Deployment and Upgrade for Rural Commercial Bank Intelligent Due Diligence Reports

Data for rural commercial bank intelligent due diligence reports comes from four main sources: internal credit management systems, the People's Bank

What the data for this use case looks like

Data for rural commercial bank intelligent due diligence reports comes from four main sources: internal credit management systems, the People's Bank of China credit reporting system, public enterprise industrial and commercial information, and operation filing data from local agricultural and rural departments. Data for one-time due diligence tasks is pulled in real time when the task is submitted. Regular due diligence data for existing customers is synchronized and updated on a quarterly basis. Documents use structured tables as their core framework, with fields including customer name, unified social credit identifier, credit balance, operating cash flow, and regulatory rating level. Some documents include OCR-recognized text from pre-loan interview minutes and on-site inspection photos. Field units are mostly ten thousand yuan, rating identifiers, and similar types.

Constraints Imposed on Deployment and Upgrade by These Characteristics

Rural commercial bank due diligence data has a high structured proportion and contains financially sensitive information. During deployment, configure structured data desensitization rules and encryption options for vector storage to prevent sensitive data leaks. Data updates follow two schedules: real-time and quarterly. During upgrade, support both incremental synchronization and full synchronization task scheduling modes to ensure tasks with different update frequencies run normally. Some documents contain unstructured text from OCR recognition. During deployment, configure local OCR engine parameters to avoid parsing delays caused by cross-network calls. Individual due diligence reports have long text lengths. During deployment and upgrade, adjust relevant parameters for long text parsing and recall to avoid content truncation or recall failure.

Configuration ItemRecommended ValueRationale
PARSE_FILE_TIMEOUT_SECONDS600 secondsRural commercial bank due diligence reports often include multi-page OCR scans and long text. 600 seconds covers the full parsing duration
UPLOAD_FILE_MAX_SIZE2000 MBA single due diligence report may include multiple attachments. 2000 MB meets bulk upload requirements
maxContext8000–12000 charactersDue diligence report text is lengthy. This range retains complete context for recall and generation
recall countTop 10 entriesRural commercial bank due diligence data fields are concentrated. 10 recall entries cover core associated information
rerank return countTop 5 entriesSimplified reranking results improve due diligence report generation efficiency
SYNC_INTERVAL_MINUTES15 minutesDue diligence data for existing customers requires regular synchronization. 15 minutes balances real-time performance and server load

The parameter values provided on this page are general recommendations used as a starting point 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

  • Symptom: Redis fails to start. Logs show connection timeout or port occupation. Cause: Redis is not deployed on a server in the same network segment as FastGPT, or access permissions for the default port 6379 are not enabled.
  • Symptom: Abnormal number of recall results when generating due diligence reports. Core fields are not recalled. Cause: The recall count parameter was not adjusted, and the default short text recall configuration was used, which cannot cover core information from long documents.
  • Symptom: No return results after connecting a private reranking model in version 4.9. Cause: The correct model API address and key were not filled in the model configuration page, or model input and output format adaptation was not configured.

How to Verify Successful Configuration

  • Upload a standard rural commercial bank due diligence report. Check if parsed fields match preset structured fields. Adjust PARSE_FILE_TIMEOUT_SECONDS until parsing completes without truncation.
  • Run an incremental synchronization task. Check if synchronized updated data matches the latest records from the internal credit system. Adjust SYNC_INTERVAL_MINUTES until the synchronization frequency meets business requirements.
  • Initiate a due diligence report generation request. Check if the returned results include core fields such as credit and cash flow. Adjust recall count and rerank return count until results meet business expectations.
  • Log in to the system backend. Check the running status of the Redis service. Confirm port openness and normal connection. Adjust server firewall rules until no connection errors occur.

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.