Money-Saver-Preditor

Repository Structure

.
├── app/
│ ├── __init__.py
│ ├── main.py
│ ├── routes.py
│ ├── models/
│ │ ├── __init__.py
│ │ └── deploy_model/
│      ├── decision_tree.pkl
│      └── fraud_detection_model.pkl
│ ├── templates/
│ └── utils/
│   ├── __init__.py
    ├── model.py
│   └── data_preprocessing.py
├── data/
│ ├── raw/
│ │ └── transactions.csv
│ ├── processed/
│ │ └── processed_transactions.csv
│ ├── results/
│ │ └── evaluation_results.csv
├── scripts/
│ ├── preprocess_data.py
│ ├── train_model.py
│ └── evaluate_model.py
├── tests/
├── .gitignore
├── README.md
├── requirements.txt
└── setup.py

Setup Instructions

1. Clone the repository:

   git clone https://github.com/leopers/Money-Saver-Preditor.git
   cd Money-Saver-Preditor

2. Create and activate a virtual environment:

   python3 -m venv venv
   source venv/bin/activate  # On Windows, use `venv\Scripts\activate`

3. Install the required packages:

   pip install -r requirements.txt

4. Make sure your python environment variable is setup correctly

   export PYTHONPATH=$(pwd)

5. Run the Flask application:

   python app/main.py

Usage

• Access the web application at http://localhost:5000
• You can either check for fraud on a specific and existent transaction or even add new transactions to our database.

Dataset description

About the Dataset This is a simulated credit card transaction dataset containing legitimate and fraud transactions from the duration 1st Jan 2019 - 31st Dec 2020. It covers credit cards of 1000 customers doing transactions with a pool of 800 merchants.

Source of Simulation This was generated using Sparkov Data Generation | Github tool created by Brandon Harris. This simulation was run for the duration - 1 Jan 2019 to 31 Dec 2020. The files were combined and converted into a standard format.

Dataset Columns

1. trans_date_trans_time: The date and time when the transaction occurred.
2. cc_num: The credit card number used for the transaction.
3. merchant: The name of the merchant where the transaction took place.
4. category: The category of the merchant or transaction.
5. amt: The amount of the transaction.
6. first: The first name of the cardholder.
7. last: The last name of the cardholder.
8. gender: The gender of the cardholder.
9. street: The street address of the cardholder.
10. city: The city of the cardholder.
11. state: The state of the cardholder.
12. zip: The ZIP code of the cardholder.
13. lat: The latitude coordinate of the cardholder's address.
14. long: The longitude coordinate of the cardholder's address.
15. city_pop: The population of the city where the cardholder resides.
16. job: The occupation of the cardholder.
17. dob: The date of birth of the cardholder.
18. trans_num: A unique identifier for the transaction.
19. unix_time: The transaction time in Unix time format.
20. merch_lat: The latitude coordinate of the merchant's location.
21. merch_long: The longitude coordinate of the merchant's location.
22. is_fraud: A binary indicator of whether the transaction is fraudulent (1) or not (0).

License

This project is licensed under the MIT License.