Fraud Buster API Integration Example

Welcome to the official integration example for the Fraud Buster API by Hive Forensics AI Inc. This guide is designed to help developers seamlessly implement our cutting-edge fraudulent transaction detection within their payment forms.

Overview

The Fraud Buster API provides real-time transaction risk assessment to help prevent fraudulent activities in your payment systems. This React-based example demonstrates how to integrate our API into your frontend applications, enhancing security and user trust.

Features

• Real-time risk score assessment based on transaction details.
• Dynamic response handling to guide user actions.
• Easy-to-implement React hooks for quick integration.

Prerequisites

Before starting, ensure you have the following:

• Node.js and npm installed.
• Basic understanding of React and JavaScript.
• An API key from Hive Forensics (obtainable through our website).

Installation

1. Clone the repository:

   git clone https://github.com/HiveForensics/FraudBusterExample.git
   
   

Navigate to the cloned directory and install dependencies:

cd FraudBusterExample npm install

Start the application:

npm start

Usage

To integrate the Fraud Buster API effectively, follow these steps:

1. Fill out the payment form with the necessary transaction details.
2. Click 'Submit Payment' to dispatch the data to the Fraud Buster API.
3. Review the risk score to determine the transaction risk:
   • Green: Proceed to payment (Risk Score < 50).
   • Yellow: Review payment (Risk Score between 50 and 65).
   • Red: Risky payment (Risk Score > 65).

Integration Guide

Follow these steps to integrate the Fraud Buster API into your existing payment system:

1. Set up the React environment: Confirm that your project is equipped with React and all necessary dependencies.
2. Import and use the custom hook: Utilize useApi, a custom React hook, for seamless interaction with the Fraud Buster API. Incorporate this hook within your payment form component.
3. Handle form submission: Adapt the form's submission logic to include the current time and employ the postData function offered by useApi.
4. Display risk assessment results: Execute conditional rendering based on the API's feedback to enlighten users about the transaction's risk score.

Support

If you require assistance, please visit our support page or reach out to us directly via our website for more personalized support.

Contributing

We are open to contributions that can enhance this example. Adhere to our contribution guidelines when submitting pull requests.

License

This project is made available under the MIT License.

About Hive Forensics AI Inc.

Hive Forensics AI Inc. is committed to delivering state-of-the-art AI solutions for cybersecurity and fraud detection. Discover more about our mission and services at our website.

Thank you for choosing Hive Forensics AI Inc. Together, we are paving the way towards a more secure digital environment.