Creating a credit card anti-fraud prediction model using TensorFlow and Machine Learning

People’s desire for credit cards is increasing because of the rapid rise and development of e-commerce. There is no doubting that the advancement of e-commerce has made life and work more easier for individuals. But, at the same time, this system has some flaws, which are occasionally used to get fraudulent benefits. In the real world, both fraudulent and legitimate transactions occur, and traditional pattern matching algorithms are typically ineffective in detecting fraud. This article combines tensor flow and machine learning to process historical credit card transaction data, perform machine learning, develop a credit card anti-fraud prediction model, and forecast consumer credit card theft in advance. The recall rate and accuracy rate of the model are obtained, which is conducive to building an efficient and accurate credit card fraud detection mechanism.