For companies building in-house fraud models, risk decisions can’t be made in isolation. Risk evolves in real time, and in-house fraud detection systems that rely primarily on internal data create a universe of unknown blind spots that fraudsters can easily exploit.
The Sift Score API eliminates hidden threats by providing real-time risk signals derived from Sift’s vast Global Data Network. It bridges the gap between internal risk signals and industry-wide fraud intelligence—by using Sift as a key data input.
What is the Sift Score API?
The Sift Score API is a modular fraud intelligence solution that delivers real-time risk scores derived from over 1 trillion annual events and 16,000+ fraud signals accumulated over 13 years. The solution delivers the following:
- A fraud risk score (0-100) to assess transaction legitimacy.
- Top 20 risk signals explaining why an action was flagged.
- Seamless API integration into internal fraud models and decision engines.
With this solution, data science and risk teams can enhance their existing fraud stacks with external intelligence while maintaining full control over their risk management workflows.
The Missing Piece for In-House Fraud Models
Many companies build custom fraud detection models tailored to their unique data and risk patterns. While this approach has its advantages, it also comes with limitations:
- Limited Data Scope. Internal models rely solely on company-specific transaction history, missing broader fraud patterns that occur across industries and geographies.
- Delayed Threat Recognition. Emerging fraud tactics (e.g., card testing and credential stuffing) may not be detected until they cause significant losses.
- Benchmarking Challenges. Without external data, it’s difficult to measure the accuracy and effectiveness of internal models.
By incorporating the Sift Score API, businesses gain access to a global fraud intelligence network, augmenting their internal models with the same level of risk insight as full-platform Sift customers—without needing to adopt the entire platform.
How the Sift Score API Works
The Sift Score API integrates with in-house risk engines fluently and without friction, providing fraud detection intelligence that would take years to build from scratch. When your internal risk engine submits real-time data via API calls (e.g., IP address, email, device fingerprint, transaction details), Sift cross-references that input against our Global Data Network. An identity match or link is then made, and anomalies and patterns linked to fraudulent behavior can then be accurately identified in real-time.
Industry-specific risk factors are applied to ensure relevance for your industry sector. Finally, the API returns a fraud risk score (0-100), while also providing the top 20 risk signals to help your business understand the factors driving each risk assessment and score. This data feeds directly into your in-house decisioning systems, enabling automated responses or downstream manual review. Businesses using the API maintain access to the complete Sift Console, and can leverage it as needed.
Powerful outcomes include:
- Benchmarking & Model Validation. Compare internal fraud scores against an industry-wide benchmark, identifying areas for improvement.
- Real-Time Global Visibility. Access global fraud context beyond company walls, preventing threats before they reach your platform.
- Higher Detection Accuracy. Reduce false positives and improve fraud detection rates by 15-20%, leveraging Sift’s deep learning models.
Build How You Want Without Limiting Insights
The Sift Score API is built for data science-focused digital businesses on a journey to build a bespoke world-class fraud intelligence system. Whether your team is running multiple custom machine learning models or relying on a rules-based risk engine, our API delivers data-driven precision directly within your existing fraud stack.
Stop fighting fraud blind—book a demo to see the Sift Score API in action.
