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Bank of South Carolina Corporation: financing cash flow

Financing cash flow for Bank of South Carolina Corporation. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All Bank of South Carolina Corporation 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 2009-01-01 to 2022-12-31. The SEC response was captured on 2026-09-23.

This selected history ends more than two years before capture. Do not treat its final value as a current balance or current annual result. More recent filings may use another accounting tag; inspect the filings before drawing conclusions about the company.

Selected filing history

Financing cash flow in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2022-01-012022-12-31-14,132,983USD2023-03-0210-K · 0001839882-23-005612
2021-01-012021-12-31142,889,696USD2023-03-0210-K · 0001839882-23-005612
2020-01-012020-12-3179,131,311USD2023-03-0210-K · 0001839882-23-005612
2019-01-012019-12-31-7,079,604USD2022-03-0410-K · 0001387131-22-003161
2018-01-012018-12-31-24,016,188USD2021-03-0510-K · 0001387131-21-003179
2017-01-012017-12-3127,873,803USD2020-03-0610-K · 0001387131-20-002611
2016-01-012016-12-3111,596,273USD2019-03-0410-K · 0001387131-19-001670
2015-01-012015-12-3127,057,010USD2018-03-0510-K · 0001387131-18-000907
2014-01-012014-12-3121,417,368USD2017-03-0310-K · 0001387131-17-001160
2013-01-012013-12-3112,649,713USD2016-03-0410-K · 0001387131-16-004470
2012-01-012012-12-31-12,532,188USD2015-03-0910-K · 0001387131-15-000795
2011-01-012011-12-3148,669,823USD2014-03-1110-K/A · 0001387131-14-000823
2010-01-012010-12-3111,880,300USD2013-03-0510-K · 0001387131-13-000613
2009-01-012009-12-3120,380,293USD2012-03-0510-K · 0001387131-12-000574

Related Bank of South Carolina Corporation histories

Inspect the source

Entity
Bank of South Carolina Corporation / CIK 0001007273
Captured
SEC response SHA-256
19b83ef268e7c5f94d88f87891d29cf8ec86043661749a95ed67a0b67955a515

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/0001007273.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"])))