Description
The financial services industry is rapidly changing.
Application of Business Intelligence In Banks (Pakistan)
Muhammad Nadeem and Syed Ata Hussain J affri
SZABIST
Karachi, Pakistan
Abstract: The financial services industry is rapidly
changing. Factors such as globalization, deregulation,
mergers and acquisitions, competition from non-
financial institutions, and technological innovation, have
forced companies to re-think their business.
Many large companies have been using Business
Intelligence (BI) computer software for some years to
help them gain competitive advantage. With the
introduction of cheaper and more generalized products
to the market place BI is now in the reach of smaller and
medium sized companies. Business Intelligence is also
known as knowledge management, management
information systems (MIS), Executive information
systems (EIS) and On-line analytical Processing
(OLAP).
Keywords: Business Intelligence, Data warehouse, Star
Schema, Cube, Enterprise Resource Planning, Customer
Relationship Management, OnLine Analytical
Processing.
1. DEFINING BUSINESS INTELLIGENCE
“Business intelligence is the process of gathering
high-quality and meaningful information about the
subject matter being researched that will help the
individual(s) analyzing the information, draws
conclusions or make assumptions.” [J onathan, DMR
2000]
Business intelligence refers to the use of technology
to collect and effectively use information to improve
business effectiveness. An ideal BI system gives an
organization's employees, partners, and supplier's easy
access to the information they need to effectively do
their jobs, and the ability to analyze and easily share this
information with others.
1.1. Traditional Reporting
Traditionally reporting in an organization often
flows up the management hierarchy of the business e.g.
Production operators will collect information about a
production line, e.g. units produced, production time,
down time and utilization %, this information will be
passed to a shift supervisor who may well pass it in a
summarized form to the production manager and then to
a production director.
“The key to an information marketplace is an
active information repository--or catalog--which
contains or points to a variety of "information objects"
both inside and external to the organization. Users can
browse through the catalog, shopping for objects that
interest them and publishing objects that they've created
or modified for others to consume.” [Eckerson, DMR
1998]
1.2. Analytic versus Business Intelligence
“Information workers at all levels of the
organization need to be able to interact with the data: to
drill down, drill up, slice and dice business information
to quickly find the relevant facts on their own, without
administrative intervention.”[MS, MSW 2002]
Both business intelligence tools and analytic
applications draw on information that has been sourced
from multiple disparate systems across (and sometimes
beyond) an enterprise and integrated into an information
repository. Apart from this commonality, the contrast
between them couldn’t be greater.
Business intelligence tools have been likened to
spreadsheets on steroids. They deliver powerful analysis
and knowledge discovery capabilities into the hands of
specialists who have gone through week-long training
classes to become familiar in their use. But in practice,
using a business intelligence tool is a painstaking and
time-consuming process even for a power user. The user
has to be proficient in the use of the tool, know how to
structure ad hoc queries and SQL statements, and also
understand how to perform intricate analyses.
Consequently, with business intelligence tools, analysis
is performed in a silo – separate from management
functions rather than integrated with them. The resulting
reports and forecasts are not always intuitively
understandable and, in any case, represent after-the-fact
knowledge.
In contrast, analytic applications are focused on
immediacy of information, its broad deployment and its
direct applicability across the entire enterprise value
chain from front- and back-office operations to supply
chain, CRM, Web channel, sales and marketing, and
other critical line functions. Integration, analysis and
delivery capabilities can all built into the application.
Instead of waiting for reports to be sent to them by
power users, analytics-enabled managers themselves use
business problem-specific, Web- based dashboards and
scorecards to evaluate key performance metrics on a
continual basis. Rather than putting users through a
voodoo-like process that is staggering in its complexity,
analytic applications provide analytic workflows that
guide managers quickly and consistently through their
business decisions.
1.3. Strategic or Tactical
Business intelligence applications can be
deployed either strategically i.e. across functional
department or tactically i.e. within a functional
department.
1.3.1. Strategic
Strategic BI has the potential of big rewards. It
can give senior managers a holistic view of the company
and can identify trends and opportunities for growth. It
can also be used for monitoring the company against its
Key Performance Indicators (KPI’s). Because it goes
across departmental boundaries it encourages
collaborative working in the organization.
