- Saturday, Jan 3rd, 2026
| TITLE | Cutting Edge Machine Learning Strategies for Advanced Credit Card Fraud Detection |
|---|---|
| ABSTRACT | The rapid expansion of the system for digital payment has been led to the risks of a digital payment mechanism has developed for credit card fraud is loss and the security concerns for the banks. Beyond this the monitory damage caused by the fraud is harming the bank reputation and the customer’s too. As to overcome this now a day the banks are utilizing the machine learning methods and they are also implementing the algorithm in their system banks too for overcome these frauds in their banks and for the customer concerns also. In machine learning structured the framework that was employed for the projects are have been classified in some following ways the financial industry has utilized the system for suspicion of a credit card like this support the KNN algorithm, Logistic regression, and Vector machines and some more algorithms also have been used. As each algorithm is utilized in different scenario and done execution in different cases in the backend for the prevention of the theft involving credit cards. The central mission of the identification fraud involving credit card is that to study with the different of the model regarding machine learning and identify the most suitable for the card for credit detection as the primary object of this conduct a competitive research to provide the suitable qualities of the trade off the different algorithm and the recognition of the fraud for the insights. The relationship of the dynamic of the transaction and the continues adopt of the enraging fraud detection by applying the effective machine learning procedures with the accurate evaluation insights which minimizes the finding a credit card theft and also reduces the economic loss also with the trust with financial security solutions. This provide the perfect solutions for the ongoing efforts for the combining credit card prevention of in the financiering sectors with the meaning sectors also with less reinforce public confidence. |
| AUTHOR | Mahalakshmi S, Keerthana H S PG Student, Dept. of MCA, City Engineering College, Bengaluru, India Assistant Professor, Dept. of MCA, City Engineering College, Bengaluru, India |
| VOLUME | 12 |
| DOI | DOI:10.15680/IJARETY.2025.1206026 |
| 26_Cutting Edge Machine Learning Strategies for Advanced Credit Card Fraud Detection.pdf | |
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