Skip to content

The Procter & Gamble Company: net current accounts receivable

Net current accounts receivable for The Procter & Gamble Company. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All The Procter & Gamble Company financial histories

What this measure means

Current customer receivables after the allowance for credit loss. The balance is not cash collected or a guarantee of collection.

Exact concept: us-gaap:AccountsReceivableNetCurrent. Each value is a balance at the reporting date, not a flow earned over a year. Different units remain separate; no currency conversion or interpolation is applied.

Coverage of this history

Selected reporting periods run from 2009-06-30 to 2026-06-30. The SEC response was captured on 2026-09-19.

Selected filing history

Net current accounts receivable in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
At date2026-06-306,056,000,000USD2026-08-0410-K · 0000080424-26-000103
At date2025-06-306,185,000,000USD2026-08-0410-K · 0000080424-26-000103
At date2024-06-306,118,000,000USD2025-08-0410-K · 0000080424-25-000076
At date2023-06-305,471,000,000USD2024-08-0510-K · 0000080424-24-000083
At date2022-06-305,143,000,000USD2023-08-0410-K · 0000080424-23-000073
At date2021-06-304,725,000,000USD2022-08-0510-K · 0000080424-22-000064
At date2020-06-304,178,000,000USD2021-08-0610-K · 0000080424-21-000100
At date2019-06-304,951,000,000USD2020-08-0710-K/A · 0000080424-20-000059
At date2018-06-304,686,000,000USD2019-08-0610-K · 0000080424-19-000050
At date2017-06-304,594,000,000USD2018-08-0710-K · 0000080424-18-000055
At date2016-06-304,373,000,000USD2017-08-0710-K · 0000080424-17-000047
At date2015-06-304,568,000,000USD2016-08-0910-K · 0000080424-16-000212
At date2014-06-306,386,000,000USD2015-08-0710-K · 0000080424-15-000070
At date2013-06-306,508,000,000USD2014-08-0810-K · 0000080424-14-000057
At date2012-06-306,068,000,000USD2013-08-0810-K · 0000080424-13-000063
At date2011-06-306,275,000,000USD2012-08-0810-K · 0000080424-12-000063
At date2010-06-305,335,000,000USD2011-08-1010-K · 0000080424-11-000014
At date2009-06-305,836,000,000USD2010-08-1310-K · 0001193125-10-188769

Related financial histories

Inspect the source

Entity
The Procter & Gamble Company / CIK 0000080424
Captured
2026-09-19T14:51:29.563Z
SEC response SHA-256
606ad7056b611e91cfab9f7568b747404405772add188600efa5ccda5824f3d8

Current SEC company facts · Download the original response snapshot (gzip) · Download the selected JSON

Latest-filed annual-report facts per unit and reporting period at capture time. Duration facts cover 300 to 400 days. This selection can include restatements and is not a point-in-time backtest dataset. Missing concepts are omitted, never zero-filled. Values retain original units and are not currency converted. Extended concepts require compatible unit shapes and at least three reporting ends with changing values within one unit. Constant or incompatible added histories are omitted.

Public company accounting reference, not market prices, returns, an investment recommendation, or ALPHAC performance. Validate a separately constructed return series with the validation API; accounting values are not returns.

Use this in research

A financial period ends before its results become public. Use the filing date as a minimum availability boundary, inspect amendments, and retain the original filing vintage when testing historical signals. This latest-filed selection can contain information unavailable at the time.

These pages do not supply prices, total-return histories, corporate-action adjustments or a tradable universe. Build those inputs separately before evaluating a strategy. A profitable backtest can still reflect selection bias or costs that were left out.

Research methodology · Execution and cost assumptions · Check backtest overfitting

Build with the open-source tools

Use these accounting records as inspectable inputs. When you have constructed a return series, the validation tools can help test its statistical evidence and preserve the result with its limitations.

Read the published dataset with Python
import json
from urllib.request import urlopen

with urlopen("https://canlicapital.com/company-data/0000080424.json") as response:
    record = json.load(response)
print(record["fetched_at"])
print(record["policy"])
for concept in record["concepts"]:
    print(concept["tag"], next(iter(concept["observations"])))