This internship project aims to leverage machine learning classification techniques to develop an effective fraud detection system for Fastag transactions. The primary goal is to create a robust model that can accurately identify instances of fraudulent activity, thereby ensuring the integrity and security of Fastag transactions.
The dataset includes the following key features:
- Transaction_ID: Unique identifier for each transaction.
- Timestamp: Date and time of the transaction.
- Vehicle_Type: Type of vehicle involved in the transaction.
- FastagID: Unique identifier for Fastag.
- TollBoothID: Identifier for the toll booth.
- Lane_Type: Type of lane used for the transaction.
- Vehicle_Dimensions: Dimensions of the vehicle.
- Transaction_Amount: Amount associated with the transaction.
- Amount_paid: Amount paid for the transaction.
- Geographical_Location: Location details of the transaction.
- Vehicle_Speed: Speed of the vehicle during the transaction.
- Vehicle_Plate_Number: License plate number of the vehicle.
- Fraud_indicator: Binary indicator of fraudulent activity (target variable).
- Understand the distribution of features and the prevalence of fraud indicators in the dataset.
- Identify and engineer relevant features that contribute to the accuracy of fraud detection.
- Build a machine learning classification model to predict and detect Fastag transaction fraud.
- Evaluate and fine-tune model performance using appropriate metrics.
- Explore the feasibility of implementing the model for real-time Fastag fraud detection.
- Provide insights into the factors contributing to fraudulent transactions.
- Addressing the imbalanced dataset issue due to the likely low occurrence of fraud.
- Feature engineering to capture nuanced patterns indicative of fraud.
- Model performance assessed using metrics such as precision, recall, F1 score, and accuracy.
- Trained machine learning model for Fastag fraud detection.
- Evaluation metrics and analysis report.
- Documentation on relevant features and their impact on fraud detection.
- An effective and scalable Fastag fraud detection system capable of minimizing financial losses and ensuring the security of digital toll transactions.