What This Category's Data Looks Like
The data for financial leasing intelligent due diligence reports comes from lessee business registration archives, People's Bank of China credit reports, leased asset ownership registration documents, the most recent audited financial statement materials, historical leasing project ledgers, and industry regulatory compliance documents.
Update cadence aligns with business nodes:
- Update leased asset ownership and lessee operating status data in real time when ownership changes
- Synchronize financial statements quarterly or annually
- Update historical project ledgers when rent is collected or paid
Documents fall into two categories: structured fields and unstructured text. Structured fields include unified social credit code, leased asset original value (unit: yuan), lease term (unit: month), and total rent amount (unit: yuan). Unstructured content includes due diligence interview records, site inspection notes, and compliance verification opinions.
Constraints on Knowledge Base Retrieval and Recall
The large number of structured fields with clear units requires retrieval to match both field semantics and unit consistency, avoiding confusion of similar fields from different lessees.
Data sources have varying update cadences. Filter expired data during recall to ensure content timeliness. For example, exclude financial statements that have not updated for more than 6 months.
Unstructured text length varies widely, from dozens of characters for compliance verification opinions to thousands of characters for interview minutes. Adapt text segmentation and recall rules for different lengths to avoid semantic fragmentation.
Historical project ledgers contain repeated business field combinations. Set deduplication rules to avoid redundant recall, while ensuring accurate recall of multiple leasing project information for the same lessee.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
Recall Top K | Top 10 Entries | Financial leasing due diligence covers multi-dimensional related information including lessee subject, leased assets, and compliance requirements. 10 entries balances information completeness and retrieval efficiency |
Segment Length | 800–1200 Characters | Most unstructured text in due diligence reports consists of interview minutes and verification opinions. This segment length preserves semantic integrity |
Similarity Threshold | 0.72–0.85 | Distinguish matching accuracy for three semantic categories: lessee subject, leased assets, and compliance requirements. This interval covers matching needs for different scenarios |
PARSE_FILE_TIMEOUT_SECONDS | 300 Seconds | A single due diligence report often contains multiple scanned pages and structured tables. 300 seconds covers complete parsing duration |
Rerank Top K | Top 3 Entries | Core related information of due diligence reports must display first. Returning the top 3 entries after reranking focuses on key business content |
UPLOAD_FILE_MAX_SIZE | 200 MB | A single due diligence report may include multiple attachments. 200 MB covers attachment upload requirements for conventional projects |
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 specific analysis, and it is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Issue: Retrieved files referenced in search results do not match the query topic. For example, querying leased asset ownership information for a specified lessee returns contract documents from other lessees. Cause: No dedicated semantic matching rule is set for structured fields, causing general retrieval to confuse subject-related information.
- Issue: Single retrieval latency exceeds 20 seconds, and some requests return error code
504. Cause: ThePARSE_FILE_TIMEOUT_SECONDSparameter is not adjusted, or batch processing rules for segmented recall are not set for ultra-long due diligence reports. - Issue: The answer output by the knowledge base deviates significantly from actual due diligence content. For example, the unit of leased asset original value is incorrectly marked as ten thousand yuan. Cause: No field-level unit matching rule is configured, causing retrieved structured data to not match the correct unit.
How to Verify Proper Configuration
- Upload a complete financial leasing due diligence report, check whether parsed structured fields fully extract core business information.
- Initiate a retrieval targeting a specific lessee subject, verify whether referenced files in recall results belong to that lessee's project ledger.
- Adjust the
similarity_thresholdparameter, compare recall result quantity and matching accuracy across different values to confirm alignment with business needs. - Test query texts of different lengths, check whether retrieval latency has no obvious abnormal fluctuations and no timeout errors.
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.