Skip to content

Bank of New York Mellon Corp: capital expenditure payments

Capital expenditure payments for Bank of New York Mellon Corp. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All Bank of New York Mellon Corp financial histories

What this measure means

Cash payments to acquire property, plant and equipment. This taxonomy concept does not capture every form of investment or acquisition.

Exact concept: us-gaap:PaymentsToAcquirePropertyPlantAndEquipment. 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 2026-09-20.

Selected filing history

Capital expenditure payments in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2025-01-012025-12-311,553,000,000USD2026-02-2510-K · 0001390777-26-000033
2024-01-012024-12-311,469,000,000USD2026-02-2510-K · 0001390777-26-000033
2023-01-012023-12-311,220,000,000USD2026-02-2510-K · 0001390777-26-000033
2022-01-012022-12-311,346,000,000USD2025-02-2710-K · 0001390777-25-000046
2021-01-012021-12-311,215,000,000USD2024-02-2810-K · 0001390777-24-000051
2020-01-012020-12-311,222,000,000USD2023-02-2710-K · 0001390777-23-000033
2019-01-012019-12-311,210,000,000USD2022-02-2510-K · 0001390777-22-000043
2018-01-012018-12-311,108,000,000USD2021-02-2510-K · 0001390777-21-000037
2017-01-012017-12-311,197,000,000USD2020-02-2710-K · 0001390777-20-000044
2016-01-012016-12-31825,000,000USD2019-02-2710-K · 0001390777-19-000050
2015-01-012015-12-31601,000,000USD2018-02-2810-K · 0001390777-18-000069
2014-01-012014-12-31791,000,000USD2017-02-2810-K · 0001390777-17-000065
2013-01-012013-12-31609,000,000USD2016-02-2610-K · 0001390777-16-000204
2012-01-012012-12-31652,000,000USD2015-02-2710-K · 0001628280-15-001194
2011-01-012011-12-31642,000,000USD2014-02-2810-K · 0001445305-14-000745
2010-01-012010-12-31230,000,000USD2013-02-2810-K · 0001193125-13-084562
2009-01-012009-12-31318,000,000USD2012-02-2810-K · 0001193125-12-085349
2008-01-012008-12-31303,000,000USD2011-02-2810-K · 0001193125-11-049932
2007-01-012007-12-31313,000,000USD2010-02-2610-K · 0001193125-10-042948

Related financial histories

Inspect the source

Entity
Bank of New York Mellon Corp / CIK 0001390777
Captured
2026-09-20T07:59:22.632Z
SEC response SHA-256
5e1d416fbbc5df89085c4e9d2f32ee91dfae321cb8f3a29a107699e974d926cd

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/0001390777.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"])))