HTTP Interfaces and External Systems for Urban Commercial Bank Intelligent Due Diligence Reports

The data for urban commercial bank intelligent due diligence reports comes primarily from four sources: local banking and insurance regulatory

What the data for this category looks like

The data for urban commercial bank intelligent due diligence reports comes primarily from four sources: local banking and insurance regulatory reporting systems, People's Bank of China financial statistics monitoring interfaces, the bank's own corporate credit ledger, and corporate credit data from local credit reporting platforms. Structured ledger data is updated daily in sync. External credit reporting data is updated on a T+1 basis. Regulatory reporting batch data is updated monthly.

Each individual due diligence report includes structured data tables and unstructured credit files. Structured fields include credit subject name, unified social credit code, credit contract number, credit disbursement date, credit expiration date, credit balance (unit: ten thousand RMB), guarantee method, and handling branch code. Unstructured files are mostly scanned copies of credit approvals and corporate business materials.

What constraints these characteristics impose on HTTP interfaces and external systems

The multiple data sources and staggered update schedules for urban commercial bank due diligence data require HTTP interfaces to support both real-time single-record queries and batch paginated pull invocation modes. This adapts to the synchronization needs of different data types.

Mixed transmission of sensitive fields and unstructured files requires interface configurations to support two-way SSL authentication and large file chunked upload capabilities. This meets security specifications for sensitive data transmission.

Strict alignment of field units with internal ledgers is required. The units of fields returned by the interface must exactly match the definitions used in the urban commercial bank's internal risk control system. This avoids data conversion errors.

Additionally, urban commercial banks have strict access controls on their internal networks. This requires interfaces to be configured with a fixed outbound IP whitelist. Only designated internal network IPs are allowed to initiate requests.

How to set the configurations

Configuration ItemRecommended SettingRationale
external_api_timeout300 secondsAdapts to the average response latency of urban commercial bank internal systems, preventing timeout interruptions from high-frequency calls
batch_sync_max_page100 items per pageMatches the batch pagination specifications of urban commercial bank regulatory reporting data, reducing interface call frequency
ssl_mutual_authEnabledMeets security requirements for sensitive data transmission in urban commercial banks, and adapts to two-way authentication rules for internal network access
file_upload_chunk_size8 MBAdapts to the common size of unstructured credit files for urban commercial banks, preventing chunked upload failures
response_field_unitAligned with internal systemsEnsures units of fields such as credit balance returned by the interface match the urban commercial bank's risk control ledger, eliminating the need for additional conversion
ip_whitelistFill in the urban commercial bank internal network egress IP rangeAdapts to the strict network access control policies of urban commercial banks, blocking unauthorized requests

The parameter values provided on this page are all common recommended starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require case-by-case analysis. It is recommended to test on your own samples before finalizing settings.

Three common mistakes

  • Symptom: After uploading a credit scan copy, the file_id returned by the interface fails to bind to the knowledge base collection. This prevents subsequent recall from associating the corresponding document. Cause: The collection_id parameter was not specified in the upload interface, or the passed collection ID does not match the collection mapping rules of the urban commercial bank's internal risk control system.
  • Symptom: Calling the batch pull interface returns a 413 Request Entity Too Large status code. Cause: The file_upload_chunk_size was not configured to an appropriate chunk size. Large files are uploaded directly, exceeding the interface's default limits.
  • Symptom: The unit of the credit balance field returned by the interface is yuan, which does not match the ten thousand RMB unit used by the urban commercial bank's internal system. This prevents direct import of data into the risk control system. Cause: The response_field_unit was not set to align with the internal system. The default return unit was not adapted for conversion.

How to confirm the configuration is complete

  • Initiate a single-record credit subject query request, and verify that the units of returned fields match the definitions in the urban commercial bank's internal risk control ledger.
  • Upload a standard credit scan copy, and check whether the file_id and collection_id returned by the interface can be properly associated in the knowledge base and retrieve the content.
  • After configuring the fixed IP whitelist, initiate a request from an unauthorized IP, and confirm that the interface returns a 403 Forbidden status code.
  • Initiate a batch pull request, and verify that the pagination parameters correctly return data for the specified number of pages, with no data truncation or duplicate returns.

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.