Designing Decision-Support Logic for Combo Check API Integrations

When building user onboarding or risk-review workflows, the challenge often lies in how to interpret incoming data signals. Should you treat a user's digital footprint as a single "pass/fail" gate, or as a collection of independent data points?

For developers integrating identity verification signals, the choice between CSV/TXT upload workflows, individual Per-call API requests, and the Combo Check API often depends on your application's specific decision-support requirements.

Choosing Your Integration Path

1. CSV/TXT Upload Workflow

This approach is best suited for bulk analysis or periodic auditing where immediate, real-time decision-making is not required. It is an operational choice for processing large lists of identifiers asynchronously.

2. Per-call API Integration

Use the Per-call API when your logic requires a specific, granular signal from a single service. This is ideal for lightweight checks where you only need to confirm presence on one platform (e.g., verifying a WhatsApp presence to trigger a specific communication channel).

3. Combo Check API

When your business logic requires a comprehensive view of a user's digital presence, the Combo Check API allows you to verify one identifier against multiple services in a single request. By retrieving all signals at once, you can build more nuanced, multi-factor decision rules.

Designing Robust Decision Logic

When consuming data from the Combo Check API, it is critical to treat each service result as an independent input. Because the API returns a structured object containing results for each service, your application should parse these individually.

Handling Partial Results

Integration logic must account for the reality of distributed systems. The Combo Check API runs selected services in parallel. In some cases, individual services may return a null registration status or a specific error (such as a timeout).

Instead of treating a null result as a failure of the entire request, your application logic should:

1. Validate the success flag: Confirm the overall request was processed.
2. Iterate through the results object: Check the registered status for each service key.
3. Handle exceptions: If a specific service returns an error or a null value, implement a fallback or a retry strategy using the individual /v1/check endpoint for that specific service.

Best Practices for Decision Rules

• Decouple Signals: Do not create a monolithic "is_valid" flag. Instead, map registration signals to internal business requirements. For example, require a "High" score from the Unified Score API for high-value transactions, while using Combo Check signals to verify secondary platform presence for account recovery.
• Rate Limiting: Note that the API has rate limits that restrict requests per minute and that concurrency is also limited. Always consult the current API documentation for applicable limits to ensure your polling or request frequency remains within operational bounds.
• Graceful Degradation: If a service check times out, your system should be designed to either proceed with the available data or prompt the user for additional verification, rather than failing the entire onboarding flow.

Conclusion

By treating service signals as independent, modular inputs, you can create more resilient onboarding flows. Whether you are using the Combo Check API to aggregate multiple signals or the Unified Score API to obtain a risk-based PTS score, the key is to design your application to interpret these outputs as decision-support signals rather than deterministic outcomes.

This article was drafted with AI assistance and reviewed before publishing.