AUTOSCOPE TECHNOLOGIES CORP: income tax expense or benefit

Name: AUTOSCOPE TECHNOLOGIES CORP: income tax expense or benefit
Creator: AUTOSCOPE TECHNOLOGIES CORP

Income tax expense or benefit for AUTOSCOPE TECHNOLOGIES CORP. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All AUTOSCOPE TECHNOLOGIES CORP financial histories

What this measure means

Current and deferred income tax expense or benefit for continuing operations. This accounting expense differs from cash taxes paid.

Exact concept: us-gaap:IncomeTaxExpenseBenefit. 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 2021-12-31. The SEC response was captured on 2026-09-20.

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

Income tax expense or benefit in original reported units, latest-filed observation per period
Period start	Period end	Value	Unit	Filed	Source filing
2021-01-01	2021-12-31	905,000	USD	2022-03-22	10-K · 0000897101-22-000298
2020-01-01	2020-12-31	-462,000	USD	2022-03-22	10-K · 0000897101-22-000298
2019-01-01	2019-12-31	-5,165,000	USD	2021-03-11	10-K · 0000897101-21-000169
2018-01-01	2018-12-31	-10,000	USD	2020-03-12	10-K · 0000897101-20-000148
2017-01-01	2017-12-31	85,000	USD	2019-03-14	10-K · 0000897101-19-000222
2016-01-01	2016-12-31	-25,000	USD	2018-03-14	10-K · 0000897101-18-000263
2015-01-01	2015-12-31	18,000	USD	2017-03-24	10-K · 0000943034-17-000021
2014-01-01	2014-12-31	-154,000	USD	2016-03-10	10-K · 0000897101-16-001983
2013-01-01	2013-12-31	3,995,000	USD	2016-03-10	10-K · 0000897101-16-001983
2012-01-01	2012-12-31	-180,000	USD	2015-03-20	10-K · 0000897101-15-000381
2011-01-01	2011-12-31	-3,022,000	USD	2014-03-06	10-K · 0000897101-14-000273
2010-01-01	2010-12-31	910,000	USD	2013-03-27	10-K · 0000897101-13-000447
2009-01-01	2009-12-31	1,354,000	USD	2012-03-19	10-K · 0000897101-12-000474

Related financial histories

Inspect the source

Entity: AUTOSCOPE TECHNOLOGIES CORP / CIK 0000943034
Captured: 2026-09-20T05:10:10.501Z
SEC response SHA-256: cfb9622281452bfc371abc147803ca818052398df4638f41eafcc70a8334f550

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/0000943034.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"])))