Evaluation and Classification of Commercial Bank Customer Value

Peng Yanyan

Business School, Hohai University Jiangsu Nanjing, China 210000 E-mail: pengyanyan99@126.com

Abstract-In order to solve the problem of commercial banks

to identify customers, from the reality of commercial banks,

constructs a synthesis appraisal model of commercial bank

customer value, proper attention to both practical and

suitable. Proposes two-dimensional clustering segmentation

method based on the customer current value and the

increment value, provides support for the bank to evaluate

the customer value objectively, subdivide the customer

scientifically, realize the limited marketing and the

difference service effectively. Empirical results show that

this method can help managers identify high-quality

customers, and according to their ability to formulate a

quality customer training programs, use the limited

marketing resources on the most valuable or most potential

customers.

Keywords-commercial bank; customer value; customer

segmentation; clustering analyses;

I INTRODUCTION

Along with the development of the financial business, the competitive mode of bank "to the product as the center" has been gradually replaced by the new business model "to the customer as the center", Customers become the most important resource for the bank, and to pay attention to the customer management, mining the customer value be development of banking core power. At present, the bank to the value of the clients are limited to measure customer at present consumption bank products or services for Banks create profits, do not take into account the potential contribution to the customer value. At the same time, the existing evaluation method cause the relevance of every index is low and objectivity is poorer, customer classification also mainly enterprise scale, business nature, industry category index as the basis, the division of the method, the method to partition the customers from a target to classification, classification results reflect the characteristics of a certain aspect of

customer, can't reflect the value of comprehensive customer. Therefore, this article from the reality of China's commercial Banks, to build a practical consideration and apply the commercial bank customer value comprehensive evaluation model, and based on evaluation results combined with clustering analysis tools to customer resources for the bank an objective evaluation of the segment, customer value, science subdivision customers, the more effectively in layered marketing and service support difference.

II COMMERCIAL BANK CUSTOMER COMPREHENSIVE

EVALUATION INDEX VALUE

Existing customer-related indicators and evaluation models are the Market Share, RFM (Regency, Frequency, Monetary) customer net present value model and evaluation system [1]. Market share and corporate profits have a positive relationship between, for a long time it has always been an important index of enterprise to measure current situation and overall customer enterprise market strategy. FRM is used in the field of direct actions of a very useful analytical tool, Main through customer the past habitual or repetitive trading behavior and purchasing behavior preference to predict future customer consumer behavior. Customer net present value of evaluation index system is based on Frederick Reich held’s loyalty factor analysis of corporate earnings growth in the life cycle model , because some indexes are difficult to objective evaluation, the system is only a theory of design, practical applications are rare. In this paper, based on the theory of RFM, build customer value and comprehensive evaluation index system from the customer's current value and potential value of commercial banks. See table

TABLEI COMMERCIAL BANK CUSTOMERS COMPREHENSIVE

EVALUATION VALUE

Level 1 Level 2 Level 3 The current value P

Asset business value P1

Loan total daily P11

Average interest rate received P12

Way of loan guarantees P13

Liability business value P2

Deposit total daily P21

2011 Fourth International Conference on Business Intelligence and Financial Engineering

978-0-7695-4527-1/11 $26.00 © 2011 IEEE

DOI 10.1109/BIFE.2011.59

683

2011 Fourth International Conference on Business Intelligence and Financial Engineering

978-0-7695-4527-1/11 $26.00 © 2011 IEEE

DOI 10.1109/BIFE.2011.59

684

2011 Fourth International Conference on Business Intelligence and Financial Engineering

978-0-7695-4527-1/11 $26.00 © 2011 IEEE

DOI 10.1109/BIFE.2011.59

683

2011 Fourth International Conference on Business Intelligence and Financial Engineering

978-0-7695-4527-1/11 $26.00 © 2011 IEEE

DOI 10.1109/BIFE.2011.59

682

Average servicing rate P22 Deposit standard deviation P23

Intermediate business value P3

Intermediate business income P31

Transaction number P32 transaction cost P4 Weighted average expense ratioP41

Potential valueQ

Development potential Q1

Industry category Q11

Enterprise scale Q12

Credit ratingQ13

Cooperation potential Q2

Already the species number of consumer bank products Q21

Need and the number of species have not purchased the productQ22

A. The current value of the target customer

Customer's current value is the customer at present consumption bank products or services to create profit value for Banks [2]. According to the characteristics of the products and services, The major indexes by assets, liabilities business value business value, middle business value and transaction cost composition.

(1)Asset business value. The business assets including working capital loans and project loans, although bill discount is also a kind of loans to commercial Banks, but it has many differences form general loan in time limit, also in interest and liquidity. Bill discount income will be classified as intermediate business in this article. In the line of credit, the loans may be more than one , we use three indicators to measure, average daily total loans, average interest rates and loan closing period.

