Online fraudulent transactions are a significant criminal violation. Every it costs people and financial institutions billions of dollars. It emphasizes the crucial importance of financial institutions in detecting and preventing fraudulent acts. Machine learning algorithms provide a proactive way mechanism to prevent online transaction frauds with high accuracy. Online transaction fraud is a simple and easy target. E-commerce and other online sites have increased the number of online payment methods, raising the danger of online fraud. With the rise in fraud rates, machine learning approaches can be used to identify and evaluate fraud in online transactions. The primary goal of this project is to implement supervised machine learning models for fraud detection, with the goal of analyzing prior transaction information. Where transactions are classified into distinct groups based on the type of transaction. Following that, various classifiers are trained independently, and models are assessed for correctness. The classifier with the highest rating score can then be picked as one of the best approaches for predicting fraud. We worked with the Kaggle Synthetic Financial Datasets for Fraud Detection dataset collected by Edgar Lopez-Rojas. The use of technology and online shopping has gone up a lot and so has the use of online payment systems like credit cards, debit cards, mobile wallets and internet banking. This has given cybercriminals a chance to do things. People, businesses, and financial institutions think that payment fraud is a big problem. Things like phishing attacks, identity theft, fake websites and malware attacks cause people to lose money. In this research paper we will talk about why online payment fraud happens and look at kinds of online payment fraud. One big reason for payment fraud is that people who use the internet do not know enough about how to keep themselves safe from cyber-attacks like phishing emails and suspicious links. Also not having enough security measures like passwords and networks makes it easy for cybercriminals to commit online payment fraud. The fact that we can now do things on our phones and online has made it even easier for cybercriminals to commit payment fraud. This has been a worry for people who use the internet for a long time. This paper will also talk about some ways to stop payment fraud like using multi-factor authentication secure encryption techniques, tokenization, biometric authentication, and detection systems that use machine learning algorithms. Online payment fraud is a problem and online payment fraud can be stopped with the help of machine learning models that can look at transactions in real time and find anything suspicious. This way banks and other financial institutions can stop transactions before they cause a lot of damage. It is also very important for people to learn about payment security and get updates on the latest threats. The study found out that we need to use a combination of technology and awareness to stop payment fraud. If financial institutions use the security systems, they can reduce the risk of fraud and make people trust online payment systems more. This research helps us understand why online payment fraud happens and how we can stop it which makes the internet a safer place for people to do their finances.
Online Payment Fraud, Digital Payment Security, Cyber Fraud Detection, Phishing Attacks, Identity Theft, Machine Learning in Fraud Detection, Multi-Factor Authentication (MFA), Secure Electronic Transactions, Financial Cybersecurity, Fraud Prevention Techniques.
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