Jan 1, 2019 · Performance of Logistic Regression, K-Nearest Neighbour, and Naïve Bayes are analysed on highly skewed credit card fraud data where Research is carried out on examining …

May 13, 2025 · The goal of this project is to develop a machine learning model that can accurately detect fraudulent credit card transactions using historical data. By analyzing transaction …

Credit card fraud detection is a vital challenge for investment firms, requiring advanced techniques to identify fraudulent transactions efficiently.

May 5, 2022 · In this research article, we have conducted a comparative analysis of the literature review considering the ML techniques for credit card fraud detection (CCFD) and data …

Nov 20, 2024 · This paper presents a comparative analysis of multiple machine learning classifiers for credit card fraud detection such as Random Forest, Logistic Regression, K …

Detecting fraudulent transactions in real-time is a critical challenge due to the imbalanced nature of fraud datasets and the evolving tactics of fraudsters. This paper presents a robust machine …

May 17, 2024 · Algorithms based on Machine Learning are being used to spot fraudulent practices in credit card transactions. This paper presents a review of Machine Learning …

How can machine learning help with credit card fraud detection? Machine learning models can recognise unusual credit card transactions and fraud. The first and foremost step involves …

2 days ago · Mim et al. in 2024 proposed an approach to detect credit card fraud on unbalanced data using soft voting ensemble learning (Azim Mim et al., 2024). Several sophisticated …

While traditional detection systems often struggle to keep pace, credit card fraud detection using machine learning is emerging as the new standard. Let’s delve into why this shift is occurring, …