1.3.2. Tactical
Can be applied to the ‘pain’ areas of your business
where the extra knowledge and insight that BI can bring
will bring quick and quantifiable results. It is usually a
good place to start if you have had no previous
experience in BI. An example of tactical BI deployment
might be to look at production yield from a
manufacturing process, we might want to record inputs,
output, wastage, plant breakdown.
2. IDENTIFYING BUSINESS INTELLIGENCE
OPPORTUNITIES
The first task in starting a BI initiative—and the first
goal of the BI roadmap—is identifying what you want to
achieve with business intelligence. In practical terms this
means looking for opportunities in your organization
where business intelligence can improve the quality of
day-to-day decision making.
This process is divided into three primary steps:
1. Doing your homework: requires
consideration of where business
intelligence can be applied in an
organization (for example, business units
or functional areas), who is to benefit (for
example, executives, analysts, and
managers), and what types of information
are needed (for example, dimensions and
measures).
2. Sharing and collecting ideas: involves
gathering people together to brainstorm and
share their ideas and experiences about
which business processes can benefit from
business intelligence and what information
can help them improve these processes.
3. Evaluating alternatives: uses standard
criteria to assess the ideas collected during
brainstorming efforts and identify those BI
opportunities that offer the greatest
benefits.
Figure 1. A sample BI opportunity scorecard [Source:
Vitt Luckevich Misner, BI 2002]
2.1. Costs, Benefits & Returns
“Return on investment (ROI), the yardstick
against which most corporate IT projects are measured,
has not been consistently used as a justification for data
warehousing for two reasons. First, in the rush to
implement this highly popular decision support solution
and important competitive weapon, early adopters have
tended to evaluate data warehousing using less stringent
criteria than for other technology outlays. Second, due to
the relative immaturity of the technology, data
warehousing projects are recognized as inherently risky
and deserving of greater latitude in delivering ROI.”
[CRANFORD, DMR 1998]
BI opportunities are typically more difficult to
evaluate than other IT projects using traditional return on
investment, payback, and discounted cash flow
techniques, especially for companies that have no
experience with the technologies. OLTP systems are
inextricably linked to the day-to-day processes of the
business, where costs are generally well known and
consequences of systems failures, for example, not
processing an order or not invoicing a customer for
goods shipped, are understood and easily quantified.
With business intelligence, however, the most
important benefits, while intuitively obvious, are often
not easily quantifiable in advance. They revolve around
less measurable, more esoteric variables, such as the
impact of having information sooner, the quality of
decisions, new marketplace insights and tactics, and
potential shifts in competitive strategy.
The list of intangible benefits, while difficult to
quantify, is where the greatest and fastest paybacks
occur.
• Improved operational and strategic decisions
from better and more timely information
• Improved employee communications and job
satisfaction resulting from a greater sense of
empowerment
• Improved knowledge sharing
3. BUSINESS INTELLIGENCE INFRASTRUCTURE
Business organizations can gain a competitive
advantage with a well-designed business intelligence
(BI) infrastructure. Think of the BI infrastructure as a set
of layers that begin with the operational systems
information and meta data and end in delivery of
business intelligence to various business user
communities. These layers are illustrated in Figure
below.
Figure 2 Business Intelligence Infrastructure’s Layers
[DEBROSSE, TD 2003]
3.1. Business Benefits
The payback achieved by building the business
intelligence infrastructure is a function of how efficiently
it operates, how well the infrastructure is supported and
enhanced by the business organization as well as its
capacity for producing business insight from raw
operational data. The business intelligence infrastructure
delivers key information to business users. For
maximum impact, standards and procedures must be in
place to provide key business information proactively.
This business intelligence infrastructure enables the
organization to unlock the information from the legacy
systems, to integrate data across the enterprise and
empower business users to become information self-
sufficient.
Providing managers and knowledge workers
with new tools allowing them to see data in new ways
empowers them to make faster and better decisions.
Rather than responding to continuous stream of report
requests, the business intelligence platform provides
business users self-service decision support via the Web
or at the desktop.
