In day-to-day operations, a cost may be posted to the wrong matter or entered twice. When receipts, bank transactions, matter numbers, cost types and advances are spread across different screens, documents or team records, the issue may not be noticed in time.
This fragmented data delays preparation of the reconciliation difference list and forces staff to search for supporting records again by hand. Before deciding, the finance officer and matter lawyer must complete missing fields and verify each inconsistency individually.
A common exception is that a bulk payment may cover more than one matter. If this context is not checked, an incomplete or incorrect automation could remove a valid cost or show the wrong balance, so the output cannot be acted on directly.
The system stops after preparing the reconciliation difference list. The finance officer and matter lawyer review the sources and the exception, then approve, correct or reject the output. Direct execution remains disabled because a valid cost could be removed or the wrong balance shown; the system does not replace professional judgement.
Access to receipts, bank transactions, matter numbers, cost types and advances is limited to the minimum permissions needed for the task. Identifiers and sensitive fields are masked where possible, and only the necessary section is sent to the model rather than the full raw file. Access, output and the decisions of the finance officer and matter lawyer are logged; production use does not begin until the organisation approves the retention period and data location.
A good fit
Not a good fit
Receipts, bank transactions, matter numbers, cost types and advances are used. If a required field is missing, the system does not produce a definitive result and flags the missing source for review by the finance officer and matter lawyer.
The workflow stops when the reconciliation difference list is ready and waits for approval by the finance officer and matter lawyer. The reviewers can correct, defer or reject the output with reasons.
The design retains the source identifier, applied rule, exception, output and human decision together. This makes it possible to review how each source record led to a recommendation.
Project led by:DijitalPi
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