A Porter Framework for Understanding the Strategic Potential of Data Mining for the Australian Banking Industry

A Porter Framework for Understanding the Strategic Potential of Data Mining for the Australian Banking Industry

Kate A. Smith (Monash University, Australia) and Mark S. Dale (Monash University, Australia)
DOI: 10.4018/978-1-59904-951-9.ch173
OnDemand PDF Download:
$37.50

Abstract

This chapter employs Michael Porter’s Five Forces model to understand the potential strategic value of data mining within the Australian banking industry. The motivation for examining the strategic potential of data mining is to counter balance the preponderance of process level arguments for adopting this technology (e.g., risk and fraud mitigation, market campaigns, etc.) with an industry level perspective of what the technology potentially means for competition between rival firms (i.e., industry behavior). In essence, this chapter explores how data mining can affect industry structure and attractiveness by assisting businesses such as banks defend themselves against forces such as those asserted by buyers, substitute products, new entrants, and suppliers. This chapter also explores the future implications of data mining for the banking industry, the operating models of those institutions and the underlying economics of the industry. The emergence of data mining presents banks with the opportunity to either continue to develop their core competencies around the design, manufacture, distribution and support of products and/or to develop critical competencies around customer relationship management. A possible “contract banking” model supported through the application of data mining is discussed.

Complete Chapter List

Search this Book:
Reset