3.2. Data Integration
“It’s exactly this widespread source of data that
has finance organizations struggling to meet the current
challenges before them. As companies grow larger
through mergers, acquisitions and global expansion, they
collect and create more and more financial systems, a
collection that becomes increasingly difficult to manage
and integrate.” [DEBROSSE, TD 2003]
Based on the overall requirements of business
intelligence, the data integration layer is required to
extract, cleanse and transform data into load files for the
information warehouse. This layer begins with
transaction-level operational data and meta data about
these operational systems. Typically this data integration
is done using a relational staging database and utilizing
flat file extracts from source systems.
3.3. Information Warehouse
The information warehouse layer consists of
relational and/or OLAP cube services that allow business
users to gain insight into their areas of responsibility in
the organization. Important in the warehouse design the
definition of databases that provide information on
confirmed dimensions or business variables that are true
across the whole enterprise.
“What’s needed to aggregate the data, then
make it available to the appropriate decision makers is a
data repository capable of pulling data from the disparate
sources spread across the enterprise – an enterprise data
warehouse (EDW).” [DEBROSSE, TD 2003]
In order to architect this information warehouse
layer correctly, the business requirements and key
business questions need to be defined. When this
information is available, there will be additional insight
into the business derived from the underlying data that
cannot be fully anticipated before the data is actually
available. Key areas to consider in defining requirements
relate to the major functional areas of the organization.
3.4. BI Applications
The most visible layer of the business
intelligence infrastructure is the applications layer which
delivers the information to business users. Business
intelligence requirements include scheduled report
generation and distribution, query and analysis
capabilities to pursue special investigations and
graphical analysis permitting trend identification.
This layer should enable business users to
interact with the information to gain new insight into the
underlying business variables to support business
decisions.
In order to achieve maximum velocity of
business intelligence, continuous monitoring processes
should be in place to trigger alerts to business decision-
makers, accelerating action toward resolving problems
or compensating for unforeseen business events. This
proactive nature of business intelligence can provide
tremendous business benefits.
3.5. Portals
Presenting business intelligence on the Web
through a portal is gaining considerable momentum.
Web-based portals are becoming commonplace as a
single personalized point of access for key business
information. All major BI vendors have developed
components which snap into the popular portal
infrastructure.
“Strictly focusing on the business intelligence
(BI) aspects of corporate portals is dangerous because it
misses the needs of end users.” [KOUNADIS, DMR
2000]
3.6. How well is Your Business Intelligence
Infrastructure Implemented and Supported?
To determine the completeness and adequacy of
your BI infrastructure, answer the following questions.
Any "no" answers indicate opportunity areas for
improvement.
1. Do you have an effective data
integration process in place to create
required business intelligence on a
daily basis?
2. Are continuous monitoring processes
in place to allow alerts to be
communicated immediately to those
who need to take action?
3. Is your information delivery process
automated?
4. Is your warehouse administration
infrastructure completely automated?
5. Are alerting techniques used to
communicate exceptions quickly so
decisions are accelerated?
6. Are the key business questions being
answered about your business areas of
responsibility?
7. Is information available on
standardized dimension such as
customer, product and geography?
8. Do you have adequate competitive
information to answer key business
questions?
9. Have you delivered scorecards on key
performance indicators to top decision-
makers?
10. Do you leverage your enterprise portal
infrastructure to deliver business
intelligence?
4. BUSINESS INTELLIGENCE AND
FINANCIAL INDUSTRY
The financial services industry is rapidly changing.
Factors such as globalization, deregulation, mergers and
acquisitions, competition from non-financial institutions,
and technological innovation, have forced companies to
re-think their business strategy.
“As competition intensifies in the retail financial
services marketplace, accurate measures of customer
value down to the account level are becoming
increasingly pivotal to success at the retail end of the
market. This applies both to established players and new
entrants.” [SIMON, NCR 2000]
Financial services companies now have to create
new revenue streams, enter new markets, gain market
share, and reduce operational costs.
In addition, customers' expectations are changing.
They are becoming better informed and more
demanding. Companies are therefore transforming their
management strategy to become more customer-centric
than product focused.
Though these challenges span the financial services
industry, consumer banking, investment banking, and
insurance each has its own unique demands that require
different success strategies.
Challenge Process Average World
Class
Provide timely,
accurate
information to
decision makers.
