AI can help organize records and surface likely matches, but an efficient workflow should make it easy for a responsible person to check important results. Human review works best when it is built into the process rather than added as a vague final step.
Show the evidence behind a suggestion
Reviewers need to see the source documents and the fields used to produce a recommendation. Preserve the original records and make it possible to compare amounts, dates, currencies, references, and counterparties without hiding uncertainty.
Route exceptions to the right person
Incomplete, conflicting, or unusual records should be flagged for review instead of being forced into a confident-looking answer. Assign an owner and keep open questions visible until they are resolved.
Record corrections and approvals
When someone changes a suggested match or classification, record what changed and why. Keep approval separate from automated preparation so the person responsible can verify the relevant evidence before accepting an outcome.
Use checks after review
Reconcile totals to source statements, look for duplicate entries, and track unresolved items. Periodic samples of accepted results can help identify patterns that need better rules or additional reviewer guidance.
Keep accountability clear
Automation can support preparation, but it does not replace professional judgment or the customer’s responsibility to verify financial records. The workflow should make responsibilities and approvals explicit.
General educational content only; not legal, accounting, or tax advice. Confirm current Venezuelan requirements with a qualified adviser.
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