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Pyalm Books gives you the evidence an auditor asks for in one place — a double-entry ledger, manual journals, period locking, bank reconciliation, receivables ageing and VAT returns. Free while in beta.
Paste a column of amounts and see how closely their leading digits follow Benford's Law. Digits that are over- or under-represented are flagged so you know where to look first.
Paste a column of amounts (invoices, payments, expenses, journal lines) or upload a CSV. Runs entirely in your browser.
Pyalm Books gives you the evidence an auditor asks for in one place — a double-entry ledger, manual journals, period locking, bank reconciliation, receivables ageing and VAT returns. Free while in beta.
In many naturally occurring financial datasets, about 30% of amounts start with 1 and fewer than 5% start with 9. People inventing numbers, splitting invoices to stay under an approval limit, or repeating a fixed price disturb that pattern. The test does not prove fraud; it tells you which digits and which transactions deserve a second look.
The tool reports mean absolute deviation (MAD) with Nigrini's conformity bands, a chi-square statistic across the nine digits, and a z-score for each digit. Tap a digit's bar to list every transaction that starts with it and export those rows for follow-up testing. Benford analysis works best on 300 or more items that span several orders of magnitude.
📖 Read the full guide: Benford's Law for Auditors: A Practical Guide
Spot repeated payments and invoices by amount, date, vendor and reference.
Attribute and monetary-unit sample sizes, plus a seeded random selection you can reproduce.
Find missing and duplicated invoice, credit note or voucher numbers in a list.
Check that debits equal credits and get hints on why a trial balance is out of balance.
Amounts that arise from many independent events and span a wide range — invoices, expense claims, payments, journal lines, inventory values. It does not suit assigned numbers (cheque numbers, phone numbers), data with a fixed range (ages, percentages) or amounts driven by price lists.
No. Non-conformity can come from a legitimate price point, a bulk contract, rounding policy or an approval threshold. It is a screening procedure that directs sampling, not evidence in itself.
At least a few hundred. With small samples, random variation alone can make the digits look unusual, and the chi-square test becomes over-sensitive with very large ones — rely on MAD as well.
No. The file is read and analysed in your browser; nothing is sent to Pyalm or anyone else.