Closing cycle 5 - 8 days
The financial services industry is rapidly changing.
Application of Business Intelligence In Banks (Pakistan)
Muhammad Nadeem and Syed Ata Hussain J affri
SZABIST
Karachi, Pakistan
Abstract: The financial services industry is rapidly
changing. Factors such as globalization, deregulation,
mergers and acquisitions, competition from non-
financial institutions, and technological innovation, have
forced companies to re-think their business.
Many large companies have been using Business
Intelligence (BI) computer software for some years to
help them gain competitive advantage. With the
introduction of cheaper and more generalized products
to the market place BI is now in the reach of smaller and
medium sized companies. Business Intelligence is also
known as knowledge management, management
information systems (MIS), Executive information
systems (EIS) and On-line analytical Processing
(OLAP).
Keywords: Business Intelligence, Data warehouse, Star
Schema, Cube, Enterprise Resource Planning, Customer
Relationship Management, OnLine Analytical
Processing.
1. DEFINING BUSINESS INTELLIGENCE
“Business intelligence is the process of gathering
high-quality and meaningful information about the
subject matter being researched that will help the
individual(s) analyzing the information, draws
conclusions or make assumptions.” [J onathan, DMR
2000]
Business intelligence refers to the use of technology
to collect and effectively use information to improve
business effectiveness. An ideal BI system gives an
organization's employees, partners, and supplier's easy
access to the information they need to effectively do
their jobs, and the ability to analyze and easily share this
information with others.
1.1. Traditional Reporting
Traditionally reporting in an organization often
flows up the management hierarchy of the business e.g.
Production operators will collect information about a
production line, e.g. units produced, production time,
down time and utilization %, this information will be
passed to a shift supervisor who may well pass it in a
summarized form to the production manager and then to
a production director.
“The key to an information marketplace is an
active information repository--or catalog--which
contains or points to a variety of "information objects"
both inside and external to the organization. Users can
browse through the catalog, shopping for objects that
interest them and publishing objects that they've created
or modified for others to consume.” [Eckerson, DMR
1998]
1.2. Analytic versus Business Intelligence
“Information workers at all levels of the
organization need to be able to interact with the data: to
drill down, drill up, slice and dice business information
to quickly find the relevant facts on their own, without
administrative intervention.”[MS, MSW 2002]
Both business intelligence tools and analytic
applications draw on information that has been sourced
from multiple disparate systems across (and sometimes
beyond) an enterprise and integrated into an information
repository. Apart from this commonality, the contrast
between them couldn’t be greater.
Business intelligence tools have been likened to
spreadsheets on steroids. They deliver powerful analysis
and knowledge discovery capabilities into the hands of
specialists who have gone through week-long training
classes to become familiar in their use. But in practice,
using a business intelligence tool is a painstaking and
time-consuming process even for a power user. The user
has to be proficient in the use of the tool, know how to
structure ad hoc queries and SQL statements, and also
understand how to perform intricate analyses.
Consequently, with business intelligence tools, analysis
is performed in a silo – separate from management
functions rather than integrated with them. The resulting
reports and forecasts are not always intuitively
understandable and, in any case, represent after-the-fact
knowledge.
In contrast, analytic applications are focused on
immediacy of information, its broad deployment and its
direct applicability across the entire enterprise value
chain from front- and back-office operations to supply
chain, CRM, Web channel, sales and marketing, and
other critical line functions. Integration, analysis and
delivery capabilities can all built into the application.
Instead of waiting for reports to be sent to them by
power users, analytics-enabled managers themselves use
business problem-specific, Web- based dashboards and
scorecards to evaluate key performance metrics on a
continual basis. Rather than putting users through a
voodoo-like process that is staggering in its complexity,
analytic applications provide analytic workflows that
guide managers quickly and consistently through their
business decisions.
1.3. Strategic or Tactical
Business intelligence applications can be
deployed either strategically i.e. across functional
department or tactically i.e. within a functional
department.
1.3.1. Strategic
Strategic BI has the potential of big rewards. It
can give senior managers a holistic view of the company
and can identify trends and opportunities for growth. It
can also be used for monitoring the company against its
Key Performance Indicators (KPI’s). Because it goes
across departmental boundaries it encourages
collaborative working in the organization.
