What data looks like for this category
Intelligent due diligence report data for investment platforms primarily comes from public regulatory disclosure documents, target company annual and quarterly financial reports, industry research reports, and public materials of counterparties. Update cycles vary significantly by data source type. Regulatory documents are released in real time. Financial reports are updated quarterly. Research reports are updated monthly. Document structures include target entity identification fields, financial indicator fields, compliance record fields, and transaction clause fields. Some documents include unit annotations. For example, financial indicators are recorded in ten thousand yuan units.
What constraints these characteristics impose on knowledge base retrieval and recall
Dispersed multi-source data sources require retrieval systems to support mixed access to external web pages and API interface data sources. Differentiated update frequencies require flexible incremental synchronization mechanisms, to avoid excessive resource usage from full synchronization. Wide variation in document length requires adaptive variable text chunking parameters, to balance retrieval accuracy for long financial reports and short compliance announcements. Field features with units require retaining field semantics and unit information during retrieval, to avoid recall results where indicators and units do not match. Due diligence requirements involving multiple associated fields require support for precise filtering based on business fields.
How to configure the settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
external_knowledge_source_type | API integration + web crawling hybrid | Adapts to the multi-source feature of investment platform due diligence data from public web pages, API interface financial reports, and regulatory data |
chunk_size | 800–1200 characters | Covers text lengths of long-form financial reports and short compliance announcements, balances context completeness and retrieval accuracy |
similarity_threshold | 0.85–0.92 | Filters low-relevance non-target documents, avoids interfering with the accuracy of due diligence conclusions |
recall_top_k | Top 10 results | Meets the need for multi-dimensional corroboration in due diligence reports, covers major associated data sources |
incremental_sync_interval | Every 6 hours | Balances real-time performance and resource usage, adapts to update cycles of quarterly financial reports and real-time regulatory documents |
field_retrieval_enable | Enabled | Supports precise filtering based on business fields such as target ticker and disclosure date, improves recall accuracy |
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. It is recommended to test on your own samples before finalizing settings.
Three common configuration mistakes
- Phenomenon: Search results include irrelevant documents with semantic similarity below the preset threshold. Cause: The
similarity_thresholdparameter is not configured, or the value is set too low, failing to filter low-relevance content. - Phenomenon: The order of custom-chunked documents is disrupted after upload. Cause: The
duplicate_removalparameter is enabled, and original chunk order markers are not retained, leading to failure of custom index associations. - Phenomenon: External website data sources are not synchronized to the knowledge base. Cause: The
external_knowledge_api_keyis not configured correctly, or crawling rules do not cover the target website’s robots protocol restrictions, leading to synchronization task failure.
How to verify successful configuration
- Run a test search, enter the target ticker keyword, and verify that the document sources of returned results cover the preset external data sources.
- View the knowledge base synchronization logs, confirm that incremental synchronization tasks are automatically triggered and completed according to the configured time interval.
- Search for keywords of specified business fields, and verify that returned results only include documents matching that field.
- Upload duplicate test documents, and verify that the custom chunk order is retained and not automatically disrupted.
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.