Validation & Exception Management
Automated first-pass checks clear the routine records. Agents prepare the exceptions. Senior people review the cases that need judgment, not the whole pile.
The business problem
In many teams the most experienced people spend their day re-checking work: every invoice, claim, reconciliation or record, against rules they carry in their heads. Most of it is fine. They check it all because they cannot tell in advance which items are not.
The result is a queue that grows with volume, inconsistent decisions between reviewers, and exceptions that arrive with none of the context needed to resolve them.
How it runs today
- Every record goes through the same manual review, regardless of risk.
- Reviewers apply rules from memory or a checklist that is out of date.
- When something fails, the reviewer gathers context from three or four systems before acting.
- Exceptions are tracked in a spreadsheet or inbox, with no clear owner or deadline.
- Nobody can say how many exceptions there are, of what type, or why they keep happening.
Automate the work. Keep judgment human.
Plain automation where the logic is fixed. Agents where the input is messy. People wherever consequences or ambiguity rise.
Deterministic automation
- Deterministic checks: required fields, formats, tolerances, duplicates and matches against reference data.
- Two- and three-way matching where the matching rules are fixed.
- Auto-clearing records that pass every rule, with a sample held back for review.
- Routing exceptions to the right queue and tracking age against a deadline.
Agents
- Classifying why a record failed, when the reason is in free text or a document.
- Gathering the context for each exception from the systems involved, so the reviewer starts with the facts.
- Proposing a resolution for routine exception types and drafting the follow-up message.
- Spotting recurring exception patterns and summarizing them for the process owner.
People stay responsible for
- The rules and tolerances themselves, and any change to them.
- Exceptions that are novel, high-value or affect a client relationship.
- Approvals for write-offs, payments, overrides and anything hard to reverse.
- Fixing the upstream cause when the same exception keeps coming back.
Systems and integration
- ERP, billing and accounts payable
- Industry systems of record (claims, TMS, practice management)
- Reference and master data
- Case, ticket or exception queues
- Email for counterparty follow-up
Validation and controls
- Validation rules are versioned, owned and reviewed before they change.
- Auto-cleared records are sampled and checked by a person on a fixed schedule.
- Agents can propose resolutions; only people approve overrides and write-offs.
- Stop conditions pause auto-clearing if exception rates move outside the normal range.
- Every decision is logged with the rule, evidence and approver.
What we measure
- Share of records needing human review
- Errors and rework per 100 records
- Exception age and time to resolve
- Reviewer hours per 100 records
- Repeat exceptions by root cause
An example workflow design
Illustrative, not a client result. It shows where each responsibility sits.
Accounts payable invoice exceptions
Trigger: A supplier invoice is received and posted to the AP queue.
An illustrative design showing how we would approach the workflow. Not a client result.
- 1SystemERP holds the purchase order, goods receipt and supplier master data.
- 2AutomationRuns the three-way match and tolerance checks. Clean invoices are cleared for payment; a sample is held for review.
- 3AgentFor each failed match, classifies the cause, pulls the PO history and supplier emails, and proposes a resolution.
- 4AgentDrafts the supplier query or the internal request to the budget owner.
- 5HumanThe AP specialist approves, edits or rejects the proposal. Overrides and credit notes stay with people.
- 6SystemThe ERP is updated and the exception type, cause and outcome are logged.
Controls
- Agent cannot release payment or change supplier bank details
- Variances above tolerance always need human approval
- Weekly sample review of auto-cleared invoices
- Auto-clearing pauses if the exception rate spikes
What we would measure
- Invoices needing manual touch
- Exception resolution time
- Payment errors found after release
- Cost per invoice processed
Where we see this pattern
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