Conversation Logging and Audit for Joint-Stock Bank

What the Data for This Category Looks Like

Joint-stock bank investment research data primarily comes from internal compliance research report repositories, publicly disclosed documents from the central bank and banking and insurance regulatory authorities, domestic mainstream financial databases, and periodic and ad-hoc announcements of listed companies. Data update rhythms fall into three categories: Macro policy data is synced in real time upon release. Listed company announcement data is stored on the same day of disclosure. Internal investment research reports are updated within 1 hour after passing review.

Each document has fixed metadata fields: issuing institution, release time, involved ticker code, rating level. Rating level uses standardized wording. Ticker codes follow a 6-digit numeric format. Monetary field units are uniformly ten thousand yuan or hundred million yuan.

Constraints Imposed by These Characteristics on Conversation Logging and Audit

The multi-source nature of investment research data requires conversation logs to fully record data call links. This ensures every cited content can be traced back to its original source during audits. Real-time updated macro data requires logs to synchronously record data versions. This prevents audit result deviations caused by data iterations. Standardized metadata fields must be included in log archiving. This enables quick audit retrieval by dimensions such as issuing institution and ticker code. Compliance requirements for peer research reports require logs to retain records of user-triggered compliance verification steps. This ensures citations in investment research conclusions comply with internal risk control rules. The fixed 6-digit ticker code format can be used for automatic verification of log fields. This reduces manual verification costs during audits. The internal research report review process requires logs to associate the ID of the corresponding review node. This ensures investment research conversation content matches reviewed original materials.

Configuration Settings

Configuration Item	Recommended Setting	Rationale
`maxContext`	`First 20 conversations + 10,000 recent characters`	Joint-stock bank investment research conversations often involve multi-round ticker comparisons and data citations. Sufficient context ensures conversation coherence while staying within the log storage limit of FastGPT V4.9.13
`LOG_RETENTION_DAYS`	`180 days`	Banking risk control audits require retaining at least six months of operational logs, which complies with internal compliance standards
`conversation_record_api_offset`	`0`	Investment research scenarios require obtaining complete conversation history in reverse chronological order. Setting the offset to 0 directly retrieves the latest conversation records
`AUDIT_TRIGGER_CONDITION`	`When the conversation contains investment research ratings or 6-digit ticker codes`	Core investment research content must forcibly trigger audit verification, covering core compliance and risk control scenarios
`PARSE_FILE_TIMEOUT_SECONDS`	`600 seconds`	Large research report documents take longer to parse. Setting a reasonable timeout prevents incomplete log recording caused by timeouts
`maxRetries`	`3 retries`	Investment research data calls may fail due to interface fluctuations. A reasonable number of retries ensures complete log retrieval

The parameter values provided on this page are common starting points for configuration. Actual values are affected by material format, data volume and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.

Three Common Configuration Mistakes

Phenomenon: Conversation records returned by the conversation_record_api interface do not match user questions. Cause: The conversation_record_api_offset parameter is not set correctly, or the correspondence between conversation IDs and reply IDs is not spliced in reverse chronological order.
Phenomenon: System prompts do not take effect as expected in each conversation. Cause: The system_prompt configuration is not placed at the starting node of the conversation flow, leading to abnormal node execution order and failure to trigger the preset audit verification logic.
Phenomenon: The original source of data citations is not retained in logs. Cause: The LOG_DATA_SOURCE_TRACK configuration item is not enabled, or source fields are not recorded synchronously when calling data interfaces, making it impossible to trace content sources during audits.

How to Verify Proper Configuration

Call the conversation_record_api interface, pass a test user ID, check if the returned conversation list is sorted in reverse chronological order, and if the question and answer fields of each record correspond one-to-one.
Trigger an investment research conversation containing a 6-digit ticker code, check if the audit verification process is automatically triggered, and if corresponding verification records are retained in the logs.
View the effective status of the LOG_RETENTION_DAYS configuration item, confirm that conversation logs older than the set number of days have been archived or deleted according to rules.
Test the parsing process of large research report documents, confirm that parsing time does not exceed the threshold set by PARSE_FILE_TIMEOUT_SECONDS, and there are no timeout errors in the logs.

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.