Εφαρμογές εξόρυξης γνώσης στον τραπεζικό κλάδο - Πρόβλεψη απάτης σε συναλλαγές πιστωτικών καρτών
Application of data mining in banking sector - Credit card fraud prediction
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Keywords
Εξόρυξη γνώσης ; Τραπεζικός τομέας ; Πρόβλεψη απάτης ; Πιστωτικές κάρτεςAbstract
Ιt is commonly considered that we are living the “Big Data” era. The rapid development of the
artificial intelligence, machine learning and data mining has led to the digitization of most of
the actions of people's everyday lives. Therefore, the financial sector, and in particular the
banking sector, could not be unaffected by these changes. In recent years there has been a
growing tendency on the part of the administrations of banking institutions, to digitilise
financial processes. The use of plastic money and specifically credit cards tends to replace the
use of banknotes in transactions. However, the widespread use of credit cards is accompanied
by an increase in fraud worldwide.
This dissertation deals with the burning issue of credit card fraud, following an inductive
development plan. Initially, in the first and second chapter, an extensive reference is made to
the big data and their value, in the various areas of everyday life, focusing on the banking
industry. Then, the third chapter describes the problem of fraud in the financial sector and
specifically in the banking system. The fourth chapter lists the experimental part of the work,
where an attempt is made to develop various models for predicting fraudulent transactions made
by credit card, using data made available by Vesta Corporation. Finally, chapter five captures
the results of the experiments carried out and the conclusions drawn.