Bank Reconciliation Software
Matching bank statements to your books by hand doesn't scale past a handful of transactions a day. Yukti's reconciliation engine does the matching; you review the exceptions.
How Yukti Handles This
Statement lines match against rules you define
Bank statements import as a file (OFX, CSV, QIF) or through a live bank feed, and Yukti's reconciliation models match each line to an open invoice, bill, or journal entry using rules you define: exact amount, partial amount within tolerance, reference number, or a combination. A matched line reconciles itself; an unmatched one sits in a queue with the closest candidate matches suggested.
Reconciliation models are reusable across statements
Once you've set up a rule for how your payment processor's payout deposits work, gross sale minus fees, batched daily, every future payout from that processor matches the same way without reconfiguration.
Timing differences are separated from real discrepancies
An outstanding check that hasn't cleared, a deposit in transit, or a bank fee the books haven't recorded are why a book balance and a bank statement balance rarely match on the same day even when both sides are correct. Yukti's reconciliation view separates these out explicitly, so the person closing the books sees which gaps are timing differences and which are genuine discrepancies.
Matching rules scope to account and payment method
An exact amount and reference match handles routine invoice payments, a partial match within tolerance catches a short payment, and an aggregated match handles a single deposit representing several smaller payments settled together. Each rule is scoped to the bank account or payment method it applies to, so a rule tuned for card-processor payouts doesn't misfire on a wire transfer.
Where This Connects to the Rest of Your Books
Reconciliation checks AR and AP against reality
It confirms Accounts Receivable by matching an actual customer payment to the open invoice it settles, keeping the AR aging report honest. It confirms Accounts Payable the same way, matching an outgoing payment to the vendor bill and payment run that generated it, and every match posts back to the general ledger as final proof.
Reusable rules keep the exception queue genuinely small
Once a rule exists for how a payment processor's payouts work, every future payout matches automatically without reconfiguration. That leaves the exception queue for what it should contain: transactions that don't fit an existing pattern, a much smaller list for a controller to review than every line on the statement.
Where the AI agent helps
The reconciliation agent learns from every match you confirm or correct.
Picks up patterns like a payer name that never matches the customer name exactly
Proposes the same match again the next time it sees a similar pattern
Improves its suggestions the more corrections it sees over time
See What This Could Save Your Team
Accounts receivable collections
You could save ~50.0 hours/month
Wakefield Research/Billtrust 2025 (commissioned survey of 500 finance decision-makers): 75% of companies using AI in accounts receivable reported DSO reductions of 6+ days; Hackett Group reports an 8.4-day average reduction. Base case modeled at 10 days.
Bank reconciliation
You could save ~3.8 hours/month
Based on documented ERP implementation efficiency benchmarks: bank reconciliation and synchronization activities typically see a 25% efficiency gain when AI auto-matches routine transactions to bank statement lines, leaving staff to review only the exceptions.
Financial reporting
You could save ~1.5 hours/month
Based on documented ERP implementation efficiency benchmarks: standard and customized financial reporting typically sees a modest 5% efficiency gain, since pulling live data is faster but reviewing and interpreting the numbers stays a human task.
Tax calculation and compliance
You could save ~0.9 hours/month
Automatic tax rate application and GST/VAT compliance reporting replace manually looking up and applying the correct rate on each transaction.
Fixed asset tracking and depreciation
You could save ~2.7 hours/month
Automatic depreciation schedules calculated against each asset replace recalculating depreciation manually in a spreadsheet every period.
Financial audit trail and documentation
You could save ~1.3 hours/month
A complete, automatically maintained audit trail with user tracking and document versioning reduces the time spent reconstructing financial records when an audit request comes in.
General ledger and journal entry classification
You could save ~3.8 hours/month
No independently-verified third-party study measuring general ledger coding and journal entry classification time savings specifically was found during research. This uses an internal working estimate: AI-suggested account coding and recurring journal entry templates reduce the manual classification work that otherwise piles up before month-end close, since routine entries no longer need to be coded from scratch by hand.
