Superseded scope notice. This document describes the original, narrower v1 vision (liquide-middelen only: kiting, unsupported manual journal, restricted cash/ G-rekening, lapping). The owner's
data-audit-engine-requirements-source.md(2026-09-01) explicitly supersedes/expands that scope into a general ledger–wide "Data Audit Engine" (population analysis, JET, revenue, margin, debtors, sampling, workpaper, findings). The authoritative, numbered requirements are now insrs.md, sequenced for delivery inroadmap.md.srs.md§3 documents exactly what carried forward from this document (the four-layer pipeline idea, the determinism/traceability principles, the assist-not-certify stance — all still valid) versus what was dropped (the four liquide-middelen finding types themselves, and the bank-statement-PDF/bank-confirmation-DOCX ingestion paths that supported them — none of these has a corresponding row in the new MoSCoW table). Read this document only for that carried-forward groundwork, not as a still-current scope statement.
Athena is an AI-assisted audit tool focused on the liquide middelen (cash and cash equivalents) balance sheet area for Dutch financial statement audits. It ingests the heterogeneous set of documents an auditor already collects for a cash audit — general ledger bank mutations, XAF-style auditfiles, trial balances, bank statements (PDF), bank confirmation letters (DOCX), bank reconciliations (XLSX), and accounts-receivable receipt registers (CSV) — and cross-references them automatically to surface a specific, well-defined set of audit-relevant patterns that today require an auditor to manually line up dates, amounts, and accounts across multiple files.
Athena does not "audit" a company. It performs the mechanical cross-referencing work that precedes an auditor's judgment call, and it produces flagged, traceable findings for a human auditor to review, investigate, and conclude on.
A cash/liquide-middelen audit routinely requires cross-referencing facts that live in different documents and different formats: a bank mutation booked in the general ledger on one date, the same movement clearing at the bank on a different date, a manual journal entry with no counterparty bank confirmation, a balance in the trial balance that is restricted per a bank confirmation letter's wording, or a sequence of customer receipts that were re-applied to the wrong invoices. Finding these patterns by hand means an auditor manually re-keying or eyeballing rows across a CSV, an XML auditfile, two PDFs, a Word document, and two spreadsheets.
Athena's value is doing that cross-referencing automatically and consistently: parsing each source format into a common transaction/balance model, then running a fixed set of detection procedures against that model, and returning findings that state exactly which source documents and which fields produced the flag. This turns a manual, error-prone reconciliation exercise into a repeatable, auditable first pass — reducing the time an auditor spends finding the needle, while leaving all judgment about materiality, disposition, and audit opinion impact to the auditor.
Because "AI tool that produces audit findings" touches professional liability directly, the boundaries below are deliberate and load-bearing, not just scope trimming:
scope.md and architecture.md for what is in scope, and
the note on the source methodology document for what may follow in later phases).
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