Protect your payments with real-time Suspicious Transaction Prevention. Instantly detect suspicious transactions with an advanced rule engine and AI-powered analysis, and prevent fraud through blacklist management and risk scoring.
Protect your business against all types of fraud threats with a comprehensive fraud detection solution
Every payment transaction is analyzed in real time and suspicious activities are instantly blocked. Decision-making capability within milliseconds.
Customizable fraud rules tailored to your business needs. Support for query-based and action-based rules.
Monitor, analyze, and report all fraud activities. Action logs, blacklist management, and detailed metrics.
Integrate within minutes using a RESTful API. Comprehensive documentation, Postman collections, and a sandbox environment.
Dynamic blacklists for card numbers, emails, IP addresses, and more. Merchant-level isolation and automated blocking.
Evaluate payments with a risk score between 0–100. Dynamic thresholds and automated actions.
Create and manage customizable fraud rules tailored to your business needs
Analyze historical transaction data with query-based rules. Control transaction count, amount, time intervals, and more.
Rules that respond instantly. Direct actions such as blacklist checks, amount limits, and BIN controls.
Detect complex fraud scenarios by combining multiple conditions. Build powerful combinations using AND / OR logic.
Assign custom risk scores to each rule. Automatically make APPROVE / REVIEW / REJECT decisions based on the total fraud score.
Block if more than 3 transactions are made with the same card within the last 30 minutes
Trigger an alert if the hourly total amount from the same IP address exceeds 10,000 TRY
Review if the daily total amount from the same phone number exceeds 5,000 TRY
Route transactions over 1,000 TRY between 02:00–06:00 for manual review
Reject if the card has more than one transaction with fraud suspicion in the last hour
Block non-3D Secure transactions over 500 TRY made via Link / QR Code channels
Automatically reject transactions originating from specified country codes
Flag as suspicious if more than 5 different cards are used from the same device within an hour
Reduce the risk score if the card has more than 10 successful transactions in the last hour
Yes, we offer a fully customizable rule engine. You can create both query-based and action-based rules, and define rules based on dozens of parameters such as transaction amount, card details, IP address, payment channel, and transaction time.
Before each payment transaction, the system assigns a score based on the fraud rules you have defined. Each triggered rule contributes to the total score, and the transaction is evaluated with a risk score between 0 and 100. According to your configured threshold values, the transaction is automatically routed to one of these actions: APPROVE, REVIEW, or REJECT.
Thanks to the blacklist structure, after a payment transaction is received, you can add records to the blacklist based on the parameters you define (Card, IP Address, Email, Phone Number, Device Fingerprint, Card BIN).
With Paywall’s standardized error codes, when a transaction fails due to a stolen card reported by the provider, you can directly add the relevant payment details (Phone Number, Card, IP Address, Email, Card BIN, Device Fingerprint) to the blacklist either temporarily or permanently.
We support all payment channels, including Web, Android, iOS, Link/QR Code, Checkout, Recurring payments, Bulk payments, and Split payments. You can define separate rules for each channel.
Yes, fraud checks are performed for all payment types, including 3D Secure, Direct Payment, Half 3D, and OTP. You can define different rules based on the payment type, such as blocking transactions over 500 TRY for non-3D Secure payments.
Yes, our system is PCI-DSS compliant. Card numbers are never stored in plain text; all sensitive data is processed using hashing. End-to-end security is ensured with 256-bit SSL encryption, and full compliance with KVKK requirements is maintained.
