Advances in Banking Technology and Management: Impacts of ICT and CRM

Advances in Banking Technology and Management: Impacts of ICT and CRM

Vadlamani Ravi (Institute for Development and Research in Banking Technology, India)
Indexed In: SCOPUS View 1 More Indices
Release Date: October, 2007|Copyright: © 2008 |Pages: 380|DOI: 10.4018/978-1-59904-675-4
ISBN13: 9781599046754|ISBN10: 159904675X|EISBN13: 9781599046778|ISBN13 Softcover: 9781616926434
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Description

Banking across the world has undergone extensive changes thanks to the profound influence of developments and trends in information communication technologies, business intelligence, and risk management strategies. While banking has become easier and more convenient for the consumer, the advances and intricacies of emerging technologies have made banking operations all the more cumbersome.

Advances in Banking Technology and Management: Impacts of ICT and CRM examines the various myriads of technical and organizational elements that impact services management, business management, risk management, and customer relationship management, and offers research to aid the successful implementation of associated supportive technologies.

Topics Covered

The many academic areas covered in this publication include, but are not limited to:

  • Adoption and diffusion of Internet banking
  • Banking technology and management
  • CRM process
  • Data mining for credit storage
  • Data Warehousing
  • Engineering banking applications
  • Information assurance
  • Internet banking methodologies
  • Logical data model
  • M-commerce fraud management
  • M-payment solutions
  • Neural Network Models
  • Risk Management
  • Service Quality
  • Smart card technology
  • Strategic Decision Making
  • Training algorithm
  • Value-at-risk

Reviews and Testimonials

This book attempts to demystify 'banking technology' and offer a much broader meaning and more realistic and operationally sufficient perspective on 'banking technology'.

– Vadlamani Ravi, Institute for Development and Research in Banking Technology, India

Ravi has selected 18 papers on the role of information and communication technology in banking and data mining tools for customer relationship management. Topics include customer acceptance of internet banking in Greece, collaboration among smart card innovators, m-commerce fraud management, data mining for credit scoring, and forecasting foreign exchange rate using SVR-based neural network ensemble.

– Book News Inc. (2008)

Table of Contents and List of Contributors

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Preface

Although ‘banking’ is an old activity and has its roots in economics, finance and commerce, the word ‘banking technology’ is of recent origin. To many people ‘banking technology’ means the use of computers and related hardware to streamline and automate banking operations. This book attempts to demystify the word ‘banking technology’ and offers much broader meaning and more realistic and operationally sufficient perspective on ‘banking technology’. Universally conducting efficient banking operations and associated business involves managing (i) the information and communications technology that drives the banks’ core business (ii) the customer relationships and (iii) risks associated with conducting its business with customers and other banks and financial institutions. Therefore the book is categorized according to the three focal areas: (i) Services management (ii) Business management and (iii) Risk management.

Successful banks all over the world have invested considerably in information and communications technologies, which in turn would increase banks’ profits considerably on one hand and improve the convenience and comfort levels of their customers in doing business with them on the other. Further, such banks are very sensitive to the risks they face in dealing with money in the form of credit risk, or market risk or operational risk. Banks continuously embrace, with great fervor, the latest developments in information and communication technologies and customer relationship management in order to service customers better and reap more profits. If banks employ cutting edge technologies to service their customers effectively and efficiently, regulatory requirements such as Basel II also force the banks to implement these technologies to enable uniform banking services throughout the world.

This book brings together research contributions from several academics and industrial professionals in all the three aspects mentioned above and conveys the message that banking technology and management emerged as a new discipline in its own right over the last decade and half.

The foreword of the book by Rammohan Rao, Dean, Indian School of Business highlights the nature of the demand and supply equation that exists between the banks, as a service provider and the customers and the resulting explosion of research opportunities. It finds the division of chapters in to three areas to be operationally sufficient.

In Chapter 1, Ravi introduces an overview of banking technology, its various facets and the evolution of banking. Banking technology is introduced as a consortium of several disparate disciplines such as finance and risk management, information technology, communication technology, computer science and marketing science. The influence of all these disciplines on various aspects of modern banking operations is clearly explained. Nowadays, banks and their customers are in a win-win situation where banks offer more and more services under one roof with impeccable reliability in a fairly secure manner resulting in more profits and customers on the other hand can feel the pleasure and convenience of banking.

In Chapter 2, Bellini and Pereira discuss various aspects of service quality for customer in banking industry. They study the quality of banking services on the basis of the perception of 11,936 customers of a major Brazilian bank. They identified five drivers that could explain the customer satisfaction in an indirect way. They are (1) business and financial transactions (2) customer relationship (3) information technology (4) branch and (5) image. They argued that these factors would help bank executives make strategic decisions in addressing bank’s customers.

