Magazine article Journal of Services Research

Profiling of Internet Banking Users in India Using Intelligent Techniques

Magazine article Journal of Services Research

Profiling of Internet Banking Users in India Using Intelligent Techniques

Article excerpt

INTRODUCTION

Internet banking is a new channel for the distribution of financial services through the Internet and the World Wide Web infrastructure. The Internet is now being considered as a strategic weapon - a competitive advantage that will revolutionize the way banks operate, deliver, and compete against one another. The Internet promises a revolution in retail banking of monumental proportions providing customers with new levels of convenience and flexibility. Internet banking allows customers to perform a wide range of banking transactions electronically via the bank's Web site. When first introduced, Internet banking was used mainly as an information presentation medium in which banks marketed their products and services on their Web sites. With the development of asynchronous technologies and secured electronic transaction technologies, however, more banks have come forward to use Internet banking both as a transactional as well as an informational medium. As a result, registered Internet banking users can now perform common banking transactions such as writing checks, paying bills, transferring funds, printing statements, and inquiring about account balances. Internet banking has evolved into a "one stop service and information unit" that promises great benefits to both banks and consumers. Internet banking would help banks present a potentially low cost alternative to brick and mortar branch banking.

From the consumers' perspective, Internet banking provides a very convenient and effective approach to manage one's finances as it is easily accessible 24 hours a day, and seven days a week. Besides, the information is current. For corporate customers, sophisticated cash management packages offered through Internet banking provides them with up to the minute information, allowing for timely funds management decisions. There are about four million computer users in India. The banking industry has tried to provide Internet banking services to its customers. However, customers have not adopted Internet banking in a big way in India.

Lack of trust in Internet banking has been identified as the key to the failure to adopt Internet banking (Araujo and Araujo, 2003; Castelfranchi and Tan 2001; Noterberg et al., 2003). Several studies have attempted to model technology adoption. In this paper, based on the antecedents to trust we identify significant variables that influence the adoption of Internet banking. After identifying key variables, we operationalize them in the form of a questionnaire. After collecting responses from a group of Internet banking users and non-users, four predictive classification models were built using intelligent techniques such as Classification and Regression Trees (CART 2005), Logistic Regression (Garson, 1998) Support Vector Machines (http://www.research.microsoft.com/users/jplatt/svm.html) and Neural Networks (Rummelhart and McClelland, 1986). The profile developed of users and non-users of Internet banking may be used to target segments of potential customers.

The rest of this paper is organized follows. The next section reviews existing trust models to identify key variables that affect adoption of Internet banking. Then the various methodologies that were used, the data collection and analysis via intelligent techniques are discussed. The results are followed by conclusions.

REVIEW OF LITERATURE

Theories such as Theory of Reasoned Action (TRA) (Lin and Wu, 2002; Gefem et al., 2003), Theory of Planned Behavior (TPB) (Matheison, 1991), Technology Acceptance Model (TAM) (Araujo and Araujo, 2003; Noteberg et al. 2003; Gefen et al., 2003, Matheison, 1991; Malhotra and Galleta, 1999) and Diffusion of Innovation Theory (DIT) (Loch et al; 2003) provide insight into usage of Internet banking. Significant variables from these theories are drawn to build predictive classification models. This work differs from Confirmatory Factor Analysis (Garson, 2005), which tries to validate the designed model and its reliability. …

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