International Journal of Engineering Trends and Technology (IJETT) – Volume 14 Number 5 – Aug 2014
Centralized Financial Networking System for
Banking Applications through Data Mining
Techniques
P.V.D Prasad,
Senior Consultant,
J M R InfoTech,
Beta Building, Sigma Soft Tech Park,
Whitefield, Bangalore - 560066
Abstract -Financial sector is the core sector to decide
the country’s GDP. The substantial and continuous
development of any country is based on the financial
health of the nation. Last few decades witnessed the
proliferation of financial reforms, liberalization and
globalization of Indian economy coupled with rapid
revolution in information technology (IT).The paper
presents the benefits of applying data mining (DM) and
data warehousing (DW) techniques in customer
relationship management (CRM) of the financial sectors
like banking. It is a process of analyzing the data from
various perspectives and summarizing it into valuable
information. Data mining assists the banks to look for
hidden pattern in a group and discover unknown
relationship in the data. These techniques facilitate useful
data interpretations for the banking sector to avoid
customer attrition. And also fraud is a significant problem
in banking sector. Detecting and preventing fraud is
difficult, because fraudsters develop new schemes all the
time, and the schemes grow more and more sophisticated
to elude easy detection.
Key words - centralized system, financial Networking,
Data Mining, Operational Data.
I.INTRODUCTION
Technological innovations have enabled the banking
industry to open up efficient delivery channels to the
public. IT has helped the banking industry to deal with the
challenges the new economy poses. Nowadays, Banks
have realized that customer relationships are a very
important factor for their success in the market. Advent of
information technology and cyber devices heralded a new
world and bought tremendous change in all the sectors of
the economy. For this banks are exploring new financial
products and service options that would help them grow
without losing existing customers.
ISSN: 2231-5381
Financial services are the economic services provided by
the finance industry, which encompasses a broad range of
organizations that manage money, including unions,
banks, credit card companies, insurance companies,
accountancy companies, consumer finance companies,
stock brokerages, investment funds and some government
sponsored enterprises.
II.THE PRIMARY OPERATIONS OF BANKS
INCLUDE
Keeping money safe while also allowing withdrawals
when needed. Issuance of chequebooks so that bills can
be paid and other kinds of payments can be delivered by
post.Provide personal loans, commercial loans, and
mortgage loans.Issuance of credit cards and processing of
credit card transactions and billing.Issuance of debit cards
for use as a substitute for cheques.Allow financial
transactions at branches or by using Automatic Teller
Machines (ATMs).Provide wire transfers of funds and
Electronic fund transfers between banks through internet.
Provide Charge card advances of the Bank's own money
for customers wishing to settle credit advances monthly.
Provide a check guaranteed by the Bank itself and prepaid
by the customer.Accepting the deposits from customer
and provide the credit facilities to them. Sell Investment
products like Mutual funds etc.
III.TECHNOLOGY APPLICATION IN BANKS
The various technology applications in banking:
a) Data Warehousing
b) Data Mining
c) Electronic Data Interchange
d) Corporate Web Sites
e) Management Information System
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International Journal of Engineering Trends and Technology (IJETT) – Volume 14 Number 5 – Aug 2014
This illustrates five things:
IV.DATA WAEHOUSING AND DATAMINING
4.1. Data warehousing-In computing, a data warehouse
(DW, DWH), or an enterprise data warehouse (EDW), is a
system used for reporting and data analysis. Integrating
data from one or more disparate sources creates a central
repository of data, a data warehouse (DW). Data
warehouses store current and historical data and are used
for creating trending reports for senior management
reporting such as annual and quarterly comparisons.
4.2 Data mining-Data mining (the analysis step of the
"Knowledge Discovery in Databases" process, or KDD),
an interdisciplinary sub-field of computer science, is the
computational process of discovering patterns in large
data sets involving methods at the intersection of artificial
intelligence, machine learning, statistics, and database
systems. The overall goal of the data mining process is to
extract information from a data set and transform it into
an understandable structure for further use. Aside from
the raw analysis step, it involves database and data
management aspects, data pre-processing, model and
inference considerations, disinterestedness metrics,
complexity considerations, post-processing of discovered
structures, visualization, and online updating.
a.
b.
c.
d.
e.
Data Sources (operational systems and flat files)
Staging Area (where data sources go before the
warehouse)
Warehouse (metadata, summary data, and raw data)
Data Marts (purchasing, sales, and inventory)
Users (analysis, reporting, and mining)
V.ARCHITECTURE OF DATAMINING
Data mining is described as a process of discover or
extracting interesting knowledge from large amounts of
data stored in multiple data sources such as file systems,
databases, data warehouses etc.
This knowledge
contributes a lot of benefits to business strategies,
scientific, medical research, governments and individual.
4.3 ARCHITECCTURE OF DATA WAREHOUSE
Banks require a variety of solutions ranging from a fully
centralized global data warehouse (DW), to not integrated
data marts (DM) for the emerging needs of the
departments. Both of these extreme solutions have
significant disadvantages along with their benefits, so it is
worth considering the indirect variant presented here
based on a global data source ODS (Operational Data
Store), a global DW and DMs.
