ISYU TUNGKOL SA SEKSWLADIDA (ISSUE ABOUT SEXUALITY
USE OF DATA MINING IN BANKING SECTOR
1. PRESTIGE INSTITUTE OF MANAGEMENT, GWALIOR
Presented by-
Parinita shrivastava
Arpit bhadoriya
2. 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.
3. KDD (Knowledge Discovery In
Database)
Steps:-
Selection
Preprocessing
Transformation
Data Mining
Interpretation And Evaluation
4. 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 .
5. 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.
6. DM Application Areas
Business Transaction
Electronic Commerce
Health Care Data
Web Data
Multimedia Documents
7. DM Techniques
Verification Model
Discovery Model
Clustering
8. APPLICATIONS IN BANKING
SECTOR
Marketing.
Risk Management.
Customer Relation Management.
Customer Acquisition And Retention.
9. APPLICATION IN
MARKETING
Objective:
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
10. 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
11. 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.
12. 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.