AI for spotting errors and fraud in your books

Why small businesses need this

In a small business, one or two people often enter, approve and pay. That is efficient, and it also means mistakes and misuse can go unnoticed for months. Owners rarely have time to read every voucher. AI can read every one, every day, and surface the few worth a look. Our guide on internal controls for small business covers the basic controls this sits on top of.

Errors AI catches well

Patterns that may point to misuse

These are not proof of fraud. They are the patterns that are worth a quiet look:

• New supplier, quick payment. A supplier created recently, paid soon after, with round amounts and no stock received.
• Bank details changed on a regular supplier just before a large payment.
• Discounts or credit notes rising for particular customers or entered by one user, especially just after month-end.
• Cash sales falling while stock moves out at the usual pace.
• Edits and deletions of old vouchers, especially after a period was reviewed.
• Payments just under an approval limit, repeated.

Treat a flag as a reason to ask, politely and with the document in hand. Most turn out to have a simple explanation.

A weekly review routine

1. Run duplicate checks on purchase bills and payments for the week.
2. Review the top ten payments by amount, with the bill behind each.
3. Look at credit notes and discounts, by customer and by user.
4. Check any new parties created and any changes to existing party bank details.
5. Compare cash in the books with the cash box.
6. Look at deleted or altered vouchers.

An owner can do this in half an hour if the flags are prepared. The Day Book is the base report for most of it; see the Tally Day Book.

Example

A distributor's AI check flags that credit notes for “rate difference” have grown from about ₹15,000 a month to ₹1,10,000 over three months, almost all to six customers on one salesperson's route, and all entered in the last two days of each month. The owner pulls the notes. Some are genuine scheme adjustments that were never approved in writing; a few are not supported by any scheme. The fix is a rule: rate-difference notes above ₹5,000 need the owner's approval, and schemes are set in writing before the month starts. See managing dealer schemes and discounts.

False alarms and how to cut them

• Monthly rent of the same amount is not a duplicate. Tell the tool which payments recur.
• Festive season spikes are not anomalies. Compare with the same month last year, not last month.
• Bulk orders from a new customer may look odd and be perfectly normal.

Too many false alarms and people stop reading them. Tune the checks so the weekly list is short enough to act on. A list of five items that someone reads every Monday is worth more than a list of fifty that nobody opens.

Limits

AI only sees what is in the books. It cannot see goods that were never billed, cash that was never entered, or a deal agreed on the phone. Physical stock counts, bank reconciliation, and separating who enters from who approves remain the basic defences. If you suspect fraud, speak to your CA before confronting anyone, and preserve the records.

Checking Tally books with Cashflow OS

Cashflow OS gives owners the Day Book, ledgers, outstanding and reports from their Tally data on the phone, so the weekly review can happen anywhere. The owner can also see the team's activity in the app. Its AI assistant answers questions from the synced books, such as “list credit notes over ₹10,000 this month” or “which suppliers were paid more than ₹1 lakh this week”. Deleting a voucher in Tally from the app needs a reason and an authorised user.