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Neural Networks in Business: Techniques and Applications aims to be an introductory reference book for professionals, students and academics interested in applying neural networks to a variety of business applications. The book introduces the three most common neural network models and how they work...

Over the last decade or so, we have witnessed neural networks come of age. The idea of learning to solve complex pattern recognition problems using an intelligent data-driven approach is no longer simply an interesting challenge for academic researchers. Neural networks have proven themselves to be a...

Forecasting future retail sales is one of the most important activities that form the basis for all strategic and planning decisions in effective operations of retail businesses as well as retail supply chains. This chapter illustrates how to best model and forecast retail sales time series that...

This paper describes a neural network modelling approach to premium price sensitivity of insurance policy holders. Clustering is used to classify policy holders into homogeneous risk groups. Within each cluster a neural network is then used to predict retention rates given demographic and policy...

The data mining activities studied in this chapter concern the early identification of potential high-value customers. Member stores can use this information to establish a close relationship with this select group of customers, thus reducing the chances of losing them. Traditionally, Japanese...

The aim of our work is to perform a market segmentation of the clients of Pousadas de Portugal, a network for over 40 high-end small hotels, ENATUR. The data for this work was provided by a sample of more than 2500 clients that filled in a given questionnaire. The segmentation is based on how often the...

The outline of the chapter is as follows. The section on direct marketing explains briefly what it is and discusses the target selection problem in direct marketing. Target selection for a charity organization is also explained. The next section discusses how neural networks can be used for building...

The World Wide Web has taken the retail industry by storm. In a short span of 5 to 6 years, millions of users around the globe have been introduced to the Web. Whether shopping for merchandise or simply searching for information, the Web has become the avenue of choice for consumers. According to a...

Corporate managers, business consultants, stock analysts, and academic researchers have long maintained that the strategic decisions of managers have a direct influence on firm performance. Although societal and economic trends, industry characteristics, and chance all influence performance, the...

In this case study, we apply the Self-Organizing Map (SOM) technique to a financial business problem. The case study is mainly written from an investor’s point of view giving much attention to the insights provided by the unique visualization capabilities of the SOM. The results are compared to results...

Some of the concerns that plague developers of neural network decision support systems include: (a) How do I understand the underlying structure of the problem domain; (b) How can I discover unknown imperfections in the data which might detract from the generalization accuracy of the neural network...

The core of the insurance business is the underwriting function. As a business process, underwriting has remained essentially unchanged since the early 1600’s in London, England. Ship owners, seeking to protect themselves from financial ruin in the event their ships were to be lost at sea, would seek...

This chapter describes the application of neural networks in foreign exchange rate forecasting between American dollar and five other major currencies: Japanese yen, Deutsch mark, British pound, Swiss franc and Australian dollar. Technical indicators and time series data are fed to neural networks to...

The use of neural networks represents a new approach to how this type of problem can be investigated. The economics and finance literature is full of studies that require the researcher to prespecify the exact nature of the relationship and select specific variables to test. In this study, we use a...

The pricing of options on futures is compared using conventional models and artificial neural networks. This work demonstrates superior pricing accuracy using the artificial neural networks in an important subset of the input parameter set.

This chapter examines the use of neural networks as both a technique for pre-processing data and forecasting cash flow in the daily operations of a financial services company. The problem is to forecast the date when issued cheques will be presented by customers, so that the daily cash flow...