Academic literature on the topic 'Bank client segmentation'

Abstract Segmentation in banking for the business client market is traditionally based on size measured in terms of income and the number of employees, and on statistical clustering methods (e.g. hierarchical clustering, k-means). The goal of the paper is to demonstrate that self-organizing maps (SOM) effectively extend the pool of possible criteria for segmentation of the business client market with more relevant criteria, including behavioral, demographic, personal, operational, situational, and cross-selling products. In order to attain the goal of the paper, the dataset on business clients of several banks in Croatia, which, besides size, incorporates a number of different criteria, is analyzed using the SOM-Ward clustering algorithm of Viscovery SOMine software. The SOM-Ward algorithm extracted three segments that differ with respect to the attributes of foreign trade operations (import/export), annual income, origin of capital, important bank selection criteria, views on the loan selection and the industry. The analyzed segments can be used by banks for deciding on the direction of further marketing activities.

Under conditions, when there is very intense competition, individualization of services is the most reasonable way to implement the client-oriented approach in banking. The article emphasizes the following organization and management tools needed for the successful individualization of corporate customer service in a commercial bank: deep market segmentation along with a selection of key clients considering their actual and potential importance for the bank, the development of flexible banking packages for sub-segments as part of banking services, the adoption of the institution a personal client's manager, staff development at all levels of the bank organizational structure in pursuit of internal marketing. The systematic use of these tools will allow a commercial bank to build partnerships with corporate clients, to raise the level of customers' satisfaction and loyalty, to ensure sustainability of interaction with the key customers that determine the essential characteristics of the banking business in the long term.

The This paper studies bank customers segmentation problem. Improved Apriori mining algorithm is a kind of data mining technology which is an important method in bank customers segmentation. In practical application, the traditional algorithm has shortcomings of the initial values sensitive and easy to fall into local optimal value, which will lead to low accuracy rate of silver class customer classification. According to the shortcomings of traditional algorithm, this paper puts forward a bank customer segmentation method based on improved Apriori mining algorithm in order to improve the bank customer segmentation accuracy. Experimental results show that the algorithm can effectively overcome the traditional algorithms shortcomings of easy to fall into local optimal value, improve the customer classification accuracy, make mining results more reasonable, lay down different customer service strategies for different client base, improve effective reference opinions of bank decision makers, and bring more benefits for the bank.

This article covers the key management issues in the loan syndications banking business. A syndicated loan is provided to a borrower by a group of commercial or investment banks. The global syndicated loan market is from one perspective, the primary funding source for corporations and on the other — one of the leading businesses for the global banks. There exist some unique challenges that must be responded by banks from a managerial and strategic perspective to establish and maintain leadership in the important business due to the features, structures, and industrial organisation of the market. We first consider how the loan syndications business is structured in a global bank, its functions and competitive advantages. Then we discuss the ways banks can implement an effective strategy and maintain leadership and growth in the market. Finally, we propose solutions to dealing with commoditization in banking: (i) adding more value-added services to the client offering; (ii) bundling of services in order to realize cross-selling opportunities and maximize share-of-wallet; (iii) further segmentation and customization of the client base (by industry/relationship/services consumption). By adopting these strategies, banks can successfully fight the commoditization magnet and increase the profitability of their loans syndications businesses.

The longitudinal study of the most sophisticated decision support system (DSS) for the management of debit accounts provides new answers to the question of conformity in French banking. In 2003, the analysis of 45 observations and qualitative interviews showed that the advisor maintains his free appreciation of risk. However, even if conformity does not exist, the results on the modification range show that the DSS does exert an influence on user behaviour. In addition, the interpretation and acceptance of DSS recommendation are different according to the type of portfolio managed and how the work is organised. The less the financial advisor knows the client, the greater the influence of the DSS. Recent decisions regarding the division of labour for the management of lower segments heighten the risk that DSS used without knowing the client leads to more conformity, or at least to what we conceptualise as strategic conformity, and a taylorisation of services.

