Bank reconciliation that eats days each month.
Reconciliation is the job that quietly eats the first days of every month. In this scenario, AI does the matching every day and a person only looks at the lines that genuinely need a decision.
An illustrative scenario, not a client case study. It describes a common situation and how the system would handle it, with no client names and no promised results.
The problem
Imagine a services business with several bank accounts, a couple of company cards, card terminal payouts and a payment processor for online invoices. Each payout bundles many customer payments and deducts fees. Some customers pay two invoices in one transfer, others pay part of one. Card statements arrive with merchant names that look nothing like the supplier name in the books.
Matching all of this by hand is slow and dull, so it gets left until month end. By then there are hundreds of lines, memories have faded, and questions such as "what was this transfer?" take an email thread to answer. The close slips, reports are late, and cash looks different in the bank than in the books for most of the month.
As businesses add more payment methods to keep customers happy, the number of lines to match keeps growing, while the time available to match them does not.
Why the usual tools fall short
Bank feeds and the built-in matching rules in accounting software are a real help with simple, repeating transactions. They struggle with bundled payouts, partial and combined payments, fees netted off deposits and card merchant names that change. Rules also need maintaining, and in many small businesses nobody owns that job.
Spreadsheet reconciliations give control but depend on one careful person and on exporting data from several places. When that person is busy or away, reconciliation simply stops.
How the AI solution works.
Every source is connected
Bank and card feeds, payment processor reports and your open invoices and bills are brought together each day, read only where possible.
Payouts are broken apart
Processor and card terminal payouts are split back into the customer payments and fees they contain, so each part can be matched to the right invoice.
AI proposes the matches
Amounts, dates, references, customer names and your past matching decisions are weighed together, including combined and partial payments. Each proposal carries a short reason.
Exceptions come to a person
Unmatched lines, uncertain matches and anything unusual are listed with the likely candidates side by side, so a decision takes moments instead of a search.
Approved matches are recorded
Once a person confirms them, matches are recorded in your accounting software, and the AI learns from every correction.
What changes
- Reconciliation happens in small daily batches instead of one long session at month end.
- Questions about unknown transactions are asked within days, while people still remember the answer.
- Cash in the books stays close to cash in the bank all month, which makes decisions easier.
- Month-end close can start on reconciled accounts rather than on a backlog.
- The process no longer depends on one person's spreadsheet.
What is needed to start
- Bank and card feeds already connected to your accounting software, or statement exports
- Access to your payment processor and card terminal reports
- Permission to read invoices and bills and to record approved matches
- A person who reviews exceptions on a regular rhythm
Human review and privacy
A person stays in the loop
The AI proposes, a person confirms. You choose which kinds of match may be recorded without review, for example a recurring rent payment, and everything else waits for approval. The reasoning behind each match is visible, so your accountant can audit it.
Your data
Bank data is accessed read only wherever the bank allows it, never used to move money, and kept with access limited to your finance team and accountant. It is not used to train public AI models.
Keep reading
- AI AccountingThe service behind this use case. Invoices captured and coded, bank lines reconciled and month-end reports ready, with a person reviewing the results.
- Month-end reports held up by messy booksAnother AI Accounting use case. With books coded and reconciled through the month, a close checklist and the core reports are ready for review soon after month end.
- AI Follow-UpsA related service. Polite, timely follow-ups on quotes, overdue invoices and reviews, so nothing depends on someone remembering.
- All use casesEvery scenario, grouped by service.
Common across Los Angeles County.
This scenario comes up often for businesses in Los Angeles, Pasadena, Beverly Hills and Torrance. Audits, setup and check-ins happen online, so I work with teams anywhere in the county, and with clients worldwide.
Serving the Los Angeles area
- Los Angeles
- Santa Monica
- Pasadena
- Glendale
- Burbank
- Long Beach
- Beverly Hills
- Culver City
- Torrance
- Inglewood
Does this sound like your business?
Book a free AI audit. We look at how this work is handled today and whether AI Accounting would help, with a person in charge of what matters. No obligation.
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