---
title: "Accounts Receivable Aging Report: How to Read It and Act on It"
description: Four in ten B2B invoices are overdue. Learn which aging buckets predict write-offs, how you compare, and the daily workflow that keeps AR clean.
image: https://images.unsplash.com/photo-1753955900083-b62ee8d97805?w=1200&q=80
---
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# Accounts Receivable Aging Report: How to Read It and Act on It
11 de September, 2026
*Last updated: September 10, 2026*
An accounts receivable aging report is the one document every finance leader opens and most collections teams ignore. It tells you exactly which invoices are unpaid, how long they have been unpaid, and which customers are quietly turning into bad debt. The problem is not producing the report. Any ERP does that. The problem is that most companies read it once a month, nod, and go back to chasing whoever shouted loudest.
This guide explains how to read an AR aging report properly, which numbers deserve attention, what "healthy" looks like against real benchmarks, and how to turn the report from a monthly snapshot into a daily collections engine.
**In this article**
- [What an accounts receivable aging report actually shows](https://blog.getdarwin.ai/en/accounts-receivable-aging-report-how-to-read-act#what-is)
- [How to read the aging buckets (and what they hide)](https://blog.getdarwin.ai/en/accounts-receivable-aging-report-how-to-read-act#how-to-read)
- [What a healthy aging report looks like](https://blog.getdarwin.ai/en/accounts-receivable-aging-report-how-to-read-act#benchmarks)
- [How to act on the report, bucket by bucket](https://blog.getdarwin.ai/en/accounts-receivable-aging-report-how-to-read-act#act)
- [Turning the report into a daily collections workflow](https://blog.getdarwin.ai/en/accounts-receivable-aging-report-how-to-read-act#automate)
- [FAQ](https://blog.getdarwin.ai/en/accounts-receivable-aging-report-how-to-read-act#faq)
## What an accounts receivable aging report actually shows
An AR aging report groups every open invoice by how many days it has been outstanding, usually in 30-day buckets: current (not yet due), 1–30 days past due, 31–60, 61–90, and 91+ days. Each row is a customer; each column is a bucket; each cell is the total dollar value of that customer's invoices sitting in that bucket.
That structure makes it a risk map, not just a list. The further right an invoice moves, the less likely it is to ever be paid. Industry research aggregated by [Chaser](https://www.chaserhq.com/blog/accounts-receivable-stats) puts the collection probability of a debt that is more than 90 days late at roughly 70%, and it keeps falling from there. Every column to the right is money being converted from revenue into write-off.
### The two numbers that matter more than the total
Most people look at the grand total of past-due receivables. That number is almost useless on its own because it mixes a large, reliable customer paying five days late with a small account that has gone silent for four months. Two better lenses:
- **Percent of AR by bucket.** What share of total receivables sits in each column? This is what you benchmark.
- **Concentration.** How much of the 61+ balance belongs to your top three delinquent accounts? If the answer is "most of it," you have three conversations to have, not a process problem.
## How to read the aging buckets (and what they hide)
Each bucket tells a different story and calls for a different response. Reading them as one undifferentiated "overdue" number is how collections teams end up sending the same polite reminder to everyone.
### Current and 1–30 days
This is your early-warning zone. Invoices here are late, but usually for mechanical reasons: a missing PO number, an invoice that went to the wrong inbox, a customer whose payment run happens on the 25th. According to Chaser's survey of finance professionals, [25.3% of businesses typically receive payment 15 to 30 days after the due date](https://www.chaserhq.com/blog/accounts-receivable-stats), which means a large share of your customers live permanently in this bucket. That is annoying, but it is not a credit problem.
### 31–60 days
The story changes here. A customer who is two months late has either a dispute you have not heard about, a cash-flow issue, or a process that has quietly deprioritized you. This bucket is where a phone call replaces an email. It is also where you start to see the difference between customers who are slow and customers who are in trouble.
### 61–90 days
Invoices in this bucket are at real risk. Your leverage is declining, and the customer has ignored several touchpoints. The right move is usually a payment plan conversation, a credit hold on new orders, or both. Getting a firm [promise to pay that actually converts into payment](https://blog.getdarwin.ai/en/promise-to-pay-improve-ptp-kept-rate?hsLang=en) is the goal, not another reminder.
### 91+ days
This is the write-off watch list. The [Dun & Bradstreet Q1 2026 U.S. Accounts Receivable Industry Report](https://www.dnb.com/en-us/reports/accounts-receivable-aging-report.html) found that 16 of 203 industry segments had 10% or more of their aging dollars sitting at 91+ days past due. If your 91+ bucket is growing quarter over quarter, your credit policy, your dispute process, or your follow-up cadence is broken upstream.
## What a healthy aging report looks like
There is no universal target, because payment terms and customer mix vary enormously by industry. But there are reference points you can hold your report against.
| Signal | Healthy | Warning |
| --- | --- | --- |
| Share of AR that is current | Majority of dollars current | Past-due dollars approaching half of AR |
| 91+ bucket as % of AR | Low single digits | 10%+ (D&B flags this as severely delinquent) |
| Bad debt write-off rate | Under 3% of revenue | 3%+ of revenue |
| Trend of 61+ dollars | Flat or shrinking | Growing three months in a row |
For context on where the market sits: the [2025 Atradius Payment Practices Barometer for North America](https://group.atradius.com/knowledge-and-research/reports/b2b-payment-practices-trends-in-north-america-2025) found that 43% of credit-based B2B sales in the US were overdue, with bad debts affecting about 5% of long-overdue invoices. In Mexico the overdue share was 41% and in Canada 44%. So if roughly four in ten of your receivable dollars are past due, you are average. Average is expensive, and it shows up directly in your [DSO](https://blog.getdarwin.ai/en/how-to-reduce-dso-b2b-playbook?hsLang=en).
