What Data Looks Like for This Category
Data for this category primarily comes from publicly disclosed submission documents of non-bank financial institutions by regulatory agencies, official disclosure documents of target subjects, compliant data from third-party credit agencies, and transcript files from on-site interviews conducted by due diligence teams. Regular disclosure files are updated quarterly and annually, temporary announcements are updated when events occur, and on-site interview data is submitted as needed. Documents include modules such as structured financial data tables, unstructured interview minutes, scanned files for pledged guarantees, and related party relationship graphs. Structured fields include unified social credit code, net assets, number of related parties, and others. Net assets are measured in ten thousand yuan, the number of related parties is an integer, and most scanned files are in PDF or image formats.
What Constraints These Characteristics Impose on Workflow Orchestration
The multi-source, scattered nature of diversified financial due diligence data requires workflow configurations with multi-source data access nodes, to support multiple formats including structured data tables, unstructured text, and image scan files. There are two scenarios for data updates: scheduled triggering and event triggering. Workflow startup must support both scheduled scheduling and Webhook triggering. Single documents vary widely in length and include image attachments, so adaptive segment parsing parameters must be configured, paired with OCR nodes to process scan files. Fields have fixed unit requirements, so standardized field mapping rules must be configured to ensure extracted fields comply with regulatory disclosure standard formats and avoid unit mismatches. When batch processing multiple due diligence reports, concurrency execution parameters must be properly configured to prevent resource overload.
How to Configure Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Diversified financial due diligence reports include long documents and image scan files, which take longer to parse. 600 seconds covers most common scenarios |
UPLOAD_FILE_MAX_SIZE | 2000 MB | A complete due diligence report may include multiple attachments, with a total size that can reach a high threshold. 2000 MB meets batch processing requirements |
context_scope | current_node | Node processing for diversified financial due diligence reports must focus on the parsing results of the current link, avoiding global context interference with field extraction accuracy |
BATCH_CONCURRENCY_LIMIT | 3–5 concurrent executions | When batch processing multiple due diligence reports, excessive concurrency will trigger interface rate limiting. 3-5 balances processing efficiency and resource usage |
OCR_ENABLED | true | Due diligence reports include image format attachments such as pledge announcements and on-site photos, requiring OCR to extract text content |
FIELD_MAPPING_RULE | Match according to regulatory disclosure fields | Fields for diversified financial due diligence reports must comply with the fixed formats required by regulatory disclosures, ensuring unified units for extracted fields such as net assets and guarantee amounts |
The parameter values provided on this page are all common recommendations used as starting points for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require specific analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Symptom: An error indicating invalid parameters is returned when calling the workflow API to upload images for parsing, or the parsing result is empty. Cause: Image files are not passed in form-data format, or the file field name required by the interface is not matched correctly.
- Symptom: Due diligence fields extracted by the LLM node include historical task data, which does not match the current input. Cause: The context scope is not limited to the current node, and using global context causes data crossover between different tasks.
- Symptom: The workflow node returns the
500 Gateway forwarding error because service is disconnectederror. Cause: The configured LLM service connection is interrupted, or no automatic retry logic is configured for node call timeouts.
How to Verify Proper Configuration
- Upload a due diligence report attachment of conventional scale, verify that the OCR node can correctly extract text content from images.
- Run a single-node test configuration, confirm that the LLM node only uses the context of the current input to complete field extraction, with no historical data crossover.
- Submit a batch task, observe whether the number of concurrent workflow executions matches the preset resource configuration requirements.
- Call the workflow API to pass image files, verify that the interface can normally receive parameters and return expected parsing results.
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.