HTTP Interfaces and External Systems for Insurance

What the Data for This Category Looks Like

Data sources for insurance intelligent due diligence reports include internal underwriting systems of insurance institutions, financial and health certificates submitted by policyholders, and industry regulatory disclosure documents. There are two data update schedules: real-time synchronization for underwriting-related data, and daily updates for historical claim data. Document structures include policyholder identity fields, health disclosure details, past claim records, compliance check items, and risk rating fields. Some documents are in multi-page PDF format, while others are structured JSON format. Fields include units such as percentage, count, and rating level, and some fields are enumeration values. For example, risk levels are divided into three categories: low, medium, and high.

What Constraints Do These Characteristics Impose on HTTP Interfaces and External Systems

Decentralized data sources and inconsistent update schedules require HTTP interfaces to support both full synchronization and incremental pull invocation modes to adapt to different business trigger scenarios. Fields include enumeration values and numerical types with units, so interfaces need to preset strict parameter validation rules to block requests that do not meet format requirements. The content volume of a single report varies greatly, so interfaces need to support chunked transfer or paged returns to avoid single-request timeouts. Insurance due diligence data involves personal privacy and industry compliance requirements, so interfaces need to integrate additional identity authentication and data desensitization configurations to ensure data transmission and storage meet regulatory requirements.

How to Set Configurations

Configuration Item	Recommended Value	Rationale
`HTTP_REQUEST_TIMEOUT`	`600 seconds`	Insurance due diligence reports usually contain multi-page structured content and a large number of validation logic, which takes a long time to parse and transmit. 600 seconds covers the processing duration of most scenarios.
`API_REQUEST_AUTH_TYPE`	`API_KEY + IP_WHITELIST`	Internal systems of insurance institutions require strict access control. Combining API keys and IP whitelists can reduce the risk of unauthorized access.
`RESPONSE_DATA_STRUCT`	`STRICT_JSON_SCHEMA`	The fields of insurance due diligence reports have strict enumeration and unit requirements. Strict JSON Schema validation can ensure the compliance of returned data formats.
`UPLOAD_FILE_MAX_SIZE`	`500 MB`	A single insurance due diligence report may contain multiple attached images and structured documents. 500 MB covers the volume of most conventional reports.
`PARSE_CHUNK_SIZE`	`800–1200 characters`	The text content of insurance due diligence reports contains a large number of professional terms and long paragraphs. This range balances parsing accuracy and processing efficiency.
`HISTORY_MESSAGE_MAX_LENGTH`	`20000 characters`	Historical interaction information for insurance due diligence usually contains multiple rounds of validation records. This length can save complete context without occupying too many resources.

The parameter values provided on this page are common recommendations used as a starting point for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require targeted analysis. It is recommended to conduct testing using samples provided by the organization before finalizing the configuration.

Three Common Mistakes

An HTTP request returns 400 Bad Request with the prompt invalid parameter name or missing required field. The request body parameter names and values are not configured according to the field definitions of the insurance due diligence report. Generic parameter names are mistakenly used instead of insurance-specific field names, for example, writing health_report as general_data.
An external database interface call returns 1045 Access denied. Dedicated access permissions for the internal database of the insurance institution are not configured, and a generic test account is used, resulting in authentication failure.
The due diligence results returned by the interface are not associated with historical interaction information, or the prompt history parameter invalid is displayed. Historical parameters are not passed according to the FastGPT OpenAPI specification. Historical messages are mistakenly placed in non-specified fields of the request body, for example, placing the history array under the query field.

How to Confirm the Configuration Is Correct

Submit a test request, verify that the returned HTTP status code is 200 OK, and the response body contains exclusive fields of the insurance due diligence report, such as risk_rating and financial_debt_ratio.
View interface logs to confirm that the request parameter names and values fully match the field definitions of the insurance due diligence report, with no format errors.
Simulate an incremental pull scenario, verify that the interface only returns data with an update time later than the specified timestamp, which matches the configured update schedule.
Trigger data desensitization validation, confirm that sensitive information in the returned results has been properly processed and meets compliance requirements.

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.