HTTP Interfaces and External Systems for Multi-Financial Intelligent Due Diligence Reports

What the data for this category looks like

Data for multi-financial intelligent due diligence reports comes from industrial and commercial public disclosure systems, non-bank financial institution registration platforms, interbank transaction disclosure systems, and third-party special credit reporting databases. Update schedules: Industrial entity information is updated quarterly. Interbank transaction data is updated daily after market close. Product outstanding status is updated in real time upon issuance and redemption nodes. Document structure uses mixed format, with dozens of pages. It includes both structured tables and unstructured disclosure text. Modules cover entity qualifications, counterparty risk, product outstanding scale, and related transaction details. Fields include character-type credit ratings, numeric transaction amounts, and count-type related transaction numbers. Amount fields mostly use ten thousand yuan or hundred million yuan as units.

What constraints do these characteristics impose on HTTP interfaces and external systems

Multi-source heterogeneous data sources require interface integration to support multiple authentication methods, including API keys and OAuth2.0 tokens. Separate call permissions must be configured for each data source. Different update schedules require setting differentiated scheduled pull cycles to avoid excessive calls or data lag. Long documents and mixed structures require interfaces to support large-volume file transfers and structured field parsing. They also require handling inconsistent units returned by different data sources. Under compliance requirements, interface calls must fully record request parameters, return results, and call times for subsequent audits.

How to set configurations

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, and it is recommended to test against your own samples before finalizing settings.

Three common mistakes

• 413 Request Entity Too Large error returned when calling external data source interfaces. Cause: The UPLOAD_FILE_MAX_SIZE configuration was not adjusted, so due diligence reports exceeding the default limit cannot be uploaded.
• Chat history records for different users cannot be distinguished, and returned context includes content from unrelated users. Cause: USER_IDENTIFIER_FIELD was not configured, and no user identifier parameter was passed via the request header.
• Parsed due diligence report amount field values are inconsistent, with unit mismatches across data sources. Cause: FIELD_UNIT_CONVERSION was not enabled, and amount units returned by different data sources were not unified.

How to confirm configurations are correct

• Upload a complete multi-financial due diligence report. Check that the parsed text fully covers all sections with no truncation.
• Initiate two interface calls with different X-User-ID request headers. Check that the returned chat history only includes interaction records for the corresponding user.
• Call the integrated third-party data source interface. Check that the returned amount fields have been unified to the preset unit.
• Simulate three consecutive interface call failures. Check that the system automatically triggers the retry mechanism with no permanent failures.

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.