Examples

Hive Forensics Fraud Detection API: Examples

In this section, we provide practical examples of using the Hive Forensics Fraud Detection API with recommended parameters. Please note that these are just examples, and the actual implementation may vary depending on your business model and requirements.

Basic Implementation

In this basic example, we set a risk threshold of 80 to verify and consider transactions risky. This is suitable for businesses with a standard risk tolerance.

// Example Request
POST /api/fraud-detection
 
{
  "transaction_id": "123456789",
  "amount": 100.00,
  "risk_threshold": 80
}
 
// Example Response
{
  "transaction_id": "123456789",
  "status": "Verified Risky",
  "message": "Transaction requires further verification."
}

High-Risk Business Model

For businesses operating in high-risk industries, it's advisable to lower the risk threshold for declines to 70 or below. This example demonstrates such a configuration.

{
  "transaction_id": "987654321",
  "status": "Declined",
  "message": "Transaction exceeds acceptable risk level."
}

Approved Transactions

{
  "transaction_id": "456789123",
  "status": "Approved",
  "message": "Transaction meets acceptable risk criteria."
}

Experimentation

Ultimately, it's essential to experiment with the API to determine the best course of action for your specific business. Your developers can adjust the risk thresholds, analyze results, and fine-tune the parameters as needed.

Remember that the Hive Forensics Fraud Detection API provides flexibility and customization options to adapt to your evolving fraud prevention needs.

These examples serve as a starting point for integrating and configuring the API. We encourage you to work closely with your development team to find the optimal settings and risk thresholds that align with your business goals and risk tolerance.

For detailed API documentation and additional examples, please refer to our developer portal. If you have any questions or need further assistance, our support team is here to help you make the most of our fraud detection capabilities.