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Digital Media Solutions, Inc.: filings

Every Digital Media Solutions, Inc. annual and quarterly report in the SEC record with the published financial measures it tagged, 30 filings, each linked to its SEC index.

Filing record ends 2024-05-15

The latest filing in this captured record is a 10-Q filed 2024-05-15. No later filing is in the SEC companyfacts record captured on 2026-09-22. Digital Media Solutions, Inc. may have stopped filing, merged, or changed its reporting entity; nothing on this page describes its current status. Values are as reported at the time.

Filings with published measures

Each page shows what one filing reported, as tagged in that filing, with the periods it covered. Later filings can restate a value; the company overview shows the latest-filed value per period.

FormFiledFiscal periodMeasuresFactsSEC accession
10-Q2024-05-15fiscal Q1 202446960001628280-24-023625
10-K2024-04-18fiscal FY 2023551110001628280-24-016708
10-Q2023-11-14fiscal Q3 2023481330001628280-23-038985
10-Q2023-08-18fiscal Q2 2023471290001628280-23-029901
10-Q2023-05-15fiscal Q1 202346930001628280-23-018259
10-K/A2023-04-05fiscal FY 2022541100001628280-23-010860
10-K2023-03-31fiscal FY 2022541100001628280-23-010238
10-Q2022-11-09fiscal Q3 2022441260001628280-22-029302
10-Q2022-08-09fiscal Q2 2022431240001628280-22-022006
10-Q2022-05-10fiscal Q1 202242880001628280-22-013658
10-K2022-03-16fiscal FY 2021501030001628280-22-006362
10-Q2021-11-09fiscal Q3 2021431280001725134-21-000202
10-Q2021-08-09fiscal Q2 2021431140001725134-21-000142
10-Q2021-08-09fiscal Q2 2021431140001725134-21-000140
10-Q2021-08-09fiscal Q2 2021431140001725134-21-000138
10-K/A2021-05-18fiscal FY 2020481410001725134-21-000093
10-Q2021-05-18fiscal Q3 202045900001725134-21-000086
10-K/A2021-05-18fiscal FY 2020481410001725134-21-000084
10-K2021-03-16fiscal FY 2020481300001725134-21-000043
10-Q2020-11-09fiscal Q3 2020371060001725134-20-000040
10-Q2020-08-10fiscal Q2 202018470001193125-20-215049
10-Q2020-05-08fiscal Q1 202018370001193125-20-137702
10-K2020-03-13fiscal FY 201918350001193125-20-073028
10-Q2019-11-12fiscal Q3 201918510001193125-19-290000
10-Q2019-08-09fiscal Q2 201918470001193125-19-218037
10-Q2019-05-10fiscal Q1 201918370001193125-19-144327
10-K2019-03-29fiscal FY 201819340001193125-19-092728
10-Q2018-11-09fiscal Q3 201818290001193125-18-323811
10-Q2018-08-10fiscal Q2 201818300001193125-18-246098
10-Q2018-05-11fiscal Q1 201812200001193125-18-160919

Inspect the source

Entity
Digital Media Solutions, Inc. / CIK 0001725134
Captured
SEC response SHA-256
26bd26aefe4534e80468a31234966c07fcbf06a2ba13ccc5cc0468edf5bf39fb

Current SEC company facts · Download the original response snapshot (gzip) · Download the selected JSON

Every published concept a filing tagged, with the periods it covered, as reported in that filing at capture time. Forms 10-K, 10-K/A, 10-Q, 10-Q/A, 20-F, 20-F/A, 40-F, 40-F/A. A filing page needs at least 8 published concepts. Later filings can restate these values; the company history pages show the latest-filed value per period.

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/0001725134.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"])))