Machine Learning Techniques for Fraud Detection in Financial Transactions

Abstract

            Monetary misrepresentation presents increasingly more danger that has serious outcomes in the monetary area. Therefore, monetary establishments are compelled to further develop their extortion recognition frameworks persistently. Lately, a few investigations have utilized AI and information mining procedures to give answers for this issue. In this paper, we propose a condition of craftsmanship on different misrepresentation methods, as well as identification and counteraction strategies proposed in the writing like characterization, bunching, and relapse. The point of this study is to recognize the strategies and techniques that give the best outcomes that have been consummated up to this point.