ISSN: 2231-5381
a.
b.
c.
d.
e.
Steps involved in architecture are
Client gives the data
Data assembling is done
Data verification
Task assignment by team leader to employees
Finally data is dispatched
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International Journal of Engineering Trends and Technology (IJETT) – Volume 14 Number 5 – Aug 2014
To best apply these advanced techniques, they must be
b. Hedge fund management - Hedge funds often
fully integrated with a data warehouse as well as flexible
employ the services of "prime brokerage" divisions
interactive business analysis tools. Many data
at major investment banks to execute their trades.
Mining tools currently operate outside of the warehouse,
c. Custody services - the safe-keeping and processing
requiring extra steps for extracting, importing, and
of the world's securities trades and servicing the
analyzing the data.
associated portfolios.
IX.FINANCIAL SERVICES
VI.INVESTMENT BANKING SERVICES
a.
b.
c.
Capital markets services - underwriting debt and
equity, assist company deals, and restructure debt
into structured finance products.
Private banking - Private Banks provide banking
services exclusively to high-net-worth individuals.
Brokerage services - facilitating the buying and
selling of financial securities between a buyer and a
seller.
The following services are obtained by the user in the
financial system.
a.
b.
c.
d.
e.
f.
g.
h.
i.
Bank cards.
Credit card machine services and networks.
Inter-mediation or advisory services.
Private equity.
Venture capital.
Angel investmentt.
Conglomerates.
Financial market utilities.
Debt resolution.
X.THE NEED FOR CENTRALIZED
INFRASTRUCTURE
a.
b.
Decentralization is the early days of banking
technology. This meant that each branch had its own
server, banking applications, database, and other
such assorted hardware/software.
Decentralized networks had their own set of
problems in terms of the cost and management
fronts.
VII.FOREIGN EXCHANGE SERVICES
Foreign exchange services include:
a.
b.
c.
Currency exchange - where clients can purchase and
sell foreign currency banknotes.
Wire transfer - where clients can send funds to
international banks abroad.
Remittance - where client that are migrant workers
send money back to their home country.
VIII .INVESTMENT SERVICES
a.
Asset management - the term usually given to
describe companies which run collective investment
funds.
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c.
There came the need for a centralized database. The
database had to be updated instantaneously
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d.
International Journal of Engineering Trends and Technology (IJETT) – Volume 14 Number 5 – Aug 2014
irrespective of the branch or channel the customer
e. When one or two private sector banks showed that it
used.
can be done efficiently, other banks began to show
Things changed when banks realized the cost
an interest—they also began consolidating their
benefits of swapping the decentralized model to
databases into a single large database.
centralized data center architecture.
Centralization using a data center has helped a lot in
improving and simplifying the network from the
operations, user, and administration perspectives. From a
cost perspective, centralization has been very effective.
f.
It is not just the data center which contributed to
centralization. The network has also evolved into a
unified IP network.
XI.MINING FOR INTELLIGENCE
1. Another important issue banks face is in proper
analysis of financial data to identify business potential.
2. CRM backing with your data warehouse solution,
streamlines the channels, but also tells you where to
move. It tells you which customer to focus on.
3, A data warehouse can help the bank get a single view
of its data across disparate systems.
4. Data warehousing solves these by integrating all the
data into a common warehouse (usually an RDBMS).
5. Data mining can help you recognize patterns in the
data you have.
Data mining will be the cornerstone of the competitive if
not the survival strategy for the next millennium in
banking. Banks which ignore it are giving away their
future to competitors which today are busy mining.
a.
b.
c.
d.
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Managing customers is one of the main issues that
banks face in today's hyper competitive
environment.
Before banks go for a CRM solution, they need to
ask themselves one question: How well do they
know their customer?
For that matter how many customers have moved in
the past? Or how existing customers use various
services that the bank provides.
In banking, being the first to market alone is not
enough since products can be copied very fast.
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e.
f.
g.
h.
i.
International Journal of Engineering Trends and Technology (IJETT) – Volume 14 Number 5 – Aug 2014
This excerpt from Data Mining: Know It All
12. www.zentut.com/data-mining/data-miningincludes examples that show how data mining
architecture/
algorithms and data sets work.
13. www.tutorialspoint.com/data_mining/dm_applicati
Retiring applications.
ons_trends.htm
Reducing data footprint and storage costs.
[14].http://www.researchgate.net/post/What_is_the_di
Enhancing operational efficiency.
fference_between_machine_learning_and_data_minin
Implementing a structured data management policy.
g2 19/1/1/7
XIII.CONCLUSION
[15].https://www.cs.ucsb.edu/research/machinelearning-and-data-mining
Data warehouses are costly and complex undertakings
with the primary purpose of supporting the management.
Development should be determined by the rules of
efficient business, not the ambitions of technology
personnel. Essential to success is the formulation of
business goals and information needs, the quality of the
input data and the proper use of the potential of modern
technology. As banking competition becomes more and
more global and intense, banks have to fight more
creatively and proactively to gain or even maintain
market shares.
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