Fraud Detection

Feature

AI-Powered Detection: Leverage machine learning to identify and prevent fraud in real-time.

Usecase

Protect Your Platform: Safeguard against financial fraud, account takeovers, and abuse.

What is Fraud Detection?

Fraud Detection is the process of identifying and preventing fraudulent activities, such as unauthorized transactions, account takeovers, and spam. In today’s digital world, where fraudsters are becoming increasingly sophisticated, having a robust fraud detection system is crucial for any online business.

Our Fraud Detection API uses artificial intelligence to analyze various signals and assess the risk of fraud in real-time. It helps you to:

• Reduce Financial Losses: Prevent fraudulent transactions and chargebacks.
• Protect Your Customers: Safeguard your users from account takeovers and other malicious activities.
• Maintain a Healthy Platform: Keep your platform free from spam, fake accounts, and other forms of abuse.
• Automate Risk Management: Streamline your fraud prevention efforts with automated risk scoring and recommendations.

API Endpoint

The Fraud Detection API endpoint is:

POST https://zoros.io/api/v1/fraud/detect

Request Parameters

Parameter	Type	Description
transaction_id	string	A unique identifier for the transaction or event.
api_key	string	Your unique API key for authentication.
data	object	An object containing the data to be analyzed.

Example Request

curl -X POST "https://zoros.io/api/v1/fraud/detect" \
     -H "Content-Type: application/json" \
     -d '{
           "transaction_id": "txn_1A2b3C4d5E",
           "api_key": "YOUR_API_KEY",
           "data": {
             "ip_address": "123.45.67.89",
             "amount": 99.99,
             "user_id": "user_123"
           }
         }'

API Response

The API returns a JSON object with the fraud risk analysis.

Example Response

{
  "transaction_id": "txn_1A2b3C4d5E",
  "risk_score": 0.92,
  "risk_level": "high",
  "indicators": [
    "IP from high-risk country",
    "Unusual transaction amount",
    "New device ID"
  ],
  "recommendation": "manual_review",
  "timestamp": "2025-08-26T10:30:00Z"
}

Response Field Descriptions

Field	Type	Description
transaction_id	string	The unique identifier for the transaction or event.
risk_score	float	A score from 0.0 to 1.0 indicating the probability of fraud.
risk_level	string	The categorical risk level: low, medium, or high.
indicators	array	A list of specific risk factors that were triggered.
recommendation	string	The suggested action: approve, review, or block.
timestamp	string	The timestamp of when the analysis was made.

Use Cases

E-commerce

Analyze transactions to prevent chargebacks and payment fraud.

Financial Services

Monitor for fraudulent transfers and unauthorized account access.

Account Security

Detect and block account takeover (ATO) attempts in real-time.

Content Moderation

Identify and filter spam, fake users, and malicious content.