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Bank reconciliation

Bank reconciliation, matched by AI. Your team confirms.

The bank statement comes in and the model proposes which open invoice each payment settles, in Business Central, Dynamics 365, legacy ERPs and bank exports. Your accounting team confirms matches instead of hunting for them.

Our team replies within two business days. Scope and price agreed before we start.

Tell us what you need.

    Where it slows down

    Reconciliation eats the days you need for the close.

    • Line by line

      Every statement line matched to an invoice by hand, every period.

    • Partial and combined payments

      One transfer for three invoices, or one invoice paid in two parts, and nobody wrote down which.

    • References that do not match

      Customers type their own reference, the bank shortens it, the ERP expects another.

    • Several ERPs, several banks

      Each market reconciles in its own system, and the group view waits for all of them.

    • Open items that stay open

      Unmatched payments pile up and reminders go out for invoices that were paid.

    • No trail

      When auditors ask why a payment was booked against an invoice, the answer lives in someone's head.

    Proven in production

    Tested on real statements, not a demo file.

    less manual entry at Bredent Medical, across four markets
    60%less manual entry at Bredent Medical, across four markets
    European markets on Dynamics 365 and legacy systems, one view
    4European markets on Dynamics 365 and legacy systems, one view
    match rate on payment reconciliation at a betting and gaming operator
    99.25%match rate on payment reconciliation at a betting and gaming operator
    transactions a month in that same reconciliation
    4.6Mtransactions a month in that same reconciliation

    Bredent Medical is named with permission. The match rate comes from a separate production system for an operator we do not name.

    Read the Bredent Medical case

    What it looks like

    Bank reconciliation in 30 seconds

    Silent, with captions. What the agent reads, what the rules decide and where a person steps in.

    How we start

    One bank, one entity, real statements. Then the rest.

    1. 01

      Pick the account

      One bank account and one entity with volume and a person who owns the reconciliation.

    2. 02

      Run it on your statements

      The model proposes matches on last month's real statements, so you see the hit rate before anything goes live.

    3. 03

      Connect it

      To your ERP and bank exports. Confirmation stays with your accounting team; nothing books without them.

    4. 04

      Add accounts and markets

      The next account goes faster than the first. Your team owns every rule.

    Works with what your team already runs

    • Dynamics 365
    • SAP
    • NetSuite
    • Legacy and local ERPs
    • Bank exports (MT940, CAMT, CSV)
    • Payment providers
    • Excel and CSV

    Why SIEL

    We built this for a distributor with four markets and four sets of habits.

    Your systems stay
    We connect Dynamics 365 and the legacy ERPs instead of migrating them.
    AI proposes, people confirm
    Every match is a proposal until someone in accounting confirms it.
    Traceable
    Each match links the statement line, the invoice, the rule or model output and the person who confirmed it.

    Start the conversation

    Which account takes the longest to reconcile?

    Tell us the bank, the ERP and the monthly volume. Our team reads it and replies within two business days.

    • No generic sales sequence.
    • Scope and price agreed before we start.
    • We tell you when AI is not the right answer.