MINISTRY OF EDUCATION AND TRAINING UNIVERSITY OF ECONOMICS HO CHI MINH CITY TO PHUC NGUYEN KHUONG CONSUMER ANALYTICS TOWARD DEVELOPMENT OF CROSS SELLING PRODUCTS AT RETAIL BANKING: AN APPROACH ON BIG DATA AT EXIMBANK MASTER THESIS Ho Chi Minh City – 2020 TIEU LUAN MOI download : skknchat@gmail.com MINISTRY OF EDUCATION AND TRAINING UNIVERSITY OF ECONOMICS HO CHI MINH CITY TO PHUC NGUYEN KHUONG CONSUMER ANALYTICS TOWARD DEVELOPMENT OF CROSS SELLING PRODUCTS AT RETAIL BANKING: AN APPROACH ON BIG DATA AT EXIMBANK Specialization: Business Administration Executive Business Administration Code : 8340101 TUTOR: ASSOC. TU VAN BINH Ho Chi Minh City - 2020 TIEU LUAN MOI download : skknchat@gmail.com COMMITMENT I assure you this is my own research. The figures and results stated in the thesis are honest and have not been published in any other works. I would like to assure you that all of the help for the implementation of this dissertation was thanked and the information cited in the thesis has been traced.
Trainees implement the thesis (Sign and write full name) TÔ PHÚC NGUYÊN KHƯƠNG TIEU LUAN MOI download : skknchat@gmail.com ABSTRACT Based on internal database as big data of the Eximbank, 3,527 active customers with the initial length of service more than 12 months, the method of data mining is concerned, in which the mathematic methods of K-Means of cluster, Tree Decision, and Association Analysis are applied. The findings show that consumers’ characteristics using services at EXIMBANK are various, in which staffs, directors as individual customers occupy a high proportion in total customers. Based on descriptive statistics, there are eight main products, such as VG (Visa Gold), VC (Visa Classis), MG (Master Gold), MS (Master Standard), VP (Visa Platinum), VV (Viva Violet Card), VA (Visa Auto Card), and others are concerned most by the customer, in which VG and VC are the two top cards used. Directors are more interested in VG card, while staffs concern VC card.
In addition, using two cards, called the main card and the extra card, is popular. This is a potential chance for the bank to develop cross-selling products, which the product bundle strategies are packed into groups. Based on the method Association Analysis, propobality of using two cards or three cards at the same time of customers are derived. This finding basically supports the bank to address cross-selling products of cards to customers.
To do this, recommendations of the strategies of bundle products are suggested in the thesis, together with implementation plans TIEU LUAN MOI download : skknchat@gmail.com TABLE OF CONTENTS COMMITMENT ABSTRACT TABLE OF CONTENTS LIST OF FIGURES LIST OF TABLES CHAPTER 1: INTRODUCTION. RATIONALE OF RESEARCH. OBJECTIVES OF STUDY. SCOPE AND LIMITATION.
3 Methods to analyze data. 5 CHAPTER 2: CONCEPTS CONCERNED AND ITS FRAMEWORK. 7 Remaining good relationships between the customer and retail banking .The concept of big data and its consideration in banking. Big data in Banking and its contribution.
9 Application of Big Data to investigate the customer’s spending habits. 10 Customer segmentation and review customer’s records. 10 The sales includes other services (service cross-selling). 11 Building a system to record customer feedback.
12 Flexible suggesting good services to customers. 12 TIEU LUAN MOI download : skknchat@gmail. CONCEPTS RELATED TO APPROACHED QUANTITATIVE METHODS. Customer Value Matrix Model.
Customer lifetime value based on RFM. Cross-selling products. 19 CHAPTER 3: BIG DATA OF BANKING INDUSTRY AND CONCEPTS APPROACHED………………………………………………………………………21 I. SITUATION OF EXIMBANK AND ITS BUSINESS.
BIG DATA AND ITS APPLICATION IN BANKING.PROFILE OF CUSTOMER.RMF AND MARKET SEGMENT. 33 Cross – Selling strategy. 38 Summary of chapter. 43 CHAPTER 4: CONCLUSION AND SOLUTIONS.
FINDING OF MARKET SEGMENTS. DETAILED CHARACTERISTICS BY MARKET SEGMENT. IDEAS OF MARKETING STRATEGY. EMPLICATION OF STATEGY.
TIEU LUAN MOI download : skknchat@gmail.com LIST OF FIGURES Figure 2.1: Customer value matrix and its description .2: Customer value matrix and its description.3: The diagram of proposed model .1: Share of investment in big data analytics by sector.2: Share of investment in big data analytics by sector.3: Position of customer .4: Type of products that consumers concerned .5: Length of service of active customers .6: Type of customers using services at the bank .7: Type of products that consumers concerned .8: Matrix of LOS and Recency .9: Market segments based on RFM .10: Result of Tree Decision of five market segments .11: Result of Association Analysis and its potential bundles.12: Characteristics of potential bundle product between MS and VA.13: Potential bundle strategy (MS-VA) by customer income.14: Characteristics of potential bundle product among VP, MS, and VA.15: Potential bundle strategy (VP-MS-VA) by customer’s income .16: Characteristics of potential bundle product among MG, VV, and VA .17: Potential bundle strategy (MG-VV-VA) by customer’s income .1: Ranges of account balance of customers .2: Marketing strategies suggested to the bank. 46 TIEU LUAN MOI download : skknchat@gmail.3: Type of product.4: Top prestigious banks in Vietnam. 48 LIST OF TABLES Table 1.1: Information of variables concerned 4 Table 2.1: Recency, Frequency and Monetary Score Description 14 Table 2.2: Presentation of customer value matrix 15 Table 4.1: Interest rate of top ten prestigious bank in Vietnam 49 Table 4.2: Plan of strategic implication 53 TIEU LUAN MOI download : skknchat@gmail.com 1 CHAPTER 1: INTRODUCTION I. RATIONALE OF RESEARCH Rapid development of information technology in the banking industry has created a big concern that the banks must think of how to explore internal data to serve competitive strategies.
