Online Payment Fraud Transaction Detection using Machine Learning

Determining and overcoming the online payment frauds is a very important and challenging step for any business as it may lead to financial losses if it occurs in increasing volume of it. These techniques of machine learning algorithms were used to identify the online fraud transactions in real world. For this, a dataset of online payment transactions was used from Kaggle and machine learning models were created and used for the classification of transactions into fraud or not fraud transactions. The outcomes of the same determined the attainability of these machine learning processes and models in identifying features associated with fraud transactions, which would result in creating an influential mechanism and preventing frauds. These models used not only increases the credibility of the model by increasing the accuracy of it but also allows to implement the bold measures to avoid these frauds. This study above determines and highlights the importance of the explanatory methods in contrast to the online payment fraud of the transactions, underlining the tips for avoiding the frauds in business for protecting their financial interfaces and maintaining the trust of the customers. Accuracy found upto 95% by implementing the things within the machine learning platform.