Model Integration and Configuration for Funding Source KYC

What the data for this category looks like

Funding source KYC data comes from multiple sources. These include user-uploaded paper credential scans, electronic bank statement PDFs, pay stubs, asset proof documents, and structured transaction details returned from integrated compliance systems. Data updates follow two patterns. Single verification static data sources update only when a user submits a request. Batch synchronized data sources sync on preset cycles. Documents include two content types. Structured fields cover transaction amount, transaction time, counterparty account entity, and transaction channel. Unstructured content includes OCR text from credential scans and handwritten notes. Field units follow fixed rules. Transaction amount uses Chinese Yuan as its unit. Transaction time uses ISO 8601 format. The account entity field is a string type.

What constraints do these characteristics impose on model integration and configuration?

Mixed structured and unstructured data requires two key configurations. First, configure structured field extraction rules. Second, enable unstructured text understanding capabilities. These configurations must adapt to numeric field extraction accuracy and natural language semantic understanding respectively. Credential types cover multiple formats, such as bank statements and pay stubs. Multimodal models must be configured to support OCR parsing and content extraction for PDF and image formats. The model's input token limit must also be adjusted to accommodate long document bank statements. Batch synchronized data source update cycles require timed task parameter configuration. Reasonable timeout thresholds must be set to avoid batch task interruptions. Compliance field verification requirements mandate model output format constraints. These ensure extracted fields such as transaction amount and transaction time meet preset standards.

Configuration Settings

Configuration Item	Recommended Setting	Rationale
`multi_modal_enable`	`true`	Supports multimodal input processing to meet OCR parsing needs for images and PDF formats of funding source credentials
`max_context_tokens`	`8000–16000`	Accommodates content extraction for long documents such as bank statements, prevents loss of critical transaction information due to long text truncation
`structured_extract_schema`	`["transaction_amount", "transaction_date", "counterparty_account", "voucher_type"]`	Clarifies required structured fields to ensure model output complies with KYC verification standard field requirements
`parse_timeout_seconds`	`600 seconds`	Accommodates time requirements for long document parsing and multimodal processing, prevents task interruption due to timeout
`batch_task_max_concurrency`	`5`	Controls concurrency of batch verification tasks to avoid exceeding call limits of compliance systems
`api_log_enable`	`true`	Enables call log recording to facilitate troubleshooting of call failures via channels such as OneAPI
`model_allow_list`	`["qwen3", "gpt-4o"]`	Adapts to current mainstream multimodal large models, supports calls to compliant models such as qwen3

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

Three Common Configuration Errors

Phenomenon: Calling the qwen3 model returns a 413 Request Entity Too Large error. Cause: The max_context_tokens parameter was not adjusted, and the uploaded long bank statement document exceeded the model's default token limit.
Phenomenon: Extracted transaction amount fields are empty or have incorrect formats. Cause: The structured_extract_schema was not configured to clarify required extraction fields, so the model did not output in the compliance-mandated field format.
Phenomenon: Detailed logs cannot be viewed after a OneAPI call failure. Cause: The api_log_enable configuration item was not enabled, and no log storage directory was specified. This results in no retention of detailed call process information.

How to Confirm Configuration is Complete

Upload a single standard bank statement PDF. Check if the parsed structured fields match the preset structured_extract_schema to verify the extraction configuration is effective.
Trigger a single large model call and view platform logs. Confirm that the logs include complete request and response information to verify the log configuration is correct.
Submit multiple test credentials. Observe whether the task processing rhythm matches the expected concurrency settings to verify the batch call configuration is reasonable.
Adjust the max_context_tokens parameter and upload an ultra-long bank statement document. Confirm that the document is not truncated to verify the token limit configuration is effective.
Check that the FastGPT runtime version is V4.9.7 or higher. This ensures all configuration items are valid parameters supported by the platform.

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.