Promise to Pay

Why Promise to Pay matters

Every collections conversation should end with a commitment: the customer either pays immediately, agrees to a specific future date, raises a dispute, or refuses to engage. The first two outcomes lead to cash; the latter two require different workflows. Promise to Pay is the operational record of the second outcome, a customer commitment to pay by a specific date. Captured systematically, PTPs let collections teams predict cash inflows by customer, prioritise follow-up effort, and detect bad debt risk early when promises break.

How Promise to Pay is captured

PTPs are captured in three common ways.

• Collections call notes: the most traditional method. Collector logs the promise in the AR system with date, amount, and any conditions.
• Email exchange: customer responds to dunning email with a date commitment. Captured manually or by AI extraction.
• Customer portal: customer self-services a promise via supplier portal with structured fields.

Best-practice capture includes four elements: specific date (not "next week"), specific amount (full invoice or partial), any conditions (e.g., "if we receive the credit memo first"), and confidence level if assessed by the collector.

What good PTP management looks like

Effective PTP workflows track four metrics.

• PTP capture rate: percentage of overdue invoice contacts that result in a captured promise (versus dispute, refusal, or no contact). Best-in-class is 50 to 70 percent.
• PTP keep rate: percentage of promises actually honoured by the committed date. Best-in-class is 75 to 90 percent.
• Time-to-cash from PTP: median days from promise to actual payment, ideally within 7 days of the committed date.
• Broken PTP recovery rate: percentage of broken promises that convert to cash through follow-up versus aging into bad debt.

These metrics together describe how effectively the collections team converts customer engagement to cash.

Common Promise to Pay mistakes

Mistake 1: Vague capture. A note saying "customer will pay soon" is operationally useless. Without a specific date, the follow-up date can't be scheduled and the cash forecast can't reflect the commitment.

Mistake 2: No follow-up workflow. Promises captured but not followed up have keep rates 20 to 30 percentage points lower than promises with scheduled follow-up. Capturing without the follow-up cadence wastes the commitment.

Mistake 3: Treating broken PTPs the same as never-contacted invoices. A customer who broke their promise carries different risk signals than a customer who hasn't been contacted. Broken PTPs warrant accelerated escalation, not the same standard sequence.

Mistake 4: Not feeding PTPs into the cash forecast. A 50,000 euro promise from a high-keep-rate customer is much more reliable cash than the same invoice without a promise. Treasury cash forecasts that ignore PTPs miss material accuracy improvements.

How AI improves Promise to Pay management

AI-native collections platforms automate PTP capture, follow-up, and forecasting:

• Automatic capture from email and call transcripts: AI extracts the date, amount, and conditions from customer responses without requiring manual logging by the collector.
• Smart follow-up scheduling: promises are automatically scheduled for follow-up 1 day before the committed date, with escalation paths for broken promises.
• Forecast integration: captured PTPs feed real-time cash forecasts, weighted by the customer's historical keep rate.
• Risk scoring: customers with chronically broken promises get flagged for credit review before bad debt accumulates.

Mid-market collections teams typically lift PTP capture rates by 15 to 25 percent and keep rates by 10 to 15 percentage points within 90 days of agentic deployment, contributing directly to DSO reduction and bad debt prevention.

Frequently asked questions

What is a Promise to Pay?

A Promise to Pay (PTP) is a commitment from a customer to pay an overdue invoice by a specific future date. It is captured by collections teams during dunning outreach and used to schedule follow-up, prioritise collection effort, and feed cash flow forecasts.

What is a good PTP keep rate?

Best-in-class PTP keep rates run 75 to 90 percent. Mid-market average is 60 to 80 percent. Teams that actively follow up on promises (typically a day before the committed date) achieve higher keep rates than teams that capture promises but don't reinforce them.

How should I follow up on a broken PTP?

Broken PTPs warrant accelerated escalation, not the standard dunning sequence. Best-practice is to contact within 24 hours of the broken commitment with a firm tone, request immediate payment or a new specific date, and escalate to credit hold or supervisor review after a second broken promise.

Should PTPs feed into cash flow forecasting?

Yes. Captured PTPs are significantly more reliable cash signal than open invoices without commitments. Weight each PTP by the customer's historical keep rate (e.g., a 50,000 euro PTP from a customer with 85 percent historical keep rate counts as 42,500 euros in the forecast). Treasury cash forecasts that include weighted PTPs typically improve week-2 to week-4 forecast accuracy by 5 to 10 percentage points.

Can AI automatically capture Promises to Pay?

Yes. AI extracts PTP date, amount, and conditions from customer email replies and call transcripts without requiring manual logging by collectors. The extracted PTPs are written to the collections system and trigger automatic follow-up workflows. Best-in-class platforms also feed PTPs into cash forecasting in real time.

What's the difference between PTP and payment commitment?

They are synonymous in collections context. Some companies use 'commitment' or 'pledge' rather than 'promise', but the workflow is identical: a customer-specified future date and amount that the collections team treats as scheduled cash and follows up to confirm.