The purpose of the research is the definition of the dominant ideas of financial technologies in digital banking. The methods of theoretical generalization, qualitative, quantitative and correlation analysis, causality tests, description and explanation are used, which made it possible to establish the relationship between the volume of investments in financial technologies and the performance of the banking system, identify the areas of application of financial technologies in the activities of the bank, determine the dominant ideas of financial technologies in digital banking and to uncover the factors and prospects of intensifying the use of financial technologies in digital banking in Ukraine. Results of the research are to substantiate the impact of artificial intelligence, biometrics, cloud services, big data, blockchain and open banking services on digital banking. Due to financial technologies in digital banking, it is possible to generate and store large amounts of data, simultaneously analyze and apply the results of their analysis, provide personalized banking services, perform the functions of central storage of information about the client of financial and non-financial nature, which facilitates the effective investment and credit decision-making, as well as improving the level of information security of banking operations. Practical implications. Financial services markets are transformed by the impact of financial technologies. Development of financial technology instruments by non-banking institutions necessitates the identification of opportunities for their use in banks. The set of financial technologies used by banks forms the digital banking system, the development level of which is the main competitive advantage of the bank in the business environment. Digital banking is characterized by the continuity and security of banking services, which provide the consumer with the ability to receive them online anywhere around the clock, personalization of banking services, digital authentication of users and digitization of banking transactions with the replacement of paperwork. The use of financial technologies in digital banking enables to automate customer segmentation processes, reduce costs on payment transactions, optimize accounting, financial and tax accounting, improve customer service and expand your customer base while maximizing revenue in certain business segments. Value/originality. The basic spheres of the use of financial technologies in digital banking, as well as the factors and prospects of intensifying the use of their instruments in Ukraine are revealed. The main areas of use of financial technologies in digital banking are customer behavior analysis, transaction monitoring, customer identification and segmentation, fraud management, banking services personification, risk assessment and regulatory compliance, customer response analysis, process automation, financial advice, investment decision-making, trade facilitation, syndicated loan services, and P2P transfers. The prospects for developing financial technology tools in digital banking include strengthening the interaction between regulators, banks and financial technology companies, the increased use of biometrics, the development of neo-banking and open banking services.

Purpose The competition among banks in Taiwan is fierce. The financial services offered by banks are highly similar and banks attempt to devise a variety of marketing campaigns to gain brand preferences of bank clients. However, little research regarding bank marketing has applied the segmentation strategy to precisely target bank clients. The purpose of this paper is to explore the moderating roles of cognitive load and brand story style in the impact of bank clients’ affective orientation on brand preference of bank clients. Design/methodology/approach A total of 216 participants who have bank accounts in Taiwan were randomly assigned to a 2 (brand story style: underdog vs top dog) × 2 (cognitive load: low vs high) factorial design. An ANOVA was conducted to examine the interaction effects of affective orientation, cognitive load and brand story style on the brand preference of bank clients. Affective orientation of participants was measured by Affective Orientation Scale. Findings Results demonstrate that for bank clients with low and high affective orientation, advertisements characterized by cognitive load (low vs high) and brand story style (underdog vs top dog) will elicit differential brand preferences of bank clients. Originality/value This is the first research to examine the moderating effects of bank clients’ affective orientation, cognitive load and brand story style on brand preferences of bank clients. Specifically, this research takes up the call to apply bank clients’ personality traits to examine the impact of bank marketing on brand preferences of banks.

Nowadays, Big Data (BD) Analytics is receiving great attention in banking industry, considering the worthy data that have been stored for several decades, to reach the main targets of marketing by increasing the bank’s efficiency of studying their clients, knowing their feedback, in addition to promoting active and passive security systems. This study focuses on utilizing BD analytics to develop marketing intelligence systems. It aims to explore the big data as a valuable resource for Egyptian commercial banks, to improve the customer experience, customer segmentation and profiling, selling products based on profiling, and describing customer behavior. In order to develop the proposed system, data were collected from several banks of transaction performed in 2016, including a report on customer satisfaction, a procedure of analyzing customer satisfaction data, consisting of about 39,000 records of transactions for customers and a collection of about 4,000 records of transaction data for cardholders. These data were analyzed using Apache Hadoop to perform many tasks such as profiling the bank's clients to groups, customer segmentation based on client’s history, interest and habits, predicting customer behavior based on profiling, designing a new marketing strategy, and presenting the right offers to the bank's clients as individuals or as groups. It was concluded that BD analytics were very beneficial for achieving Marketing Intelligence in Banks.

Today, during the period of ongoing changes in the financial market, banks face the challenges of cost reduction, revision of the product line and more explicit customer segmentation. In the environment, corporate clients are also observed significant changes: there is a rotation of personnel change the development strategies of companies that entails new requirements for banking products. Can banks quickly adapt to new market conditions and optimize work with corporate clients using existing technologies and information systems? Besides, that will help improve growth. Corporate sales of banking products in the current conditions? These questions the author tries to answer in her paper.

Abstract This paper examines drivers of mobile banking adoption by analyzing large-scale transaction data of retail banking clients. We find that the overall demand for financial services is associated with faster mobile banking adoption. Moreover, customers who already use online banking services and show digital skills in their payment behavior, tend to adopt mobile banking faster. Also, adoption rates are higher among the young. Finally, the well-documented gender gap in mobile banking adoption appears to have vanished in recent years: towards the end of our period under review, men and women adopt mobile banking equally. Our results contribute to the literature by addressing novel research questions regarding the fastest growing banking channel. Moreover, our findings carry important managerial implications as they help bank managers in the customer segmentation process and the promotion of mobile banking services.