Abstract: The banking sector is a very relevant zone in our modern generation. Almost each and every person has to deal with bank either manually or online. Due to a rapid amelioration in the electronic commerce technology, the exploit of credit cards and debit cards has increased. Nowadays most of the banking transactions are done through credit card, debit card and online net banking. These methods are endangered with new attacks. Swindling detection in banking area is one of the essential concepts nowadays because money is substantial part in our life. Data mining is popularly used to detect swindling effectively. It is an established process that acquires data as input and obtains models or patterns as output. Associative rule mining is used in this work. In this research the whole banking operations are concentrated and observed the performance on dataset to detect swindling by giving low risk and high customer satisfaction.

Keywords: Pixel, Ridges, Swindling, Transaction.

PDF | DOI: 10.17148/IARJSET.2021.8676

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