ATM Fraud Detection System using HMM & SVM Algorithm
Gurjeet Ujjainwar, Ashish Gacche, Aniket Bawankule, Aditya Sahare, Kajal Labhane, Priyanka Gonnade · International Journal of Innovations in Engineering and Science · 2022
The banking sector has long been a critical institution that contributes significantly to a country's economic sustainability and maintenance.When bank transactions are tampered with by intruders or fraudsters, the results can be disastrous.This article aims to examine the current system of Electronic Fund Transfer (EFT) ATM activities in terms of cash withdrawal, fund transfer, password hacking, pin misplacing, and biotechnology.The article will look at many types of frauds and try to come up with a solution for solving and detecting frauds on ATMs, as well as a more advanced machine that can accept security technology.Fraudsters have untiring times making illegal moneys while the proposed algorithm in this work will combat most efforts of illegalities regarding funds by electronic data processing (EDP) in the Banking sector; this will be achieved by data mining the bio data though biometric combinational operations at the initial opening of the accounts and as such will conform with the algorithm proposed; the paper worked carefully using the existing literatures and systems to combine the approaches of biometric to the already existing ones and making a complete proposal for a design of ATM engine that will be having on it an incorporated thumbprint capture area and the possibility of the eye scanners and also make sure it doesn't slow down the process to unacceptable speed.