abhisooraj / credit-fraud-detection-system

This system created on credit card transaction dataset that have imbalance issues: handling imbalance issues, this system can identify fraud and benign transactions using machine learning classifiers and class Imbalance techniques. DataSet and problem : https://www.kaggle.com/mlg-ulb/creditcardfraud

Credit-fraud-detection-system

Purpose:

This system can identify fraudulent transactions in all transactions.
These days the number of fraudulent transactions is increasing exponentially hence the bank and government want to stop these fraudulent transactions and provide a safe, secure environment for their customers. This system is built on transactions of credit card dataset.

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DataSet and problem: https://www.kaggle.com/mlg-ulb/creditcardfraud There are 3 major class imbalance techniques implemented in this work:

1. Oversampling
2. Undersampling
3. OverSampling followed by Undersampling

Imbalanced Dataset:

Architecture:

Architecture of Credit card fraud detection System:

For building the model of this problem the most important issue is that the dataset having class imbalance issues. hence various class Imbalance techniques are implemented.
After handling this class imbalance issues,The model get trained on various Machine learning algorithms and this system is able to identify fraud and benign transactions in all the card transactions. This system will be buil

Block-Diagram of Classification based Credit card fraud detection System