@conference {Ba{\"\i}na202273,
	title = {NEW INSIGHT OF DATA MINING-BASED FRAUD DETECTION IN FINANCIAL IT-SYSTEMS},
	booktitle = {Proceedings of the 15th IADIS International Conference Information Systems 2022, IS 2022},
	year = {2022},
	note = {cited By 0},
	pages = {73-80},
	abstract = {Nowadays, money exchanges are oriented to be more digitized in order to reduce personal contacts and maintain safety from the pandemic covid-19. The most important aspect of any financial institute is to be secure and protected from any suspicious action that can harm the security system and be ready for any type of fraud that can happen such as money laundering, internet frauds, credit card frauds or any other financial fraud. In this paper we present a state of the art of the newest and the most efficient strategies that help financial institutes to be well secure, more reliable, starting from a state of the art of existing ML algorithms used and ending by a benchmark of those algorithms. {\textcopyright} 2022 CURRAN-CONFERENCE. All rights reserved.},
	keywords = {Credit card frauds, Crime, Data mining, Efficient strategy, Finance, Financial fraud, Financial institutes, Fraud detection, Internet fraud, IT system, Laundering, Machine learning, Machine-learning, Personal contacts, State of the art},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137716391\&partnerID=40\&md5=e93045c4bdb15afeefea2672681ef6a3},
	author = {Baina, S. and Rihi, A.}
}
