AI use case · Is your data ready for 13-week cash flow forecasting?A cash forecast is a reconciliation with dates on it.
AI cash tools promise a live 13-week view instead of a weekly spreadsheet scramble. They read receivables, payables, the bank and payroll, and predict timing. If payment terms live in a spreadsheet and receipts aren’t allocated to invoices, the model forecasts the wrong weeks with total confidence.
Starts with a 30-minute call. Commits you to nothing.
What it needs
What 13-week cash flow forecasting needs from your data.
Each requirement, the systems it lives in, and what we check. The AI is the easy part; this list is the hard part. Each check feeds the Truth Score™, a score out of 100 for how far your data can be trusted.
Truth Score pillars that gate it mostConnectivityAccuracyThe six pillars
Where it breaks
Every system looks fine. The gaps between them don’t.
Where 13-week cash flow forecasting breaks: not inside one system, but where two of them disagree about the same customer, deal or invoice.
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Spreadsheets ↔ Finance
Payment terms held in a spreadsheet, not on the invoice
What it does to the AIThe forecast uses default terms and gets the timing wrong.
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Bank ↔ Finance
Receipts not allocated to the invoices they paid
What it does to the AICustomers look late when they have paid, and cash looks tighter than it is.
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Payroll ↔ Finance
Payroll posted as one journal, with no entity or cost centre
What it does to the AIFixed outflows can’t be split by entity or by week.
Gaps to test for this use case, not client findings.
Before you sign
Questions to ask the vendor selling it.
Four questions that separate a demo from a deployment. Bring the answers, or the proposal, to the Truth Score Read and we test them against your records.
- Q1
Do you forecast from due dates, or from how each customer actually pays?
Due dates are a promise. Payment history is the behaviour. Only the second makes a forecast better than your spreadsheet.
- Q2
What do you do with unallocated receipts?
If they are ignored, the forecast double-counts cash you already have.
- Q3
How do you handle several entities, banks and currencies?
Group cash is where mid-market forecasts usually go wrong. Ask to see it on a multi-entity example.
- Q4
Who signs off the opening cash position?
Every forecast starts from a number. If nobody owns it, nobody owns the forecast.
How a Truth Score Read tests it
13-week cash flow forecasting, tested against your own records.
Our engine matches the customers, people, deals and invoices across the exports from the systems behind the decision. Every red flag is checked by hand against sample records before sign-off, and the verdict comes in writing. Here is what that means for this use case.
- 01
Rebuild the receivables timeline
Invoices, receipts and terms from the ledger export, with each customer’s real payment behaviour calculated.
- 02
Check the outflows
Supplier bills, payment runs and payroll journals compared with the payroll export.
- 03
Find the off-system inputs
Terms, deals or adjustments held in spreadsheets that the forecast would need but no system holds.
- 04
Give the verdict
Whether an AI cash forecast can run now, after fixes, or not yet, and what to fix first.
Two systems are enough to start. We send the exact field list after the call.
How the Truth Score Read worksWhat you get back
See what comes back: a real sample memo.
One fictional B2B software company, Example Co: 72,837 records in 7 exports from its CRM, finance and HR systems, run through the same engine and the same checks as a paid Truth Score Read. Each system passes its own checks. Matched across systems, only 13% of deals tie to an invoice.
Questions
13-week cash flow forecasting, answered plainly.
Anything else, ask on the 30-minute call. It commits you to nothing.
Book the callWhat data does an AI cash flow forecast need?
Receivables and payables with real due dates and terms, bank transactions reconciled to the ledger, receipts allocated to the invoices they paid, and payroll and other fixed outflows. Above all, the inputs need to be in systems, not in side spreadsheets.
Why does reconciliation matter so much for a cash forecast?
Because a cash forecast is a prediction of when ledger items turn into bank movements. If the bank and the ledger don’t agree today, the model is predicting from the wrong starting point.
Can we automate cash forecasting if our systems aren’t integrated?
Integration is less important than agreement. Separate systems are fine if their records match on customer, supplier and invoice. We check that from exports, without touching your systems.
We have several entities. Does that change anything?
It adds intercompany flows, currencies and duplicated customers and suppliers across entities. Each is checkable, and each is a common reason group cash forecasts disappoint.
Is your data ready for 13-week cash flow forecasting? Find out before you sign.
Exports from two or more systems in. A signed verdict on this use case within 5 working days of complete exports. Starts with a 30-minute call. Commits you to nothing.
Starts with a 30-minute call. Commits you to nothing.