Data mining application in CRM of Commercial Bank.

1. Data Mining Technology and its
Application In CRM of
Commercial Banks

2. Concept of CRM
1. CRM Is a Business Strategy: Focus on profitability,
revenue and customer satisfaction by:
– Organizing your customers.
– Fostering customer-satisfying behaviors and
implementing customer centric processes.
2. And Also A Technology: Should enable greater
customer insight, produce more effective customer
interactions and should integrate of all customer
channels and back-office functions.

3. CRM Goals
• Cut Internal Costs
– Improve your Processes
• Ex: Remove customer hold times.
• Centralize data from every department
• Increase sales
– Automate the sales process
– Perform more lucrative marketing campaigns
• Gain A Competitive Advantage
– Ex: Amazon.com Data Mining

4. How CRM works in Commercial bank
• Commercial banks’ CRM refers to the
promotion and application of CRM in the
banking field of commercial banks and falls
into three levels:
• communication-level CRM
• operation-level CRM
• support-level

5. The communication-level
• CRM is the interface to interact, collect and
output information with customers, including
phone, fax, Internet, Email, wireless network,
traditional counter, branch and others.
• customers can use various ways to get contact
with customer service center, to retain the
required information and service.

6. The operation-level CRM
• It is made up of each submodule:-
-executing fundamental functions of CRM,
- including sales management module,
- marketing management module,
-customer service & support module,
-business intelligence management module,
-call center management module and
-E-commerce management module.

7. The support-level CRM
• In the whole CRM structure, support-level
CRM completes processing information
accumulated from communication-level and
operation-level, and then produces the
analytical information based on the two.

8. architecture

9. The Application of DM in Commercial
Banks’ CRM System.
• In the CRM of commercial banks, the DM is
mainly used for such aspects
• customer acquisition
• classification
• retention
• cross-selling
• customer risk analysis and customer lifetime
value management.

11. Customer Classification
• The main indicators of CRM service development
lie in new customer acquisition and customer
classification.
• It is not better for banks to have more
customers. In contrast, some customers only
increase cost of banks instead of bring profits.
• Therefore, it is quite useful to utilize the DM
technology to classify customers, e.g. net income
and Value at Risk (VaR)

12. Customer Retention
• Along with competitions in banking industry,
acquiring a new customer will cost more and
more, while retaining a customer can save much
more cost; therefore, old customers retention are
more and more valuable.
• It plays an important role in the whole task of
customer retention to use DM technology to set
up a model of different activities to retain
customers.

13. Cross-selling
• Nowadays, the relationship between banks and customers
often varies. In case of owning a new customer, banks need
to try their best to perfect this relationship.
• The cross-selling is to try to use the lowest cost to make
one customer has more financial products.
• Banks utilize the association analysis of the DW technology
to find out factors which will produce
• an influence on purchasing behaviors of customers from
their past purchasing data.
• analyze which parts of customers would be interested in
banks’ services.
• which services they would be interested in.

14. D. Customer Risk Analysis
• Credit business is one of core services of
commercial banks
• these services are always the focus of concerns
and troublesome questions.
• the CRM system of a bank can use feature
selection & attribute correlation analysis tools to
analyze the historical repayment data of
customers, scientifically strengthen the
management of credit evaluation, risk
measurement, credit risk weight of borrowing
customers, so as to effectively prevent and

15. Customer Lifetime Value Management
• CLV means the profits the customer makes
from the business relationship in the whole
lifetime.
• The DM technology can be used to judge the
lifetime status where the customer is and
forecast the time of entering the following
lifetime phase.

16. Conclusion
• The CRM in commercial banks has become a
priority tool for banks to carry out various
personalized services as a novel operating
mechanism aiming at improving the relationship
between banks and customers.
• The introduction of DM technology into CRM of
commercial banks can make classification,
clustering and association analysis of customer
behaviors according to set models to covert the
data into useful information to support operating
decision making.