Data Mining and the Banking Sector

In this chapter, we will discuss a few areas of this vast and important phenomenon, following the outline below. We will be focusing on corporate lending, although data mining permeates all aspects of today’s banking. We will discuss corporate lending based on Citigroup’s own practices, and the rest of the subject will be based on practices generic to the industry.

Data Warehousing and Analytics in Banking

In an increasingly competitive market, banks are constantly searching for sustainable competitive advantage to help them maintain their edge against competition. Over the years, banks have tried various drivers for competitive advantage, none of which were sufficient barriers for competitors. Understanding the behavior of their customers and using this knowledge to drive the interaction with customers is the most sustainable competitive advantage banks can obtain. Data Warehousing and Analytics provide banks with the ability to obtain customer knowledge and the same infrastructure can be used for multiple business applications.

Technology and Customer Value Dynamics in the Banking Industry

This paper attempts to critically examine the available literature on the subject, discuss a model that provides a framework for analyzing the variables associated with customer value, and to identify potential research areas. The paper argues through a set of linear equations that maximizing customer value which is interdependent factor for technology adoption and profit optimization in the banks need to be backed with appropriate economic parameters for attaining competitive efficiency and optimizing profit. The framework of the construct is laid on the theory of competitive advantage and customer lifetime value, so as to maximize the potential of the organization and all its subsystems to create and sustain satisfied customers. The paper draws theoretical impetus from new technologies in banking services such as mobile banking in the North American region and discusses the technology led marketing process towards optimizing profit. The discussion in the paper also analyzes the main criteria for successful internet-banking strategy and brings out benefits of e-banking from the point of view of banks, their technology and customer values and tentatively concludes that there is increasing returns to scale in the bank services in relation to the banking products, new technology and customer value.

Engineering Banking Applications

The banking industry has undergone a major change in recent years. Global competition has forced the industry to be more agile and customer focused in all its services. Banks can no more function in isolation but have to operate cutting across physical boundaries. Interoperability, scalability, maintainability, and security are the upcoming challenges for the banking industry. This has enthused software architects to develop suitable software development paradigms that can seamlessly integrate business functions across organizational boundaries. This chapter envisages a hybrid approach that uses the service-oriented paradigm along with the software agent technology as a possible solution to the growing issues of inter-and intra- bank operations.

Introduction to Banking Technology and Management

This chapter introduces banking technology as a confluence of several disparate disciplines such as Finance (including risk management), Information technology, Computer Science, Communication technology and marketing science. It presents the evolution of banking, the tremendous influence of information and communication technologies on banking and its products, the quintessential role played by computer science in fulfilling banks’ marketing objective of servicing customers better at a less cost and thereby reap more profits. It also highlights the use of advanced statistics and computer science to measure, mitigate and manage various risks associated with banks’ business with its customers and other banks. The growing influence of customer relationship management and data mining in tackling various marketing related problems and fraud detection problems in banking industry is well documented. The chapter concludes by saying that the banking technology discipline is all set for rapid growth in future.

ON THE NEW TRANSFORMATION-BASED APPROACH TO VALUE-AT-RISK

This chapter deals with the measurement of Value-at-Risk parameter for a portfolio using historical returns. The main issue here is the estimation of suitable percentile of the underlying return distribution. If returns were normal variates, the task would have been very simple. But it is well documented in the literature that financial market returns seldom follow normal distribution. So, one has to identify suitable distribution, mostly other than normal, for the returns and find out the percentile of the identified distribution. The class of non-normal distribution, however, is extremely wide and heterogeneous, and one faces a decision-making problem of identifying the best distributional form from such a wide class of potential alternatives. In order to simplify the task of handling non-normality while estimating VaR, we adopt the transformation-based approach used in Samanta (2003). The performance of the transformation-based approach is compared with two widely used VaR models. Empirical results are quite encouraging and identify the transformation-based approach as a useful and sensible alternative.

M-Payment Solutions and M-Commerce Fraud Management

Mobile security and payment are central to m-commerce. The shift from physical to virtual payments has brought enormous benefits to consumers and merchants. For consumers it means ease of use. For mobile operators, mobile payment presents a unique opportunity to consolidate their central role in the m-commerce value chain. Financial organizations view mobile payment and mobile banking as a way of providing added convenience to their customers along with an opportunity to reduce their operating costs. The chapter starts by giving a general introduction to m-payment by providing an overview of the m-payment value chain, lifecycle and characteristics. In the second section, we will review competing mobile payment solutions that are found in the market-place. The third section will review different types of mobile frauds in the m-commerce environment and solutions to prevent such frauds.

Data Mining for Credit Scoring

Credit scoring is one of the most popular uses of data mining in the financial industry. Credit scoring can be defined as a technique that helps creditors decide whether to grant credit to customers. With the use of credit scoring decisions about granting of loans can be made in an automated and faster way in order to assist the creditors in managing credit risk. This chapter begins with an explanation of the need for credit scoring followed by the history of credit scoring. Then it discusses the relationship between credit scoring and data mining. The major applications of credit scoring in three areas, which include credit card, mortgage and small business lending, are introduced. This is followed by a discussion of the models used for credit scoring and evaluation of seven major data mining techniques for credit scoring. A study of default probability estimation is also presented. Finally the chapter investigates the benefits and limitations of credit scoring as well as the future developments in this area.

Smart Cards in the Banking Industry

This chapter is concerned with the challenges of smart cards as a system innovation in the banking industry. System innovation is the innovation which cannot be adequately introduced by a single entity and is likely to fail unless two or more parties collectively accept the innovation. The study aims to understand the network system nature of smart cards. The comparative study of previous bank card innovations (ATM/Cash cards, Credit cards, EFTPOS/Debit cards) suggests a collaborative approach to reduce the risk of competitive innovation in the case of smart cards. However, the current situation reflects the competition among the powerful players. Unless innovators in the smart card industry see the benefits of collaboration, the diffusion of smart cards may not happen. Innovators may use an empirical analysis in this chapter to define strategic approach for their plan to compete in the smart card industry.

Customer Acceptance of Internet Banking Services in Greece

This chapter deals with the factors that affect the Internet Banking customer acceptance. More specifically, it is examined the case of ALPHA Bank branch in Greece, which is a pioneer in introducing and applying e-banking services in Greece. In this framework, the chapter performs a factor analysis based on the gathered results provided by customer-questionnaires in order to quantify the various parameters that affect the use of an Internet Banking System. The findings of the analysis show that although IBS in Greece is steadily increasing its penetration, factors like security, ease of use and perceived usefulness of a system continue to play a major role on the final decision of the customer to adopt an Internet Banking System.