VisionSys AI Inc: income taxes paid, net

Name: VisionSys AI Inc: income taxes paid, net
Creator: VisionSys AI Inc

Income taxes paid, net for VisionSys AI Inc. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All VisionSys AI Inc financial histories

What this measure means

Cash income taxes paid net of refunds during the period. It differs from income tax expense and can reflect prior years and estimated payments.

Exact concept: us-gaap:IncomeTaxesPaidNet. 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 2012-01-01 to 2015-12-31. 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 taxes paid, net in original reported units, latest-filed observation per period
Period start	Period end	Value	Unit	Filed	Source filing
2015-01-01	2015-12-31	360,686	USD	2016-04-20	20-F · 0001144204-16-095204
2014-01-01	2014-12-31	567,401	USD	2016-04-20	20-F · 0001144204-16-095204
2013-01-01	2013-12-31	1,846,576	USD	2016-04-20	20-F · 0001144204-16-095204
2012-01-01	2012-12-31	1,038,042	USD	2015-04-15	20-F · 0001144204-15-022976

Related financial histories

Inspect the source

Entity: VisionSys AI Inc / CIK 0001592560
Captured: 2026-09-20T09:24:19.062Z
SEC response SHA-256: 5919c855b0988061fb2346196c3c9680aae00f1513514d6cc0ac4fe74232a035

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/0001592560.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"])))