What Data for This Category Looks Like
Metric calibration data is sourced from internal business rule repositories of financial institutions, official statistical calibration documents published by regulatory bodies, and transaction logs from core business systems. There are two update cycles. Mandatory regulatory calibrations are updated uniformly by the compliance team quarterly or semi-annually. Internal business calibrations are released on demand during product iterations and rule adjustments. Each calibration document follows a structured format, with fields including unique code, Chinese standard name, official definition, calculation logic formula, applicable business scenarios, statistical dimensions, and unit of measurement. Common units of measurement are standardized financial statistical units such as ten thousand yuan, transaction counts, and percentage.
What Constraints These Characteristics Impose on HTTP Interfaces and External Systems
Structured fields for metric calibrations require HTTP interfaces to return fields that strictly match preset unique codes, definitions, and other fields. No arbitrary additions or omissions are allowed. The regular update cycle of regulatory calibrations requires external systems to implement incremental pull logic when connecting. Systems must synchronize local cached data quarterly to avoid using expired calibrations. Multi-dimensional statistical attributes require interfaces to support query parameters such as institution, product type, and other dimensions. This ensures retrieval results meet business filtering needs. Accuracy requirements for financial scenarios require interfaces to include a metric calibration version number parameter. External systems must specify the version when calling the interface. This prevents calculation errors caused by version differences.
How to Configure Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
Calibration Version Verification Switch | Enabled | Ensures calls use the currently active metric calibration version, avoiding expired rules |
Incremental Pull Update Interval | 7 days | Adapts to the quarterly update cycle of regulatory calibrations and on-demand adjustments of internal calibrations, balancing data freshness and interface call volume |
Dimension Filter Parameters | By institution, product type, transaction channel | Matches the multi-dimensional statistical business requirements of metric calibrations, narrowing retrieval scope |
Retrieval Similarity Threshold | 0.75–0.85 | Distinguishes similar calibration names, preventing retrieval results from confusing metrics with different statistical dimensions |
Interface Timeout Threshold | 30 seconds | Adapts to backend processing time for financial metric calculations, avoiding frontend request timeouts |
Return Field Whitelist | Calibration name, definition, calculation logic, unit of measurement | Only returns core fields required for in-app retrieval, reducing data transmission volume |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Configuration Mistakes
- Symptom: Interface returns status code 400 with the prompt "Invalid dimension parameter". Cause: Required dimension filter parameters such as institution and product type were not provided as required, violating the multi-dimensional query constraints of metric calibrations.
- Symptom: Retrieval results include expired regulatory calibration definitions. Cause: The calibration version verification switch was not enabled, and old cached calibration data was called.
- Symptom: Interface returns duplicate calibration entries. Cause: The incremental pull update interval was set too long, and updated calibrations were not synchronized promptly. This results in duplicate returns of old and new entries.
How to Confirm Successful Configuration
- Call the test interface, pass a known valid calibration name and dimension parameters, and verify that the returned fields include the preset core information.
- Check interface logs to confirm that each request carries the metric calibration version number parameter, and that the returned calibration version matches the currently active version.
- Simulate an incremental pull task, and verify that the number of returned entries matches the number of updated calibration records, with no duplicate or missing entries.
- Adjust the similarity threshold, observe changes in retrieval result ranking, and confirm that the threshold configuration meets business differentiation needs.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.