(2) Liability business value. Customer deposits are the main form of liability business, the business value of liabilities from the total average daily deposits, the average interest rate of deposits and deposit comprehensive standard deviation duration of four aspects to consider.

(3) Intermediate business value. Reflect that customers through the use of intermediate business products or services to create value, such as customer billing using the tools provided by the banks pay fees and discount income, but also consider the number of transactions of the customer in the investigated period.

(4) Transaction costs. Banks to obtain and retain customers is not without cost, but as other businesses need to pay the cost, the customer created value for the banks higher, does not mean that the higher the net profit for the enterprise, and only takes into account the cost of the customer how much, in order to create the current

value of the customer to get a comprehensive and objective evaluation. Banks in the course of business based on business characteristics and marketing costs and other factors determine the cost rate for each variety of businesses, combined with the structure of deposit and loan customers can calculate the weighted average cost of the customer's rate.

B. The potential value of the client indicators

The potential value of the clients is to point to the customer for any one of the same line of business within the territory of the enterprise may be the benefits. This value is independent of any outside the enterprise, for any companies are no differences. When enterprise and customer transaction, the enterprise through the efforts to put part of the customer potential value into real value [3]. Already transformed the potential value formed the current value of the customer; the other potential value is directly decided to the upper limit of appreciation potential in customer’s future value. The potential value of the customer mainly by customers own attribute decision mainly from the potential development and cooperation potential two aspects.

(1) Development potential. It measures the customer whether to conform to the bank policy guidance. Such as, at present, many banks to develop small business credit, restrict real estate credit business. The index mainly from the sectors, firm size, credit rating and other aspects of evaluation.

(2) Cooperation potential. It is used to evaluate the possibility of additional customer consumption, specific indicators are the number of products which customer have spend and the number of product which customer need and have not buy.

III COMMERCIAL BANK CUSTOMER VALUE

COMPREHENSIVE EVALUATION MODEL

Starting from the last level indicator, each index value multiplied by the weight of each draw on a comprehensive indicator of the value, and so on, calculates current value and potential value of the customer, and on this basis, calculated the total value of the customer. The total value of the customer set E, the current value of P the potential value of Q, the weight of w v can get the combined value of commercial bank customers evaluation model is:

E=wP +vQ (1)

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P= wi( wijPij) (2)

Q= vi( vijQij) (3)

The weight of each index said to the important degree of superior index, scientific and reasonable weight is extremely important factors in evaluation process, this paper in determining the weights of each index used the analytic hierarchy process, invited experts to discuss the comprehensive evaluation index system, obtains the weight of each layer of the index ,as shown in table .

TABLEII COMMERCIAL BANK CUSTOMER VALUE

COMPREHENSIVE EVALUATION INDEX WEIGHT DISTRIBUTION LIST

level 1 level 2 level 3

w=0.56 w1=0.28 �w1j=1(j=1/2/3) w11=0.48 w12=0.25 w13=0.27

w2=0.34 �w2j=1(j=1/2/3) w21=0.50 w22=0.21 w23=0.29

w3=0.25 �w3j=1(j=1/2/) w31=0.54 w32=0.46

w4=0.13 �w4j=1(j=1) w41=1

v=0.44 V1=0.52 �v1j=1(j=1/2/3) v11=0.35 v12=0.21 v13=0.44

V2=0.48 �v2j=1(j=1/2) v21=0.55 v22=0.45

Customers in the indicator of comprehensive score are subdivision the customer's final basis. For all kinds of index score can be additive, this paper uses classification rules to give the hierarchy of values for each indicator, to give each class to determine a score. The customer value fell on one level, the customer in the index for the corresponding are rated, according to this rule, the end all index values of all transformed into the form of are rated in order to comprehensive weighted evaluated.

IV COMMERCIAL BANK CUSTOMERS CLUSTER

SUBDIVISION

At present the main clustering algorithm has division method, level method, based on grid method, based on the model of the algorithm, based on the method of density, etc[4][5]. Level method relies on the given conditions, in the method based on grid depends on the threshold value of filter conditions set, based on model algorithm depends on the assumption of the model, a based on density of the algorithm relies on set the density of the threshold. For users, these conditions or the threshold sure is hard, and divided law depends on users want to ultimately divided the grouping of several K. For bank customer segmentation, K value for the determination of the breakdown of the particle size

depends on customers hope, the operation is more easily. Therefore, the K-Means division method is employed to clustering analysis, segmentation procedure is as follows:

(1) Two-dimensional cross-clustering, resulting in an initial customer base. According to the previous description, the use of K-Means clustering method, the customer's current value and added value to do two-dimensional cross-clustering, clustering produces an initial customer base calculation, credited to the customer segmentation data mart.

(2) Customer base adjusted to produce the final customers. Customer base the adjustment process is a process to constantly adjust the value of K, a K value that is selected for clustering analysis, the need to judge the results of cluster analysis to determine the reasonableness of the classification of customers, whether it has achieved the desired segment size. If you need to adjust accordingly below the expected value of K, and then re-clustering, after repeatedly until a satisfactory segmentation results[5].

