What the data for this category looks like
Data sources for state-owned large bank intelligent due diligence reports include internal credit management systems, the People's Bank of China Enterprise Credit Reference Basic Database, the National Enterprise Credit Information Publicity System, and regulatory submission documents from the China Banking and Insurance Regulatory Commission. The update rhythm follows monthly internal reconciliation updates and quarterly regulatory submission updates. Document structures include structured credit line ledger reports, unstructured interview minutes and collateral evaluation reports. Fields include credit exposure (unit: ten thousand yuan), non-performing loan balance (unit: hundred million yuan), customer credit rating (combination of letters and numbers), and five-category classification identifier. The length of a single due diligence report ranges from 50 to 150 pages, and batch tasks include multiple cross-entity due diligence materials.
What constraints do these characteristics impose on the workflow orchestration link
Multi-source compliant data sources require workflow configurations to include layered permission verification nodes, ensuring only authorized interfaces can pull sensitive data such as central bank credit information. Monthly and quarterly update rhythms require workflows to be bound to scheduled triggers to avoid invalid real-time data pulls. Mixed structured and unstructured document structures require workflows to split format recognition nodes, to handle structured field extraction and unstructured content parsing separately. Specific field units and value rules require built-in field verification logic in workflows, to ensure credit exposure is uniformly converted to ten thousand yuan units, and five-category classification only matches preset compliant values.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
workflow_trigger_cron | 0 2 1 * * | Matches the monthly update cycle of state-owned large bank due diligence data, schedules execution during non-business peak hours |
rag_chunk_size | 800–1200 characters | Adapts to the business paragraph structure of due diligence reports, retains complete semantic units and avoids split breaks |
global_var_override_limit | 3 times | Matches the scenario where only 3 key variable updates are needed in the due diligence process, avoiding logic confusion caused by excessive modifications |
file_parse_timeout | 600 seconds | Covers the parsing duration of a single 50-150 page due diligence report, avoiding task interruption due to timeout |
rag_recall_top_k | Top 10 entries | Adapts to scenarios with multiple reference documents for due diligence reports, recalls core compliant basis and business data |
batch_task_max_size | 20 documents/batch | Matches the conventional scale of batch due diligence for state-owned large banks, avoiding resource exhaustion caused by overly large single-batch tasks |
The parameter values provided on this page are 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, and it is recommended to test on your own samples before finalizing settings.
Three Common Mistakes
- Phenomenon: After modifying global variables in the workflow, the downstream node returns a
variable_emptyerror. Cause: Runtime modification permissions for global variables are not enabled, only variables with initial assignments can be read by fixed nodes. - Phenomenon: When selecting the variable reference mode for the AI chat component, there is no temperature setting button in the interface. Cause: The "Advanced Configuration" submenu is not switched to, and the temperature parameter configuration item is hidden in the default mode.
- Phenomenon: When pulling due diligence data in batches, some nodes time out, and the status code shows
504 Gateway Timeout. Cause: A reasonable file parsing timeout threshold is not set, and the parsing duration of a single due diligence report exceeds the timeout time configured for the node.
How to Confirm Successful Configuration
- Trigger a test schedule, check the global variable modification records in the workflow log, and confirm that downstream nodes can read the updated values.
- Enter the advanced configuration menu of the AI chat component, confirm that the temperature parameter input box is displayed and can manually enter a value between 0 and 2.
- Copy the test knowledge base ID, fill it into the parameter configuration of the node, trigger a test call, and confirm that the
kb_query_successstatus code is returned. - Upload a standard state-owned large bank due diligence report, check the parsed field mapping results, and confirm that the units and values of fields such as credit exposure and five-category classification meet preset rules.
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.