and insurance products to personal, commercial, corporate and
public-sector customers.
Business challenge
Rules-based decision-making
processes at FNB were not fast,
agile or consistent enough to meet
demands imposed by geographic
expansion, increasing regulation and
new consumer expectations.
Transformation
By deploying a centralized rules
engine on its IBM mainframe, FNB
greatly accelerated the creation,
dissemination and processing of new
business rules, driving smarter and
faster decision-making.
First National Bank
Driving faster, smarter, more
consistent and more efficient
decision-making
“We are helping the
business to make better
decisions at higher speed.”
Jay Prag
First National Bank
Business benefits:
40x increase
in performance, for
faster and more accurate
decision-making
Accelerates
adaptation of business rules
to meet changing demands
Reduces
latency to enable support for
online channels

2. 2
Fragmented rules
Most organizations—and larger ones
in particular—maintain sets of business
rules designed to ensure that all
employees are empowered to make
operational decisions that support the
strategic goals of the organization. In
banking, these rules form the basis of
decisioning systems that help determine
which investments should be made,
which people are permitted to open
accounts, which products can be offered
to which customers, and much more.
Like other banks, FNB relies on shared
business rules and assessment tools to
ensure that it strikes the optimal balance
between risk and opportunity in all
operations. As it expanded its business
activities both within South Africa and in
neighboring countries, FNB found that
its decision-support systems were not
running optimally in the face of increasing
demands from internal users, customers
and regulators. In particular, the inflexibility
of existing systems was making it slow
and costly to adapt rules to meet new
requirements, hindering business agility.
Avsharn Bachoo, Development Manager
responsible for Dynamic Decisioning in
FNB, takes up the story: “Architecturally,
the existing solution could not support
different sets of rules for each country,
so we were forced to construct multiple
instances of the rules engine. This
implied the costly replication of rules and
associated redevelopment and testing
work, and also meant that changes made
by head office took too long to propagate
out to the subsidiary countries.”
With up to 40 changes to shared central
rules each month, each of which had
to be separately tested and deployed
across ten countries, the existing
approach at FNB was clearly inefficient
in development terms. More important,
the subsidiary countries were often
working with outdated rules and risk
profiles, potentially decreasing the quality
of decisions and limiting the ability of the
business to respond to new challenges
and opportunities.
“We needed a new approach that would
give us the agility to cope with changing
regulations and business conditions,”
comments Avsharn Bachoo. “By cutting
the time required to code, develop and
deploy rules, we knew that we could save
on internal costs and greatly improve the
bank’s competitive stance.”
He adds: “Our new model was based
on the idea of deploying rules and
parameters from a central point of control
out to multiple environments, and it
made sense to bring the rules engine
into our mainframe landscape to run
alongside our core banking systems. In
the existing set-up, each reference to
the rules engine meant switching out to
a separate platform, and the latency that
this introduced meant that we couldn’t
support increasingly vital online channels,
which need high-speed responses.”
“Beyond the value of reduced effort
and increased reusability in
development, employees get the
benefit of new rules and
decisioning support faster than
before, helping them to make
smarter decisions for the business.”
Avsharn Bachoo, Development Manager
responsible for Dynamic Decisioning, First
National Bank

