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CATERPILLAR FINANCIAL SERVICES CORP: depreciation, depletion and amortization

Depreciation, depletion and amortization for CATERPILLAR FINANCIAL SERVICES CORP. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All CATERPILLAR FINANCIAL SERVICES CORP financial histories

What this measure means

Combined depreciation, depletion and amortization for the period. A noncash allocation of asset cost, not a measure of maintenance spending.

Exact concept: us-gaap:DepreciationDepletionAndAmortization. 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 2009-01-01 to 2025-12-31. The SEC response was captured on 2026-09-21.

Selected filing history

Depreciation, depletion and amortization in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2025-01-012025-12-31717,000,000USD2026-02-1310-K · 0000764764-26-000007
2024-01-012024-12-31738,000,000USD2026-02-1310-K · 0000764764-26-000007
2023-01-012023-12-31728,000,000USD2026-02-1310-K · 0000764764-26-000007
2022-01-012022-12-31732,000,000USD2025-02-1410-K · 0000764764-25-000006
2021-01-012021-12-31770,000,000USD2024-02-1610-K · 0000764764-24-000011
2020-01-012020-12-31772,000,000USD2023-02-1510-K · 0000764764-23-000016
2019-01-012019-12-31827,000,000USD2022-02-1610-K · 0000764764-22-000029
2018-01-012018-12-31832,000,000USD2021-02-1710-K · 0000764764-21-000015
2017-01-012017-12-31820,000,000USD2020-02-1910-K · 0000764764-20-000032
2016-01-012016-12-31851,000,000USD2019-02-1410-K · 0000764764-19-000013
2015-01-012015-12-31848,000,000USD2018-02-1510-K · 0000764764-18-000016
2014-01-012014-12-31883,000,000USD2017-02-1510-K · 0000764764-17-000015
2013-01-012013-12-31790,000,000USD2016-02-1610-K · 0000764764-16-000111
2012-01-012012-12-31707,000,000USD2015-02-1710-K · 0000764764-15-000006
2011-01-012011-12-31710,000,000USD2014-11-1410-K/A · 0000764764-14-000125
2010-01-012010-12-31715,000,000USD2013-02-1910-K · 0000764764-13-000005
2009-01-012009-12-31742,000,000USD2012-02-2110-K · 0000764764-12-000017

Related financial histories

Inspect the source

Entity
CATERPILLAR FINANCIAL SERVICES CORP / CIK 0000764764
Captured
2026-09-21T17:16:30.647Z
SEC response SHA-256
d39234d30bccf3c17abd04ccd063679a968cbf61fa0af0e22f2e082b49cc9598

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/0000764764.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"])))