In Chapter 3, Carr reviews important theories in information systems viz., The Diffusion of Innovations Theory, the Theory of Planned Behavior and the Technology Acceptance Model, that explain the adoption and diffusion of Internet banking. Empirical works investigating these theories are discussed. It also highlights the theoretical and methodological limitations of these models. Approaches that complement or challenge positivistic methodologies that are interpretive are presented in a case study. This chapter also discusses future trends in Internet banking that could include populations not included in the modern electronic financial systems.

In Chapter 4, Koumaras et al., describe the factors that affect the customer acceptance of Internet Banking with the help of a case study of ALPHA Bank in Greece, which pioneered in introducing and applying e-banking services in Greece. They also present a thorough analysis of the case study with the help of factor analysis on customer-questionnaires in order to quantify the various variables that affect the use of an Internet Banking System. They infer that although internet banking in Greece is steadily penetrating, factors like security, ease of use and perceived usefulness of a system continue to affect the customer’s decision to adopt an Internet Banking System.

In Chapter 5, M’Chirgui and Chanel present the electronic purse as one of the latest smart card applications. This chapter explores and models the factors - economic, technological and social - and forces driving the adoption and use of the Moneo electronic purse in the South of France. An empirical study presented analyses the determinants of the probability of adoption for consumers and retailers and of the frequency of use for consumers. They found that the frequency of use of Moneo is influenced by relative advantage, cost, visibility, security, income and gender. Finally, the reasons why Moneo seems to have met with failure are determined and solutions to help reach the required critical mass are proposed.

In Chapter 6, Patra proposes a novel hybrid service-oriented agent architecture for developing software in banking industry as a possible solution to the growing issues of inter-and intra- bank operations. He cites the issues of Interoperability, scalability, maintainability and security as the challenges for the banking industry. He argues that the hybrid architecture can seamlessly integrate business functions across organizational boundaries. He illustrates the proposed service-oriented agent architecture with the help of a few banking applications.

In Chapter 7, Wonglimpiyarat, introduces smart card (ATM/Cash cards, Credit cards, EFTPOS/Debit cards) application in banking industry as a system innovation, where several parties join hands together and make it a success. The chapter elucidates the network nature of smart cards. She argues that unless innovators in the smart card industry realize the advantages of collaboration the diffusion of smart cards may not happen.

It is well-known that internet or electronic banking is vulnerable to cyber threats and attacks that would help the hacker or fraudster steal the whole customer’s data in no time. Consequently, information assurance is of paramount importance to e-banking services. In chapter 8, Gupta et al., present an interesting state-of-the-art survey on the important issue of information assurance in electronic or internet banking security. It highlights the critical aspects of information assurance that would be needed for design, development, and assessment of an adequate electronic security infrastructure.

After internet banking the next big wave in e-banking is mobile payment systems (m-payment systems) and mobile commerce (m-commerce). The paradigmatic shift from physical to virtual payments systems has been beneficial to both customers and merchants. For customers it affords ease of use. For mobile operators, mobile payment systems facilitate to consolidate their central role in the m-commerce value chain. Financial organizations view mobile payment and mobile banking as a new way of providing added convenience to their customers along with an opportunity to reduce their operating costs. Chapter 9 by Nambiar and Lu presents all these issue along with an overview of competing mobile payment solutions that are found in market today. It also reviews different types of mobile frauds in the m-commerce environment and solutions to prevent such frauds.

In Chapter 10, Murali et al., present ideas and concepts taken from marketing research literature for a successful CRM implementation in retail banking. They describe a framework for conceptualizing, operationalizing and measuring CRM process implementation and illustrate its use to identify activities that must be performed for successful CRM. They explain the proposed framework in the context of a case study of CRM implementation at a European Bank. They also describe the importance of customer response to self-service banking technologies to CRM managers at banks. This chapter is a contribution on the operational and managerial aspects of CRM.

In Chapter 11, Rajagopal discusses a model that analyzes the variables associated with customer value. It combines customer value, competitive efficiency and profit optimization through a set of linear equations The framework is based on the theory of competitive advantage and customer lifetime value, so as to maximize the potential of the organization to create and sustain satisfied customers. The chapter 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 concludes that there is increasing returns to scale in the bank services in relation to the banking products, new technology and customer value.

In Chapter 12, Venkat Narayanan presents the fundamental concepts of a data warehouse and its usefulness in banks. He argues that they are important for banks to achieve sustainable competitive advantage against competing banks. Using data warehousing and analytics it is possible for the banks to understand the behavior of their customers, which in turn helps them improve interaction with customers. They argue that the same infrastructure can be used for multiple business applications.

In Chapter 13, Venkat Narayanan presents the implementational details of Data Warehousing and Analytics in banking industry with the help of a real-life case study. Data warehouse represents one of the foremost technologies that can be used by banks to obtain sustainable competitive advantage. He argues that adopting the right implementation methodology is important to ensure successful implementation and describes alternate implementation methodologies, typical challenges in implementation and critical success factors.

