- Bank confirmations and invoices are full validation, every value matched to the ledger; bank statements are partial validation, key fields checked and the rest captured.
- Document AI in Enterprise h2oGPTe reads each page with intelligent character recognition and returns structured output that matches your schema, with no templates, no labeling and no model training.
- A person reviews every difference, and your auditors decide what counts as evidence.
- Documents stay inside your environment in any of four deployment options: on-premises, air-gapped, private cloud and cloud.
Make sure the paper agrees with your ledger
Your general ledger holds the cash balances, the loans and the payables. Banks send confirmation letters and statements, and suppliers send invoices, that should agree with those records. Your audit, controllership and finance operations teams check them line by line, often at quarter end and year end.
Most documents agree, so the checking feels like overhead. The ones that do not agree are the reason for the work: a balance that differs from the ledger, a facility nobody recorded, an invoice posted at the wrong amount or in the wrong period.
The documents arrive as PDFs, scans, signed letters and spreadsheets, in a different layout from every bank. Template capture breaks on each new layout, so the checking stays manual and the review window gets shorter every close.
How AI bank statement and audit confirmation validation works
Document AI, a capability of Enterprise h2oGPTe, reads each page with intelligent character recognition and returns structured output that matches the schema you define, with no templates, no labeling and no model training.
Step 1: bring the documents in
Confirmation responses, statements and invoices enter a collection in Enterprise h2oGPTe by upload, connector or API.
Step 2: read every page
Intelligent character recognition reads text, tables, stamps, signatures and handwriting as content and understands what each value means, so different labels for the same figure land in the same field.
Step 3: extract to your schema
You define the fields once as a JSON schema, such as bank, account number, currency, balance date, balance, facility and terms. The extractor returns structured output that matches the schema for every document.
Step 4: check against the general ledger
Each value is joined to your general ledger or trial balance on keys such as entity, account and date. Matches pass; differences become exceptions with the document and the ledger value side by side.
Step 5: act on the exceptions
An agent in H2O AI Super Agent can route each exception to its owner, draft the follow-up to the bank or the supplier, and assemble the evidence for the workpaper. A person approves every step.
Confirmations and invoices get full validation, statements get partial validation
A bank confirmation reports what the bank holds for you on a date: account balances, loans, guarantees, overdraft facilities and other arrangements. Every item on it gets matched to the ledger, including items the ledger does not show, so a facility with no ledger entry becomes an exception on its own. Invoices follow the same pattern against accounts payable.
A bank statement is partial validation. The fields that must agree, account holder, account number, statement period, opening balance and closing balance, get checked against the ledger. The transaction lines are captured as structured data for sampling and reconciliation, not individually judged.