Regulatory Compliance Knowledge Base Retrieval and Recall

What the data for this category looks like

Regulatory policy data comes from official public documents issued by national financial regulatory authorities and industry associations. The update schedule follows regulatory policy changes, with no fixed cycle. Old versions are replaced immediately after new policies are issued or existing ones are revised. Document structures typically include fields such as document number, issuing authority, effective date, chapters and clauses, applicable subjects, penalty provisions, and similar details. Some documents include quantitative standards, with units involving ten thousand yuan, percentage points, business scale thresholds, and similar metrics.

Constraints imposed on knowledge base retrieval and recall by these characteristics

Official source requirements: Retrieval results must match the latest active version, and must synchronize updates from regulatory authorities. No fixed update cycle requires a configurable incremental synchronization mechanism to avoid redundant full updates. Long text structures require retaining clause hierarchy associations during splitting, to avoid breaking contextual logic through splitting. Document number and effective date fields require adding timeliness filtering conditions during retrieval, to only recall currently applicable valid documents. Quantitative standard fields require supporting numerical range matching during retrieval, to ensure recalled content aligns with quantitative requirements of the business scenario.

How to set configurations

Configuration Item	Recommended Value	Rationale
`recall_top_k`	`Top 10-15 results`	Regulatory policy clauses are densely packed. Too many recalled results will exceed the context window, while too few may miss critical compliance clauses
`similarity_threshold`	`0.75-0.85`	Regulatory clauses use precise wording. A higher similarity threshold avoids recalling irrelevant content, while still covering compliance scenarios with similar phrasing
`parse_chunk_size`	`800-1200 characters`	Regulatory policy clauses are mostly coherent statements. This length preserves the complete logic of individual clauses, avoiding truncation of critical information such as penalties and effective conditions
`valid_date_filter`	`Only recall documents with an effective date earlier than the current time and not revoked`	Regulatory policies have timeliness. Invalid old versions must be excluded to ensure retrieved results are compliant and valid
`file_sync_trigger`	`Triggered by file update time`	Regulatory policy updates have no fixed cycle. Incremental synchronization reduces resource consumption and ensures content timeliness
`rerank_top_n`	`Top 3-5 results`	After long text recall, core clauses must be reranked to reduce redundant information processed by the model and improve answer accuracy

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 case-by-case analysis, and it is recommended to test on your own samples before finalizing settings.

Three common configuration mistakes

Phenomenon: Retrieval results return revoked old regulatory policies. Cause: The valid_date_filter parameter is not configured, and expired documents are not filtered out.
Phenomenon: Single retrieval takes more than 20 seconds. Cause: The recall_top_k value is set too high without enabling reranking, or the parse_chunk_size is set too small, resulting in too many split paragraphs that increase retrieval and splicing overhead.
Phenomenon: Retrieved results reference documents unrelated to the query and do not carry metadata. Cause: Metadata return is not enabled in the retrieval configuration, or the similarity_threshold value is set too low, recalling non-core clauses with similar phrasing that do not match the regulatory scenario.

How to confirm your configuration is correct

Manually upload both the old and new versions of the same regulatory policy, submit a query containing effective date keywords, and verify that the retrieval results only return the currently active version.
Submit multiple high-frequency compliance questions, compare retrieval latency and result relevance across different parameter combinations, and adjust recall_top_k and similarity_threshold to values that meet business requirements.
Enable system retrieval logs, check whether the metadata of recalled paragraphs includes fields such as document number and effective date, and confirm that parse_chunk_size does not truncate critical clause content.
Trigger an incremental synchronization task, verify that the system only updates regulatory policy documents modified in the last 7 days, and confirm that the file_sync_trigger configuration logic 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.