While developing data warehouses for banks, an important aspect is the development of a logical data model and the entire success of a data warehouse depends heavily on, among other things, the logical data model conceived and used. In Chapter 14, Mauser describes a data model called SKO-Datenmodell, for a savings bank, Sparkassen-organization, in germany. The data model with 17490 well-defined modeling objects was initially developed 15 years ago based on the Financial Services Data Model (FSDM) of IBM. The SKO-Datenmodell is specially designed for Sparkassen-organization. The different levels of the SKO-Datenmodell and their uses are described in this chapter.

In Chapter 15, Ravi et al., present an algorithm to train radial basis function neural networks (RBFN) in a semi-online manner and demonstrate its effectiveness on bankruptcy prediction in banks. It employs the online, evolving clustering algorithm in the unsupervised training part of the RBFN and the ordinary least squares estimation for the supervised training part. They compared its performance with multi layer perceptron, Adaptive neuro-fuzzy inference system (ANFIS), TreeNet, Support vector machine (SVM), Radial basis function neural network (RBFN), Rough set based expert system (RSES) and Orthogonal RBFN. They concluded that the proposed semi-online algorithm for RBFN is better than other neural networks when area under the ROC curve (AUC) is taken as the performance metric.

In Chapter 16, Lean Yu et al., present a thorough literature review on the applications of neural network models to foreign exchange rates forecasting. Further, they propose a novel support vector regression (SVR) based nonlinear ensemble forecasting model for foreign exchange rates forecasting. The ensemble comprises single neural network models as its constituent members, which are selected based on conditional generalized variance approach. For illustration purpose, four typical foreign exchange rate series are used for testing. He compared several nonlinear ensemble methods for forecasting foreign exchange rates with the proposed SVR based ensemble with respect to the measures such as normalized root mean square error and directional change statistics. Results obtained indicate that the proposed nonlinear ensemble model can improve the performance of foreign exchange rates forecasting.

In Chapter 17, Samanta presents a procedure for 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. When returns are normal variates, it is a very simple task. But it is well known that financial market returns seldom follow normal distribution. So, one has to identify suitable non-normal distribution for the returns and find out the percentile of the identified distribution. The class of non-normal distributions, however, is extremely wide and one has to identify the best distributional form from such a wide class. In order to handle the non-normality, he adopts a transformation-based approach proposed in Samanta (2003). The performance of the transformation-based VaR models is compared with two widely used VaR models. He concludes that the transformation-based approach is a useful alternative.

The usefulness of data warehouse and data mining in banking industry is very well-known. In chapter 18, Felsovalyi and Courant highlight the importance of data mining in risk management in lending and credit card activities in Citi group. They focus attention on corporate lending based on Citi group’s own practices. They describe various aspects of risk management and assessment, early warning models, measuring loss and also consumer lending with reference to credit cards.

In Chapter 19, Bose et al., present an overview of credit scoring models in banking and the applications of data mining in credit scoring. The applications of credit scoring presented include credit card, mortgage and small business lending. A detailed discussion and review of the use of various data mining techniques to credit scoring is presented. A method to estimate the default probability is also presented. The chapter concludes by highlighting the merits and demerits of credit scoring.

This book is useful to the undergraduate and graduate students of MBA program in Financial Engineering on any University. The book can also be used as reference book by researchers of Financial Engineering and banking executives.

Author(s)/Editor(s) Biography

Vadlamani Ravi is working as an assistant professor at the Institute for Development and Research in Banking Technology, Hyderabad. He obtained his PhD in the area of soft computing from Osmania University, Hyderabad and RWTH Aachen Germany (2001) under a DAAD Long Term Fellowship; his MS (science and technology) from BITS, Pilani (1991), and his MSc (statistics & operations research) from IIT, Bombay (1987). Prior to joining IDRBT he worked as a faculty member at the Institute of Systems Science, National University of Singapore (April 2002-March 2005). Earlier, he worked as assistant director from 1996-2002 and scientist C from 1993-1996 respectively at the Indian Institute of Chemical Technology, Hyderabad, and as scientist B and scientist C at the Central Building Research Institute, Roorkee (1988-1993). He is listed as an expert in soft computing by TIFAC, government of India. In a career spanning 19 years, Dr. Ravi has worked in several cross-disciplinary areas and published more than 40 papers in refereed international/national journals/conferences and invited chapters in edited volumes. Further, he is a referee for several international journals including Applied Intelligence, Computes and Operations Research, Asia-Pacific Journal of Operational Research, IEEE Transactions on Fuzzy Systems, IEEE Transactions on Reliability, European Journal of Operational Research, and International Journal of Computational Intelligence.

Indices