PRESTIGE INSTITUTE OF MANAGEMENT, GWALIOR

Presented by-Parinita shrivastavaAbhishek sharmaArpit bhadoriyaBhupendra sonyBCA 2nd sem

What is DATA

WAREHOUSE..? A DATA WAREHOUSE is a subject oriented,

integrated, time-varying, non-voletile collection of

data in support of the management’s decision-

making process.

KDD (Knowledge Discovery In

Database)

Steps:-

Selection

Preprocessing

Transformation

Data Mining

Interpretation And Evaluation

What is DATA MINING..?

DATA MINING refers to extracting knowledge from

large amount of data.

It is a powerful new technology with great potential

to analyze important information in the data

warehouse .

Why use DATA MINING?

Two main reasons to use data mining:

Too much data and too little information.

There is a need to extract useful information

from the data and to interpret the data.

DM Application Areas

Business Transaction

Electronic Commerce

Health Care Data

Web Data

Multimedia Documents

DM Techniques

Verification Model

Discovery Model

Clustering

APPLICATIONS IN BANKING

SECTOR

Marketing.

Risk Management.

Customer Relation Management.

Customer Acquisition And Retention.

APPLICATION IN

MARKETINGObjective:

Improve marketing techniques and target customers

Traditional applications:

Customer segmentation

Identify most likely respondents based on previous campaigns

Cross selling

Develop profile of profitable customers for a product

Attrition analysis:

Alert in case of deviation from normal behaviour

RISK MANAGEMENT

Objective:

Reduce risk in credit portfolio

Traditional applications:

Default prediction

Reduce loan loses by predicting bad loans

High risk detection

Tune loan parameters ( e. g. interest rates, fees) in order to

maximize profits

Profile of highly profitable loans

Understand characteristics of most profitable mortgage loans

Credit card fraud detection

Identify patterns of fraudulent behaviour

CUSTOMER ACQUISITION AND

RETENTION

Objective:

Increasing value of the Customer and Customer Retention.

Traditional Application:

Needs of the customer by providing products and services

which they prefer.

Help us to find the loyal customer.

Need to accomplish relation between bank and customer.

CONCLUSION

Data mining is a tool enable better decision-making

throughout the banking and retail industries..

Data Mining techniques can be very helpful to the banks for

better targeting and acquiring new customers.

Fraud detection in real time.

Analysis of the customers.

Purchase patterns over time for better retention and

relationship.