1.3.2. Tactical
Can be applied to the ‘pain’ areas of your business
where the extra knowledge and insight that BI can bring
will bring quick and quantifiable results. It is usually a
good place to start if you have had no previous
experience in BI. An example of tactical BI deployment
might be to look at production yield from a
manufacturing process, we might want to record inputs,
output, wastage, plant breakdown.
2. IDENTIFYING BUSINESS INTELLIGENCE
OPPORTUNITIES
The first task in starting a BI initiative—and the first
goal of the BI roadmap—is identifying what you want to
achieve with business intelligence. In practical terms this
means looking for opportunities in your organization
where business intelligence can improve the quality of
day-to-day decision making.
This process is divided into three primary steps:
1. Doing your homework: requires
consideration of where business
intelligence can be applied in an
organization (for example, business units
or functional areas), who is to benefit (for
example, executives, analysts, and
managers), and what types of information
are needed (for example, dimensions and
measures).
2. Sharing and collecting ideas: involves
gathering people together to brainstorm and
share their ideas and experiences about
which business processes can benefit from
business intelligence and what information
can help them improve these processes.
3. Evaluating alternatives: uses standard
criteria to assess the ideas collected during
brainstorming efforts and identify those BI
opportunities that offer the greatest
benefits.
Figure 1. A sample BI opportunity scorecard [Source:
Vitt Luckevich Misner, BI 2002]
2.1. Costs, Benefits & Returns
“Return on investment (ROI), the yardstick
against which most corporate IT projects are measured,
has not been consistently used as a justification for data
warehousing for two reasons. First, in the rush to
implement this highly popular decision support solution
and important competitive weapon, early adopters have
tended to evaluate data warehousing using less stringent
criteria than for other technology outlays. Second, due to
the relative immaturity of the technology, data
warehousing projects are recognized as inherently risky
and deserving of greater latitude in delivering ROI.”
[CRANFORD, DMR 1998]
BI opportunities are typically more difficult to
evaluate than other IT projects using traditional return on
investment, payback, and discounted cash flow
techniques, especially for companies that have no
experience with the technologies. OLTP systems are
inextricably linked to the day-to-day processes of the
business, where costs are generally well known and
consequences of systems failures, for example, not
processing an order or not invoicing a customer for
goods shipped, are understood and easily quantified.
With business intelligence, however, the most
important benefits, while intuitively obvious, are often
not easily quantifiable in advance. They revolve around
less measurable, more esoteric variables, such as the
impact of having information sooner, the quality of
decisions, new marketplace insights and tactics, and
potential shifts in competitive strategy.
The list of intangible benefits, while difficult to
quantify, is where the greatest and fastest paybacks
occur.
• Improved operational and strategic decisions
from better and more timely information
• Improved employee communications and job
satisfaction resulting from a greater sense of
empowerment
• Improved knowledge sharing
3. BUSINESS INTELLIGENCE INFRASTRUCTURE
Business organizations can gain a competitive
advantage with a well-designed business intelligence
(BI) infrastructure. Think of the BI infrastructure as a set
of layers that begin with the operational systems
information and meta data and end in delivery of
business intelligence to various business user
communities. These layers are illustrated in Figure
below.
Figure 2 Business Intelligence Infrastructure’s Layers
[DEBROSSE, TD 2003]
3.1. Business Benefits
The payback achieved by building the business
intelligence infrastructure is a function of how efficiently
it operates, how well the infrastructure is supported and
enhanced by the business organization as well as its
capacity for producing business insight from raw
operational data. The business intelligence infrastructure
delivers key information to business users. For
maximum impact, standards and procedures must be in
place to provide key business information proactively.
This business intelligence infrastructure enables the
organization to unlock the information from the legacy
systems, to integrate data across the enterprise and
empower business users to become information self-
sufficient.
Providing managers and knowledge workers
with new tools allowing them to see data in new ways
empowers them to make faster and better decisions.
Rather than responding to continuous stream of report
requests, the business intelligence platform provides
business users self-service decision support via the Web
or at the desktop.