V APPLICATION EXAMPLES

This article collected 100 corporate clients to conduct empirical research from a branch company of a city commercial bank, time limit for samples from January 1, 2010 through December 31, 2010, data from the public balance sheet and the credit inquiry system of the bank.

(1) The data collection. This paper collected deposit and loan data, transaction data and customer service date, used to calculate the value of customer segmentation. Deposit and loan data by sorting the table to obtain, customer’s transaction history to get from the bank's settlement system, customer service data to inquires the bank credit management system, as well as consult relevant employees.

(2) The data arrangement. The basic data collected samples according to the principle of hierarchy dimensionless calculation, data statistics to table .

TABLEIII T DESCRIPTION OF SAMPLE DATA

Index Max Min Average Standard

deviation

P11 93.96 12.50 33.06 19.86

P12 96.64 20.85 59.57 12.17

P13 90.00 20.00 43.00 15.28

P21 94.58 8.65 48.32 20.38

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P22 73.25 0 53.21 10.26

P23 95.63 18.25 30.54 16.31

P31 90.61 0 38.74 18.95

P32 93.27 8.36 36.00 19.36

P41 92.56 24.73 47.93 13.51

Q11 91.45 26.39 64.73 21.36

Q12 95.71 17.54 52.34 24.65

Q13 96.85 20.18 73.61 13.93

Q21 90.20 9.80 25.41 17.56

Q22 92.43 35.79 53.68 14.62

(3) Build customer segmentation data mart. AHP to get the weight of the index system, and to look for each level 2 index values and the current value and potential value, build a simplified customer segmentation data mart.

(4) Clustering subdivision. Use SPSS11.5 statistical software, according to K-Means method to establish the data mining model. In customer dimension, doing two-dimensional cross-cluster to the customer's current value and potential value, plans to produce eight customer base(K=8). After the data mining, and produced the preliminary customers division, as table .

TABLEIV SAMPLE CUSTOMER SEGMENTATION CLUSTERING

PRELIMINARY RESULTS

Customer base

current value Potential value Proportion of the customer

number

limit lower limit lower

1 1.58 0.00 3.49 0.00 5%

2 3.48 0.05 4.58 0.00 9%

3 32.68 10.47 41.69 17.34 21%

4 57.63 30.93 64.57 3.84 15%

5 98.35 20.31 10.76 4.65 18%

6 4.62 0.00 98.27 5.72 14%

7 95.87 53.75 97.02 39.51 14%

8 21.43 6.09 99.14 18.54 4%

From the above produce customer groups can be found, it is very small difference between customer base 1 and 2, the current value and potential value is lower. Customer’s current value and potential value of base 3 and 4 is in the middle and lower level. For customer base 5 , the current value is high and the potential value is relatively low. For customer base 6 and 8, their current value is relatively low and potential value is high. For customer base 7, the current value and potential value

both are very high. From the clustering results look, can be summarized as roughly five types of customers, so K value adjustment for 5, to produce the new customer base cluster, such as shown in table .

TABLEV SAMPLES TO CUSTOMERS AFTER CLUSTERING

RESULTS

Customer base

current value Potential value Proportion of the customer number

limit lower limit lower

41.53 10.47 53.89 16.48 34%

98.35 40.62 99.02 62.53 15%

3.45 0.00 2.67 0.00 13%

19.78 4.37 93.68 35.26 23%

94.76 23.68 15.36 4.37 15%

(5) Marketing strategy. Both current value and potential value of customer base are in the middle and lower reaches, the bank should give their more attention to have more understanding, but also the implement of the cross selling marketing strategy, such as providing new services, etc. Customer base has high current value and potential value, this kind of customer is of high value, is the most important customer, bank should put the main source into development and keep the customer relationship, fully understand the customers, to provide the high quality service one-on-one. Customer base has low current value and potential value, the customer doesn't have to again the investment of resources, finish each transaction step by step, it is necessary to consider whether it should be give up located in the area of customer. The current value of customer base is lower, but potential value is high, this kind of customer is the important development and cultivate object for bank, implements the effective marketing strategy to them, they will bring higher profit margin to bank in the future. Customer base has high current value, but potential value is low, this kind of customer and bank current volume is larger, but it is unlikely to obtain greater profits due to the limited strength of the customer, the bank should try to maintain good relationship with the customer to avoid customer churn, but it is not necessary to invest too many resources.

VI CONCLUSIONS

This paper constructed the customer value comprehensive evaluation model based on commercial bank customers management features, and put forward two dimensional clustering subdivision methods based on

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current and potential value. Not only can help managers identify high-quality customers, and according to their ability to formulate a quality customer training program, put the limited marketing resources on the most valuable or most potential customers. Finally, in a city commercial bank as an example, the method described the practical application of proof, proved the feasibility of the proposed method.

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