3. 3
Driving better
business decisions
FNB carried out a major study of
decisioning solutions from seven vendors
before selecting IBM Operational Decision
Manager running on IBM z/OS.
“The IBM solution was the only rules
engine that could run equally well both
within and outside of the mainframe
environment,” says Avsharn Bachoo.
“Our initial projects have focused
on the mainframe but we will be
deploying to distributed platforms as
well. Another factor in our choice of
IBM Operational Decision Manager was
the ability to use the industry-standard
ECLIPSE development environment
and tooling rather than a proprietary
environment. Openness and re-usability
are very important to us.”
During the proof-of-concept phase,
IBM Operational Decision Manager
proved itself to be the only solution that
could handle the volumes of data FNB
needed to process. At that time, FNB was
looking to create an internal credit-risk
bureau that would eliminate the need
to make costly and time-consuming
inquiries to a third-party bureau each time
a new customer opened a bank account.
“We tried to use our old decision engine
to support the new credit-risk bureau, but
the data volume was too large,” recalls
Avsharn Bachoo. “We experimented with
the other engines under consideration,
but at that time they were all doing flat
processing. With its multi-dimensional
approach, IBM Operational Decision
Manager was the only one up
to the task.”
IBM helped FNB fast-track the
deployment of Operational Decision
Manager to support the fixed go-live date
for the internal credit-risk bureau. “IBM
helped us make sure that the solution
would handle the production workload,
accelerated the implementation, helped
us with the development of rules and
provided intensive on-the-job training
to get our developers up to speed with
the new tool and with object-oriented
principles,” says Avsharn Bachoo.
FNB initially processed decisions in
Java running on a standard mainframe
processor. By choosing to output the
rules files in a binary format and moving
the workload to a specialty zIIP processor,
FNB both improved the performance and
reduced its MIPS consumption.
The first new application FNB has built
using Operational Decision Manager is
Aggregations, which scores customers
for credit risk based on an analysis
of 24 months of transactional history.
The scoring process runs overnight and
produces 150 metrics on each customer,
which are then used by the core banking
system to determine each individual
risk profile. With the help of IBM, the
application went from initial inception to
production in less than three months.
The next application in the pipeline,
Personal Banking, will provide scoring
for all products available to personal
banking customers and will include rate
and pricing recommendations, fraud
detection, and cross/upsell features.
Beyond this, FNB plans to move its
monthly data enrichment batch job into
Operational Decision Manager to speed
up the ingestion of new data for online
credit scoring.
Easier, faster, more
cost-effective
Deploying Operational Decision Manager
on the IBM z Systems platform has given
FNB a single point of control for multiple
sets of business rules, with a consistent
set of development tools and practices.
Tactical or strategic changes to business
rules can now be applied more rapidly
and propagated down to subsidiary
countries with no additional development
or testing effort, enabling the bank to
respond faster and in a more agile way to
emerging threats or opportunities – all at
lower cost.
“Today, it is easier, faster and more
cost-effective to adapt our business
rules,” says Avsharn Bachoo. “We
can deploy almost simultaneously
to all geographies, and the use of a
parent-child structure keeps local variants
of central rules updated with any later
changes. Beyond the value of reduced
effort and increased re-usability in
development, employees get the benefit
of new rules and decisioning support
faster than before, helping them to make
smarter decisions for the business.”

4. Please Recycle
Solution components
• IBM® Operational Decision Manager
for z/OS®
• IBM PureData® System for Analytics
• IBM z Systems™
• IBM z/OS
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To learn more about IBM Operational
Decision Manager for z/OS, please contact
your IBM representative or IBM Business
Partner, or visit the following website:
ibm.com/software/products/en/category/
operational-decision-management
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© Copyright IBM Corporation 2016, IBM Corporation, 1 New Orchard Road, Armonk, NY 10504 U.S.A. Produced in the United States of America, January 2016.
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compliance with any law or regulation.
With the decision-support rules engine
now running alongside core banking
systems on the IBM z Systems platform,
FNB has simplified its architecture and
practically eliminated latency. In the past,
calls to the rules engine were directed to
a different server on the internal network,
adding at least a second of latency. By
contrast, the new rules engine is called
across memory on z Systems, delivering
an estimated 40 times improvement in
performance and enabling the engine to
serve online channels.
“With faster delivery of recommendations
based on the latest sets of rules, we
are helping the business to make
better decisions at higher speed, which
ultimately translates into competitive
advantage,” comments Jay Prag of
FNB. “We also have the advantage
of running the solution alongside
our core banking software on the
tried-and-trusted z Systems platform,
ensuring extremely high availability
and security. This is all part of our
migration from a batch-oriented culture
to a real-time, events-driven and
insightful architecture.”
For the future, FNB is considering
deploying the Decision Server
Insights component of Operational
Decision Manager, which will
draw data from the bank’s new
IBM PureData System for Analytics to
enable intelligent response to events in
real time.
For example, if a customer’s balance
drops below zero, the solution will
determine an appropriate response and
execute it. For an entry-level customer,
that might mean sending an SMS to
their mobile handset reminding them to
top-up their balance, while for a premium
customer, it might result in a call-center
operative contacting them to offer
assistance.
ZSC03323-USEN-00
“While our initial use of Operational
Decision Manager has largely been
for credit scoring, we are moving into
areas such as fraud detection, customer
segmentation, pricing, loyalty schemes
and our life insurance business,”
comments Avsharn Bachoo. “The
solution gives us a vanilla tool that we
can adapt to any requirements, taking
advantage of the skills and knowledge we
are accruing in the Center of Excellence.
Consolidating to a single strategic tool for
decisioning will therefore produce further
benefits in the future.”