What data looks like for this category
Data for large state-owned bank intelligent due diligence reports primarily comes from internal credit management systems, regulatory submission archives, annual financial reports, and single credit facility approval archives. Data updates follow fixed quarterly and annual cycles, with temporary updates when individual credit facilities are modified. Document structure is mostly composed of structured fields, including fixed fields such as the customer’s unified social credit code, credit limit, approval date, and risk rating, along with several thousand characters of due diligence explanation text. Field units are mostly ten thousand yuan and percentage points, and ratings use a regulatory-unified grading system.
What constraints do these characteristics impose on the knowledge base retrieval and recall link
The high proportion of structured fields requires retrieval to match both keywords and field attributes, to avoid mixing irrelevant content. The combination of fixed update cycles and temporary updates requires the recall mechanism to support both incremental update and manual trigger modes, ensuring that the latest credit information can be retrieved quickly. The combination of long-text due diligence explanations and fixed fields requires that the association between fields and their corresponding texts is retained during segmented retrieval, to avoid breaking information integrity. The high credibility requirement for regulatory-related content requires verification of the document metadata of recall sources, to ensure that content is compliant and traceable.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
Recall Count | Top 10-15 results | Large state-owned bank due diligence reports cover multi-dimensional fields, requiring valid results across different retrieval dimensions to avoid missing core information |
Similarity Threshold | 0.75-0.85 | Due diligence report content is rigorous, requiring filtering of low-relevance retrieval results while adapting to some non-standard due diligence description texts |
Segment Length | 800-1200 characters | Balances the contextual integrity of due diligence explanation texts and the retention of associations with structured fields, avoiding splitting fields and their corresponding explanations due to overly short segments |
Incremental Update Trigger Cycle | 2:00 AM daily | Matches the fixed update rhythm of large state-owned banks, and temporary credit facility changes can be supplemented with the latest data via manually triggered incremental updates |
Field Weighting | Credit approval fields: 1.2 weight, risk rating fields: 1.1 weight | Due diligence reports primarily focus on credit limit and risk rating content, increasing the retrieval weight of corresponding fields optimizes result ranking |
Reranked Return Count | Top 5 results | Focuses on core due diligence content, reducing the cost of valid information filtering for engineers |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require specific analysis, and it is recommended to test against your own samples before finalizing settings.
Three common mistakes
- Phenomenon: Retrieval results are empty or insufficient in quantity, and logs show matching degrees below the threshold. Cause: The similarity threshold is set too high, failing to adapt to some non-standard business description content in due diligence reports.
- Phenomenon: Returned results include expired historical credit documents. Cause: Incremental update trigger rules are not configured, and expired due diligence report versions are not filtered.
- Phenomenon: Retrieval results cannot be associated with the corresponding credit subject, and field information is chaotic. Cause: The field association of document metadata is not retained, or field weighting configuration is not enabled.
How to confirm the configuration is complete
- Upload a standard large state-owned bank due diligence report, check whether the parsed fields are fully extracted, including core fields such as the customer’s unified social credit code and credit limit.
- Enter specific keywords for a single credit facility, verify that the similarity of returned results falls within the set range, with no obvious irrelevant content.
- Trigger a manual incremental update, upload a new temporary credit due diligence document, and confirm that the new document can be normally retrieved and recalled.
- View retrieval logs, confirm that in the sorted results after field weighting, content related to credit approval and risk ranking ranks first.
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.