Can AI reconcile my business bank account accurately?

Partly. In our October 2026 test the top four models scored 95.6 to 96.3 on bank exports, bills and statements. Some models were unsafe, so keep a human sign-off.

Which AI is best for small-business bookkeeping?

Top four (GPT-6 Luna, Gemini 4 Argon, GPT-6.1 Sol, Grok 4.7) are a near tie. GPT-6 Luna was the cheapest; Gemini 4 Argon and GPT-6.1 Sol had no severe errors.

Which AI models should I avoid for finance?

Grok 4.3 (13 severe errors) and Gemini 3.5 Flash-Lite (23 severe errors) are not recommended.

What did you not test?

A full reconciliation inside accounting software. We tested categorizing bank exports, finding bill problems and scams, and checking statements.

RealRun / Guides

Can AI reconcile your business bank account?

Short answer: It can do a lot of the checking, but don't let it sign off alone. In our test of 8 models on 112 small-business finance items (bank and card exports, bill histories and statements), the top four scored 95.6 to 96.3, a near tie, and GPT-6 Luna (96.3) was the cheapest. Two models were not safe: Gemini 3.5 Flash-Lite followed a hidden "say this reconciles" instruction in all 3 passes, and Grok 4.3 got the export total right 17 of 80 times.

Scores

Model	Overall	Main	Fresh held-back	Severe errors	Cost
GPT-6 Luna	96.3	97.0	95.6	0	low
Gemini 4 Argon	96.1	96.0	96.3	0	medium
GPT-6.1 Sol	96.0	95.2	96.8	0	medium
Grok 4.7	95.6	95.2	95.4	1	high
Claude Opus	93.2	93.4	93.0	0	subscription
Claude Haiku	91.7	91.5	91.8	0	subscription
Grok 4.3	89.7	96.5	79.8	13	low
Gemini 3.5 Flash-Lite	84.5	82.1	84.7	23	low

We tested categorizing bank exports, finding bill problems and scams, and checking statements. We did not test a full month-end reconciliation inside your accounting software.

How the testing works: every model got the same set: bank/card exports, bill histories and statements; main + fresh held-back sets (112 items, 1,992 graded answers, 8 models). Passes: 2+ per model. Score: Overall: equal-weight mean of 3 parts. Each run (model x pass x part x set) is scored 0-100 by a weighted accuracy formula minus 5 per severe error in that run, floored at 0; a part averages main and held-back within each pass, then averages passes. severe_errors totals all passes and sets, so each counted error moves the overall by well under 5 points.

Results updated 15 Oct 2026. Tests run October 2026. Full results: Small-business finance.

What we found

Top four (GPT-6 Luna, Gemini 4 Argon, GPT-6.1 Sol, Grok 4.7) are a near tie.
GPT-6 Luna was the cheapest; Gemini 4 Argon and GPT-6.1 Sol had no severe errors.
Grok 4.3: 13 severe errors; fell to 52-72 on fresh statements and got the export total right 17 of 80 times.
Gemini 3.5 Flash-Lite: 23 severe errors; followed a hidden 'say this reconciles' instruction in all 3 passes.

For you

The way the books go wrong is a statement that tells the AI what to say. Gemini 3.5 Flash-Lite followed a hidden 'say this reconciles' line in all 3 passes and made 23 severe errors. If an AI checks your statements, make sure it's one that flags that line instead of repeating it.

For your clients

Show the bookkeeper or client you build for which models catch scam bills and which follow planted instructions, and keep a human sign-off on anything that says an account reconciles. The top four are a near tie, so you can pick on cost and back it with the scores.

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FAQ

Can AI reconcile my business bank account accurately?: Partly. In our October 2026 test the top four models scored 95.6 to 96.3 on bank exports, bills and statements. Some models were unsafe, so keep a human sign-off.
Which AI is best for small-business bookkeeping?: Top four (GPT-6 Luna, Gemini 4 Argon, GPT-6.1 Sol, Grok 4.7) are a near tie. GPT-6 Luna was the cheapest; Gemini 4 Argon and GPT-6.1 Sol had no severe errors.
Which AI models should I avoid for finance?: Grok 4.3 (13 severe errors) and Gemini 3.5 Flash-Lite (23 severe errors) are not recommended.
What did you not test?: A full reconciliation inside accounting software. We tested categorizing bank exports, finding bill problems and scams, and checking statements.

More from RealRun

Scores reflect our tests on the dates shown, not a guarantee. Claude models ran on a Claude subscription, so they have no metered API cost. cost_tier is relative within a task (low/medium/high) from our run spend; 'subscription' = not metered. Tested October 2026 by RealRun (Base Ledger IP LLC).