Import CSV remittances into Xero
Upload any CSV remittance file and Remittance Go auto-detects the columns, matches every invoice against Xero, and creates a batch payment — no manual data entry, no spreadsheet gymnastics.
Process your first CSV remittance →
CSV remittances come in too many formats
Every payer exports different columns with different names. Cleaning the file before you can even start is work you shouldn't be doing.
Column names are never consistent
One payer calls it "Your invoice", another calls it "Your ref". A third exports "invoice_number". Manually interpreting and reformatting these before you can begin entry wastes time on every single remittance.
CSVs arrive with extra clutter
Summary rows, sub-totals, blank lines, and repeated headers all end up in remittance exports. Cleaning the file before you can use it is an invisible step that adds minutes every time.
Errors hide in rows
A short payment or a missing row in a 200-line CSV looks identical to a correct entry. Without a structured review step, discrepancies go unnoticed until reconciliation falls apart weeks later.
How it works
How CSV remittances are processed
Remittance Go reads the CSV structure, identifies the columns containing invoice references and payment amounts, matches each row against your open Xero invoices, and presents everything for review before the batch payment is created.
Step 1 — Upload the CSV
Drag in the CSV file from your downloads folder, email attachment, or client portal. Remittance Go reads it immediately and queues it for processing.
Step 2 — Columns are auto-detected
Remittance Go identifies the invoice number, amount, payment reference, and date columns automatically — even if the payer named them something unusual.
Step 3 — Review matched invoices
Every CSV row is matched against your open Xero invoices. Errors, unmatched references, and short payments are flagged clearly before anything is posted.
Step 4 — Batch payment in Xero
Confirm the results and Remittance Go creates the batch payment via the official Xero API. It appears in Xero immediately, correctly dated and ready to reconcile against your bank feed.
About CSV remittance processing
Handle CSV remittances from any payer, in any format
Upload it. We read it. Xero gets the batch payment.
Column detection that works across every payer
Different payers export their remittance data with entirely different column structures. Health funds, government agencies, and corporate clients all have their own naming conventions.
Remittance Go analyses the CSV and maps the right columns automatically — invoice references, amounts, payment dates — regardless of what the payer called them. No templates, no setup. It also works seamlessly alongside PDF remittance processing, so mixed-format workflows are handled in the same queue.
Review every line before anything hits Xero
Before the batch payment is created, Remittance Go shows you every matched invoice row — amount, reference, and the corresponding Xero invoice — so you can catch discrepancies before they become a reconciliation problem.
Short payments, unmatched references, and duplicate lines are flagged automatically. Confirm when you're satisfied, and Remittance Go posts the batch payment to Xero via the official API — correctly named, correctly dated, ready to reconcile against your bank feed.
One workflow for every remittance format
Whether a client sends a CSV, a PDF, or an email with remittance data pasted into the body, Remittance Go processes them all in the same interface — extract, match, review, post.
CSV files that arrive as email attachments can be handled automatically via the email remittance queue, which captures attachments as they arrive. You never touch the file — it just appears in your queue, ready to process.
“We get CSV remittances from three different health funds every week. Each one uses completely different column headers. Remittance Go reads all of them without any fuss — we just upload and review.”
CSV remittances in the accounts receivable workflow
CSV remittances are typically exported directly from the payment systems of large institutional payers — health funds, government departments, NDIS plan managers, and enterprise clients. Because they're already structured data (unlike scanned documents), Remittance Go can parse them faster than PDF remittances, which require text and layout extraction first.
Once imported, every CSV remittance follows the same review workflow as any other format in Remittance Go. Payment errors and discrepancies are surfaced before the batch is posted, so your accounts receivable team is reviewing clean, matched data — not a 200-row spreadsheet.
If your clients also send remittances via email body or as plain text, text remittance processing handles those in the same interface.
CSV remittance questions
Do I need to set up a column mapping template before uploading?
No. There is no configuration required. Upload the CSV and Remittance Go handles column detection automatically. If there is genuine ambiguity in the file structure, the review screen lets you confirm the mapping before anything is posted to Xero.
What if the CSV has extra columns, summary rows, or unusual formatting?
Extra columns are simply ignored. Summary rows, sub-totals, and blank rows are filtered out automatically. Remittance Go focuses on extracting the columns it needs — invoice references, amounts, and payment dates — and leaves everything else alone.
What happens if a CSV row doesn't match an invoice in Xero?
Unmatched rows are flagged clearly on the review screen before the batch is created. You can see exactly which lines didn't match and investigate before confirming. See also how Remittance Go handles remittance errors and discrepancies more broadly.
Can I upload multiple CSV files at once?
Yes. You can queue multiple CSV files and work through them in a single session. Each file is treated as a separate remittance and matched independently against your Xero invoices.
Is CSV processing different from PDF processing?
Not really. CSVs have native text, which we process directly. A PDF is more like an image — the text is less accessible, so we use various OCR techniques to extract it. But once both are in text format, they are largely the same.
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