Association Rules Model Of E-banking Services
Author(s)
V. Aggelis
Abstract
The introduction of data mining methods in the banking area although conducted
in a slower way than in other fields, mainly due to the nature and sensitivity of
bank data, can already be considered of great assistance to banks as to prediction,
forecasting and decision making. One particular method is the investigation for
association rules between products and services a bank offers. Results are
generally impressive since in many cases strong relations are established, which
are not easily observed at a first glance. These rules are used as additional tools
aiming at the continuous improvement of bank services and products helping
also in approaching new customers. The scope of this paper is the presentation of
a model which discovers and determinate such rules concerning e-banking using
different methods.
Keywords: data mining, e-banking, association rules, a priori, generalized rule
induction.
1 Introduction
Determination of association rules concerning bank data is a challenging though
demanding task since:
• The volume of bank data is enormous. Therefore the data should be
adequately prepared by the data miner before the final step of the application
of the method.
• The objective must be clearly set from the beginning. In many cases not
having a clear aim results in erroneous or no results at all.
• Good knowledge of the data is a prerequisite not only for the data miner but
also for the final analyst (manager). Otherwise wrong results will be
produced by the data miner and unreliable conclusions will be drawn by the
manager.
Keywords
data mining, e-banking, association rules, a priori, generalized rule induction.
Related Book
Other papers in this volume
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