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Aniket Singh
Bengaluru, Karnataka
Credit Card Fraud Detection using AI/ML
Credit card fraud detection systems leverage AI/ML to detect patterns of fraudulent behavior in spending data. They identify anomalies, flag suspicious activity, and improve over time through machine learning. This helps prevent losses for financial institutions and consumers. ...learn more
Project status: Under Development
oneAPI, Artificial Intelligence, Cloud
Intel Technologies
oneAPI
Overview / Usage
Credit card fraud detection systems use AI/ML algorithms to analyze large amounts of data and identify patterns of fraudulent behavior. These systems can detect anomalies in spending patterns, identify unusual transactions, and flag potentially fraudulent activity for further investigation. Machine learning algorithms are trained on historical data to recognize fraudulent patterns, and can adapt and improve over time as new data becomes available. By using AI/ML, credit card fraud detection systems can help prevent losses for both financial institutions and consumers.
Methodology / Approach
Credit card fraud detection systems use various techniques and frameworks, including supervised and unsupervised machine learning, statistical modeling, and pattern recognition. The systems are trained on historical data that includes both normal and fraudulent transaction patterns. The models learn to recognize patterns and anomalies in the data and use these to identify potentially fraudulent transactions in real-time.
Frameworks such as Apache Spark, TensorFlow, and scikit-learn are commonly used for building credit card fraud detection systems. Standards such as the Payment Card Industry Data Security Standard (PCI DSS) and ISO 27001 provide guidelines for protecting sensitive data and preventing fraud.
Techniques such as neural networks, decision trees, and clustering algorithms are used to analyze transaction data and identify fraudulent activity. Additionally, real-time monitoring and alerting systems can be employed to quickly respond to suspicious activity and prevent further losses.
Overall, credit card fraud detection systems use a combination of technology, frameworks, and techniques to protect against fraud and minimize losses for financial institutions and consumers.
Technologies Used
Flask
gunicorn
pandas
numpy
matplotlib
seaborn
sklearn
Repository
https://github.com/shiva0123m/IntelOneAPi
Collaborators