Accounts payable invoice processing
You could save ~15.0 hours/month
Ardent Partners State of ePayables research: the average cost to process an invoice manually is $9.84, while Best-in-Class AP teams process invoices at costs 79% lower, driven largely by less manual data entry, matching, and exception handling per invoice. Modeled conservatively at a 40% reduction in per-invoice processing time rather than the full 79% ceiling.
Multi-currency FX rate updates and revaluation
You could save ~2.0 hours/month
No independently-verified third-party study quantifying time savings from automating multi-currency FX rate updates and revaluation specifically was found during research. This uses an internal working estimate: automatic daily exchange rate feeds and automated revaluation entries replace manually looking up and applying the correct rate for every foreign-currency transaction, leaving staff to review the resulting revaluation journal instead of building it by hand.
Budget vs. actual variance reporting
You could save ~4.2 hours/month
No independently-verified third-party study quantifying time savings from automating budget-vs-actual variance compilation specifically was found during research. This uses an internal working estimate: real-time budget tracking against posted actuals removes the need to manually export general ledger data and rebuild a variance view in a spreadsheet for every cost center each month.
GST return prep and e-invoice generation
You could save ~8.0 hours/month
Billentis e-invoicing report (a widely cited industry benchmark on e-invoicing economics): moving from manual/paper invoicing to structured electronic invoicing delivers 60-80% total cost savings, with invoice-issuer savings averaging EUR 6.40 per invoice. Cost savings include more than labor time, so this calculator applies a conservative 40% reduction in per-invoice processing time. In India, GST e-invoicing under the GSTN Invoice Registration Portal (IRP) framework increasingly lets GST return data auto-populate from e-invoice records instead of separate manual entry.
Multi-company consolidation and inter-company elimination
You could save ~4.8 hours/month
No independently-verified third-party study quantifying time savings from automating multi-company consolidation and inter-company elimination specifically was found during research. This uses an internal working estimate: automated inter-company matching and elimination rules replace manually tracing the same transaction across each entity's books and removing it by hand before consolidated statements can be produced.
Total: ~97.9 hours/month, ~$3,260/month
Common Questions
What's the difference between a bank feed and importing a statement file, and does Yukti support both?
A bank feed pulls transactions automatically on a schedule through your bank's connection, while a statement import means downloading a file (OFX, CSV, or QIF) from your bank and uploading it manually. Yukti supports both, so a business without a live feed for their bank still reconciles the same way, just with a manual import step instead of an automatic pull.
How does Yukti handle an outstanding check that hasn't cleared yet when we're trying to close the period?
An outstanding check stays visible in the reconciliation view as a known, already-recorded item that simply hasn't hit the bank statement yet, so it doesn't block a period close. The reconciliation report shows it explicitly as a timing difference rather than an unexplained gap between your book balance and the bank statement balance.
Can one bank deposit that bundles several customer payments be matched against multiple invoices at once?
Yes. An aggregated matching rule handles a single deposit line that represents several smaller payments settled together, splitting it against each open invoice it actually pays, which is the common case with payment processor payouts and batch customer remittances.
What happens to a transaction that doesn't match anything, does it block the reconciliation from closing?
It doesn't post to the ledger on its own. Unmatched lines sit in a queue with the closest candidate matches suggested, and someone has to confirm or manually code them before that specific line reconciles, but that queue is scoped to genuine exceptions since routine transactions match automatically.
Do we have to rebuild our reconciliation rules every month?
No. Reconciliation models are reusable and persist once configured, so a rule built for how your payroll provider's debits work, or how a specific payment processor batches payouts, keeps applying to every future statement without reconfiguration.
See Bank Reconciliation Software in Yukti
Get a walkthrough of how Yukti handles your books, or compare plans to see what is included in the free community edition.