In fact, currently, most banking institutions, insurances and financial services are attempts to adopt a new approach toward data mining to the development and innovation of services that they provide to customers. Like most other industries, big data analytics are going to be a major change to support business units to generate campaigns for a short term and long term strategies to attract more new customers, retain existing ones and fight against the competitors. Investing a big data system cause simulation that data mining is much concerned in the banking industry, because it supports to extract valuable information form huge amounts of data. Particularly it contributes into finding out consumer behavior and present a market situation picture of a firm.
However, it is not easy to explore big data of firms. Data scientists developed quantitative methods as mathematic approaches, such as descriptive and predictive analytics, etc. Nowadays, banks have realized the importance of customer relation, this is one of successful factors. However, challenges of how to retain most profitable customers and to reduce a churn rate are problematic.
To solve this problem, consumer behavior should be investigated and analyzed, which big data are a worth resource and quite helpful to measure and predict consumer behavior correctly. Therefore, the power of data is to derive utility across various spheres of their functioning, product across selling, regulatory compliance management, risk management, and customer service management. As we know, particularities of banks’ activities generate a huge amount of data from unstructured data, such as transaction history, customer to the unstructured data such as the customer’s activities on the website, or the mobile banking application on social networks. However, how to explore big data available is the most problem.
Although there are not few banks who recognize that and want to turn the big data available to the most effective weapon for the market competition, they are seemly facing problems of new system, skills, and so on. With changes in integration policies of Vietnam through information technology system, together with fire competition, more and more banks in Vietnam have paid more attention to investing a huge money for big data system and people capacity. For example, EXIMBAK is one of the banks, who is willing to pay money to structure data TIEU LUAN MOI download : skknchat@gmail.com 2 system very early. It realizes benefits of data warehouse to support business strategies.
In fact, the benefits of internal brought not the raise of the internal management efficiency, but also help increase the competitive advantages, maximize profits. Currently, the banks must be flexible for their plan toward activities of innovation, in term of capturing needs of customers and improving satisfaction and retention of customer. By the way, CRM is quite helpful and recognized for acquisition and retention of customers. As a result, the bank can get more opportunism to make long lasting and profitable relationships with customers.
To investigating big data system of the bank, Eximbank has offered a program of building capacity for staffs, who are directly related to data analytics and business development. In addition, the department of database is established to exploit internal database, which the role of an employee is placed in the ecosystem talent development. However, everything is seemly concerned and exploited more and more toward data mining, predictive analytics on customer behavior. OBJECTIVES OF STUDY - Presenting characteristics of consumers who are using services of banking - Analyzing history of transaction behavior of consumers - Identifying and developing market segments through consumer behavior - Developing developments of cross-selling products to increase benefits of customers toward customer retain.
RESEARCH QUESTIONS There are some questions concerned as follows (1) What are characteristics of consumer toward service usage at banking? (2) How do customers take transaction at the bank? (3) How is the market segment developed? (4) What are cross-selling product developments to increase benefits of customers to retain them? TIEU LUAN MOI download : skknchat@gmail. SCOPE AND LIMITATION The thesis only concerns on internal database as well as big data of Eximbank located in a district of Ho Chi Minh City. Due to the confidential information and secret information requirements, the name of district is asked to hidden. Even the study is not taken qualitative method into the study, because the author is the head/leader of the branch of Eximbank, what the thesis is done it is based on actual demand of the bank.
Its finding is actual expectation for the Eximbank’s business plan in the time coming. RESEARCH METHODOLOGY Data collection Data used are extracted from data warehouse of the bank. Because of security requested, this thesis is seriously asked to be confidential. Using information as well as findings of this study is not convinced, it must be responsible for who going to use that.
Data pre-processing is taken into account of the data mining process, because it improves the accuracy and efficiency of subsequent modeling (Han & Kamber, 2006). Activities of data pre-processing techniques are data cleaning, data transformation, data integration and data reduction, these are concerned, due to data quality. The database used in the study is extracted from data warehouse of the bank, which the period of study is 12 months, from January 1, 2019 to December 31, 2019. Accordingly, the database selected has 130,000 rows, equivalent to 3,527 customers.
This means one individual customer has more transactions during study, so the rows are more than the customer amount. As presented in table 1.1, 25 fields or variables are taken into account of the current study. Each one has a defined measurement, such as nominal, continuous, date, categorical. TIEU LUAN MOI download : skknchat@gmail.1: Information of variables concerned Name of variable Definition Measurement 1.
CIF ID of customer 2. Branch ID of branch 3.document ID of customer document 4. Type of customer Type of customer Nominal + Credit customer variable + Individual customer + family business customer 5. Access date Date to register service of customer date 6.
Approved date Date of documents approved date 7. Document score Score on initial documents of customer Continuous that the staff evaluates 8. Gender Gender of customer Nominal 9. Age Age in years Continuous 10.
Education Education of customer Nominal 11. Community Behavior community relations Nominal + Prestige + Good enough + Unknown 12. Marital status Marital status: Single and married Nominal 13. Job position Positions Nominal + Manager + Worker + Director + Office staff 14.
House ownership Status of house property of customers Nominal + Owned house TIEU LUAN MOI download : skknchat@gmail.