On write-offs, [Chaser's data](https://www.chaserhq.com/blog/accounts-receivable-stats) shows 38% of businesses writing off between 3% and more than 14% of annual revenue as bad debt, while 91.7% of IT and software companies keep it under 5%. The gap between sectors is mostly explained by process discipline, not customer quality.
**Key takeaway:** Benchmark your aging report on *percentages and trends*, not absolute dollars. A growing 61+ bucket is a leading indicator of next quarter's write-offs. That is the number to put in front of leadership, not total past due.
## How to act on the report, bucket by bucket
The value of an aging report is entirely in what happens after you read it. Here is a practical playbook that maps each bucket to an action, an owner, and a channel.
### Segment before you chase
Sort your past-due accounts on two axes: balance size and days late. Large-and-late gets a human call today. Small-and-slightly-late gets an automated reminder. Large-and-slightly-late gets a friendly personal nudge, because those customers are worth protecting. Small-and-very-late gets a final notice and a decision about whether to escalate or write off. Doing this once a week takes twenty minutes and beats working the list top to bottom.
### Match the channel to the bucket
Email is still the default collections channel, used by [91% of finance teams surveyed by Chaser](https://www.chaserhq.com/blog/accounts-receivable-stats), but the same research found that adding a phone touchpoint after an unanswered email resolves invoices 73% of the time versus 49% for email alone. WhatsApp and SMS are growing fast in LatAm and Southern Europe precisely because they get read. The rule of thumb: the further right the invoice, the more direct the channel.
### Chase every invoice, every time
The single highest-return change most teams can make is consistency. Chaser found that [31% of businesses leave some invoices unchased every month](https://www.chaserhq.com/blog/accounts-receivable-stats), and that companies following up on 100% of overdue invoices were 76% more likely to be paid within a week. Unchased invoices are the ones that drift silently from the 31–60 bucket into 91+.
### Fix the disputes hiding in the middle buckets
Pull every invoice in 31–90 with a partial payment or a customer note attached. Those are disputes, not delinquencies, and no reminder cadence will collect them. Route them to whoever can resolve the pricing, delivery, or quality issue, and track them separately so they stop polluting your collections metrics. Clean [cash application](https://blog.getdarwin.ai/en/cash-application-automation-unapplied-cash?hsLang=en) matters here too: unapplied cash makes customers look later than they are.
## Turning the report into a daily collections workflow
The monthly aging report is a lagging indicator. By the time a customer shows up in the 61–90 column, you have already lost sixty days of leverage. The teams that consistently keep their aging clean have stopped treating the report as a document and started treating it as a trigger.
In practice that means three things. First, the aging data refreshes daily and each bucket transition fires an action automatically: an invoice crossing day 1 gets a friendly reminder, day 15 gets a firmer one, day 31 gets queued for a call. Second, outreach is conversational and two-way, so when a customer replies "we never got the invoice" or "can we split this into two payments," the response happens in minutes, not at the next weekly review. Third, every interaction is logged against the invoice so the human who eventually picks up the phone knows the full history.
This is exactly the kind of high-volume, rules-plus-judgment work that AI collections agents are built for. [Darwin AI's collections worker, Rio](https://www.getdarwin.ai/en/worker/rio), reads the aging data, runs the reminder cadence across WhatsApp, email, and SMS, negotiates payment dates within the rules you set, and escalates only the accounts that need a human. The finance team stops working the list and starts working the exceptions.
The measurable result is a report that looks different month over month: fewer dollars drifting into 61+, a higher share of [invoices paid on the first or second reminder](https://blog.getdarwin.ai/en/automated-payment-reminders-invoices-paid?hsLang=en), and a [Collection Effectiveness Index](https://blog.getdarwin.ai/en/collection-effectiveness-index-cei-formula-benchmarks?hsLang=en) that climbs without adding headcount. Chaser's respondents who used AR automation were [52% more likely to be paid within two weeks](https://www.chaserhq.com/blog/accounts-receivable-stats) than those relying on manual processes.
## FAQ
### What is an accounts receivable aging report?
It is a report that lists all unpaid customer invoices grouped by how long they have been outstanding, typically in buckets of current, 1–30, 31–60, 61–90, and 91+ days past due. It is used to prioritize collections, estimate bad debt, and assess customer credit risk.
### How often should you review an AR aging report?
Finance leadership typically reviews it monthly for reporting and bad-debt provisioning, but collections teams should work from a version that refreshes daily or at least weekly. Waiting a month between reviews lets invoices slide a full bucket before anyone acts.
### What percentage of receivables should be past due?
The lower the better, but for context, the [2025 Atradius barometer](https://group.atradius.com/knowledge-and-research/reports/b2b-payment-practices-trends-in-north-america-2025) found 43% of US credit-based B2B sales were overdue. A company where the large majority of AR dollars are current, and 91+ dollars are in the low single digits as a share of AR, is performing well above the market.
### Can AI automate accounts receivable aging follow-up?
Yes. AI collections agents can read aging data daily, send personalized reminders as invoices move between buckets, hold two-way conversations with customers about payment dates, and escalate exceptions to humans. Chaser's research found teams using AR automation were [52% more likely to be paid within two weeks](https://www.chaserhq.com/blog/accounts-receivable-stats).
Stop working the aging report by hand. Let an AI collections agent chase every invoice, every day, and hand your team only the exceptions.
[Meet Rio, Darwin AI's collections worker](https://www.getdarwin.ai/en/worker/rio)
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