What the data for this category looks like
The data for insurance intelligent due diligence reports primarily comes from internal underwriting systems and claims databases of insurance companies, official public documents from the banking and insurance regulatory authority, and data from third-party credit reporting agencies. Data update frequency changes with business nodes: underwriting data is synchronized in real time along with the insurance application process, and regulatory public data is updated quarterly. Most documents combine structured tables and semi-structured text, containing fields such as policyholder identity information, risk level of insured subjects, number of past claims, and compliance check items. Field units are mostly ten thousand yuan, times, level identifiers, and similar units.
What constraints these characteristics impose on the multi-turn conversation and prompt engineering link
Insurance due diligence data includes a large number of structured fields and semi-compliant text. Multi-turn conversations need to clearly distinguish the instruction boundaries between structured field extraction and compliance text interpretation. Real-time synchronized underwriting data requires triggering data refresh on demand during the conversation flow to avoid calling outdated information. Quarterly updated regulatory data needs to specify the data time range in the prompt to prevent the model from using outdated compliance check basis. Document lengths can be significant, so the context window for single-turn conversations must be limited to avoid redundant information interfering with core queries.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Insurance due diligence report texts are lengthy, so sufficient context must be retained to correlate field information across multi-turn queries |
similarityTopK | Top 8–12 entries | Insurance due diligence data has many fields, so a sufficient number of relevant entries must be retrieved to cover all complete check items |
rerankTopN | Top 3–5 entries | Re-rank retrieved entries to focus on highly matched core due diligence fields |
systemPrompt | Must specify the data time range as the most recent quarter, prioritize extracting structured fields | Adapt to the update rhythm and structured characteristics of insurance due diligence data, prevent the model from using outdated or non-core information |
conversationTimeout | 120 seconds | Insurance due diligence queries require processing associations across multiple data sources, so sufficient response time must be reserved |
maxConcurrentRequests | Calibrated according to server load | Adapt to scenarios where multiple users initiate due diligence queries simultaneously, avoid request blocking |
The parameter values provided on this page are all common recommended 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 on your own samples before finalizing settings.
Three common mistakes
- Symptom: The conversation interface returns a "knowledge base is empty" prompt, but all document content can be viewed normally on the knowledge base management page. Cause: The data source association of the conversation process was not re-bound after migrating the knowledge base, and the knowledge base ID called by the conversation does not match the knowledge base actually stored.
- Symptom: The AI reply annotations in the workflow are only triggered after the streaming reply is fully completed. Cause: The
streamResponseconfiguration item is not enabled, causing the annotation trigger logic to be bound to the end of full reply generation. - Symptom: Context confusion occurs after multiple calls to due diligence data in multi-turn conversations. Cause: The valid range of
maxContextis not limited, causing redundant historical information to interfere with field extraction for the current query.
How to confirm the configuration is correct
- Initiate a single due diligence query, check whether the returned results include regulatory data fields within the specified time range, and confirm that the constraints of the system prompt take effect.
- Import a complete insurance due diligence report, trigger the conversation process, check whether the returned context contains the field information required for the core query, and confirm that the context window configuration is reasonable.
- Initiate a multi-user concurrency test, observe the request response status, and confirm that the concurrent request parameters are adapted to the current server load.
- Test the streaming reply scenario, check whether annotation content is gradually displayed along with streaming output, and confirm that the streaming reply configuration is correct.
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.