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COLGATE-PALMOLIVE COMPANY: financing cash flow

Financing cash flow for COLGATE-PALMOLIVE COMPANY. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All COLGATE-PALMOLIVE COMPANY financial histories

What this measure means

Net cash from financing activities, including borrowing, repayments and transactions with owners. A positive amount does not establish operating profitability.

Exact concept: us-gaap:NetCashProvidedByUsedInFinancingActivities. Each value covers an annual-duration reporting interval, shown with both start and end dates. Different units remain separate; no currency conversion or interpolation is applied.

Coverage of this history

Selected reporting periods run from 2007-01-01 to 2025-12-31. The SEC response was captured on 2026-09-19.

Selected filing history

Financing cash flow in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2025-01-012025-12-31-3,256,000,000USD2026-02-2310-K · 0000021665-26-000006
2024-01-012024-12-31-3,389,000,000USD2026-02-2310-K · 0000021665-26-000006
2023-01-012023-12-31-2,793,000,000USD2026-02-2310-K · 0000021665-26-000006
2022-01-012022-12-31-952,000,000USD2025-02-1310-K · 0000021665-25-000008
2021-01-012021-12-31-2,774,000,000USD2024-02-1510-K · 0000021665-24-000003
2020-01-012020-12-31-2,919,000,000USD2023-02-1610-K · 0000021665-23-000007
2019-01-012019-12-31-870,000,000USD2022-02-1710-K · 0000021665-22-000003
2018-01-012018-12-31-2,679,000,000USD2021-02-1810-K · 0000021665-21-000007
2017-01-012017-12-31-2,450,000,000USD2020-02-2110-K · 0000021665-20-000004
2016-01-012016-12-31-2,233,000,000USD2019-02-2110-K · 0000021665-19-000003
2015-01-012015-12-31-2,276,000,000USD2018-02-2110-K/A · 0000021665-18-000006
2014-01-012014-12-31-2,170,000,000USD2017-02-2310-K · 0000021665-17-000002
2013-01-012013-12-31-2,142,000,000USD2016-02-1810-K · 0001628280-16-011343
2012-01-012012-12-31-2,301,000,000USD2015-02-1910-K · 0001628280-15-000846
2011-01-012011-12-31-1,242,000,000USD2014-02-2010-K · 0001545547-14-000003
2010-01-012010-12-31-2,624,000,000USD2013-02-2110-K · 0001445305-13-000275
2009-01-012009-12-31-2,270,000,000USD2012-02-2310-K · 0001445305-12-000409
2008-01-012008-12-31-1,530,000,000USD2011-02-2410-K · 0001140361-11-011883
2007-01-012007-12-31-1,803,000,000USD2010-02-2510-K · 0001140361-10-008522

Related financial histories

Inspect the source

Entity
COLGATE-PALMOLIVE COMPANY / CIK 0000021665
Captured
2026-09-19T14:45:12.279Z
SEC response SHA-256
450c2668961565047c7745ff5df5d38b40cc57d6940c48fe8f32dca13100f96d

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/0000021665.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"])))