3.2. Data Integration
“It’s exactly this widespread source of data that
has finance organizations struggling to meet the current
challenges before them. As companies grow larger
through mergers, acquisitions and global expansion, they
collect and create more and more financial systems, a
collection that becomes increasingly difficult to manage
and integrate.” [DEBROSSE, TD 2003]
Based on the overall requirements of business
intelligence, the data integration layer is required to
extract, cleanse and transform data into load files for the
information warehouse. This layer begins with
transaction-level operational data and meta data about
these operational systems. Typically this data integration
is done using a relational staging database and utilizing
flat file extracts from source systems.
3.3. Information Warehouse
The information warehouse layer consists of
relational and/or OLAP cube services that allow business
users to gain insight into their areas of responsibility in
the organization. Important in the warehouse design the
definition of databases that provide information on
confirmed dimensions or business variables that are true
across the whole enterprise.
“What’s needed to aggregate the data, then
make it available to the appropriate decision makers is a
data repository capable of pulling data from the disparate
sources spread across the enterprise – an enterprise data
warehouse (EDW).” [DEBROSSE, TD 2003]
In order to architect this information warehouse
layer correctly, the business requirements and key
business questions need to be defined. When this
information is available, there will be additional insight
into the business derived from the underlying data that
cannot be fully anticipated before the data is actually
available. Key areas to consider in defining requirements
relate to the major functional areas of the organization.
3.4. BI Applications
The most visible layer of the business
intelligence infrastructure is the applications layer which
delivers the information to business users. Business
intelligence requirements include scheduled report
generation and distribution, query and analysis
capabilities to pursue special investigations and
graphical analysis permitting trend identification.
This layer should enable business users to
interact with the information to gain new insight into the
underlying business variables to support business
decisions.
In order to achieve maximum velocity of
business intelligence, continuous monitoring processes
should be in place to trigger alerts to business decision-
makers, accelerating action toward resolving problems
or compensating for unforeseen business events. This
proactive nature of business intelligence can provide
tremendous business benefits.
3.5. Portals
Presenting business intelligence on the Web
through a portal is gaining considerable momentum.
Web-based portals are becoming commonplace as a
single personalized point of access for key business
information. All major BI vendors have developed
components which snap into the popular portal
infrastructure.
“Strictly focusing on the business intelligence
(BI) aspects of corporate portals is dangerous because it
misses the needs of end users.” [KOUNADIS, DMR
2000]
3.6. How well is Your Business Intelligence
Infrastructure Implemented and Supported?
To determine the completeness and adequacy of
your BI infrastructure, answer the following questions.
Any "no" answers indicate opportunity areas for
improvement.
1. Do you have an effective data
integration process in place to create
required business intelligence on a
daily basis?
2. Are continuous monitoring processes
in place to allow alerts to be
communicated immediately to those
who need to take action?
3. Is your information delivery process
automated?
4. Is your warehouse administration
infrastructure completely automated?
5. Are alerting techniques used to
communicate exceptions quickly so
decisions are accelerated?
6. Are the key business questions being
answered about your business areas of
responsibility?
7. Is information available on
standardized dimension such as
customer, product and geography?
8. Do you have adequate competitive
information to answer key business
questions?
9. Have you delivered scorecards on key
performance indicators to top decision-
makers?
10. Do you leverage your enterprise portal
infrastructure to deliver business
intelligence?
4. BUSINESS INTELLIGENCE AND
FINANCIAL INDUSTRY
The financial services industry is rapidly changing.
Factors such as globalization, deregulation, mergers and
acquisitions, competition from non-financial institutions,
and technological innovation, have forced companies to
re-think their business strategy.
“As competition intensifies in the retail financial
services marketplace, accurate measures of customer
value down to the account level are becoming
increasingly pivotal to success at the retail end of the
market. This applies both to established players and new
entrants.” [SIMON, NCR 2000]
Financial services companies now have to create
new revenue streams, enter new markets, gain market
share, and reduce operational costs.
In addition, customers' expectations are changing.
They are becoming better informed and more
demanding. Companies are therefore transforming their
management strategy to become more customer-centric
than product focused.
Though these challenges span the financial services
industry, consumer banking, investment banking, and
insurance each has its own unique demands that require
different success strategies.
Challenge Process Average World
Class
Provide timely,
accurate
information to
decision makers.
Closing cycle 5 - 8 days