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Regions Financial Corporation: goodwill carrying amount

Goodwill carrying amount for Regions Financial Corporation. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All Regions Financial Corporation financial histories

What this measure means

Recognized goodwill remaining after accumulated impairment. It arises from business combinations and does not measure the current value of the company’s brand.

Exact concept: us-gaap:Goodwill. 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 2008-12-31 to 2025-12-31. The SEC response was captured on 2026-09-20.

Selected filing history

Goodwill carrying amount in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
At date2025-12-315,733,000,000USD2026-02-2410-K · 0001281761-26-000019
At date2024-12-315,733,000,000USD2026-02-2410-K · 0001281761-26-000019
At date2023-12-315,733,000,000USD2025-02-2110-K · 0001281761-25-000010
At date2022-12-315,733,000,000USD2024-02-2310-K · 0001281761-24-000010
At date2021-12-315,744,000,000USD2023-02-2410-K · 0001281761-23-000012
At date2020-12-315,190,000,000USD2022-02-2410-K · 0001281761-22-000016
At date2019-12-314,845,000,000USD2021-02-2410-K · 0001281761-21-000012
At date2018-12-314,829,000,000USD2020-02-2110-K · 0001281761-20-000010
At date2017-12-314,904,000,000USD2019-02-2210-K · 0001281761-19-000019
At date2016-12-314,904,000,000USD2018-02-2610-K · 0001281761-18-000016
At date2015-12-314,878,000,000USD2017-02-2410-K · 0001281761-17-000026
At date2014-12-314,816,000,000USD2016-02-1610-K · 0001281761-16-000108
At date2013-12-314,816,000,000USD2015-02-1710-K · 0001281761-15-000022
At date2012-12-314,816,000,000USD2014-02-2110-K · 0001281761-14-000009
At date2011-12-314,816,000,000USD2013-02-2110-K · 0001193125-13-069212
At date2010-12-315,561,000,000USD2013-02-2110-K · 0001193125-13-069212
At date2009-12-315,557,000,000USD2012-02-2410-K · 0001193125-12-078199
At date2008-12-315,548,000,000USD2011-03-1810-K/A · 0001193125-11-070898

Related financial histories

Inspect the source

Entity
Regions Financial Corporation / CIK 0001281761
Captured
2026-09-20T07:48:43.715Z
SEC response SHA-256
b6dec3ef9f5ee90723b8efb243bd6e2bd9e71a6401bb93944a5411b7c5ebd729

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/0001281761.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"])))