Credit Card Duplicity Spotting on Gaining the Knowledge on Machine Learning

With the help of technologies like artificial intelligence (AI), machine learning, big data, blockchain, cloud computing, and IoT the technological revolution is speeding (IoT). There has been a dramatic increase in the number of cyber-attacks and criminal activities as a result of the widespread use of ever-improving internet technologies. Fraudulent use of credit cards is a major concern for the banking sector across the world. Credit card fraud is growing at an alarming rate and has become a major concern, especially as the amount of financial transactions utilising credit cards grows. Here, we've looked at some credit card fraud detection methods that can help protect against a variety of scams. The research problems were also discussed and analysed. For the purpose of detecting credit card fraud, we've deployed six widely-accepted machine learning approaches. A confusion matrix is created for each machine learning approach so that the algorithm's performance may be evaluated. Accuracy, precision, recall, specificity, misclassification and F1 score are used to evaluate its efficacy. Machine learning approaches can be useful in detecting credit card fraud, according to the results. For fraud detection, we propose utilising different machine learning algorithms, even though the findings demonstrate that each algorithm has a high degree of precision and recall.