Investment Schedule Guidance also published for public review
The XBRL US Data Quality Committee (DQC) has published its 19th Rule Set for a 45-day public review and comment period, which closes on September 1, 2022. The freely available DQC rules are developed through a collaborative process with stakeholders by exposing proposed guidance and validation rules for public comment. Staff of the Financial Accounting Standards Board (FASB) and the International Accounting Standards Board (IASB) act as observers of the work of the DQC. The DQC considers guidance by the FASB to ensure that filers have consistent, reliable rules that are accepted by authoritative sources.
This latest draft rule set contains three rules specific to US GAAP filers:
- Bank Ratios – Scale Issues. This rule alerts filers when capital adequacy ratios have been reported with an incorrect scale. It also ensures that filers have used the appropriate elements to report their capital adequacy ratios.
- Investment Schedule Cross Calculation. This rule checks that the investment schedule correctly calculates the difference between amortized cost and fair value, to identify misused elements.
- Inconsistent Accrued Interest Elements.The rule ensures that consistent elements are reported in the investment schedule for including or excluding accrued interest elements, depending on the filer’s accounting policy election.
The DQC has also developed guidance on how best to prepare reports featuring debt securities. The Investment Guide FAQ is designed as a companion to the Financial Accounting Standards Board (FASB) implementation guide on “Financial Instruments – Debt Securities” that was published in 2021. It includes detailed illustrations and examples to assist filers in preparing investment schedules efficiently, and consistent with the modeling of the US GAAP Taxonomy. A free webinar will be held on July 20, 2022 to explain the new rules and guidance. Register here: https://xbrl.us/events/220720/
DQC rules are freely available to issuers that use US GAAP and IFRS to help them validate their filings and identify potential errors. Using DQC rules aids issuers to prepare consistent, high quality XBRL financials, by providing automated checks that test XBRL-formatted financial statements prior to SEC submission. The DQC is funded through the XBRL US Center for Data Quality.
Issuers that use the freely available rules can find and correct errors, to ensure that regulators and investors are provided with good quality data and the most accurate view of corporate financial health. Filers, data providers, investors, accountants, and preparation tool providers are encouraged to review and comment on the proposed rules. Access the public review for DQC Rule Set 19: https://xbrl.us/data-quality/rules-guidance/public-review/
The XBRL US Filing Results & Quality Checks application allows SEC Filers or other interested parties to check EDGAR submissions for DQC errors for any company here: https://xbrl.us/data-quality/filing-results/
Graphical depictions of historical DQC error count, categorized by rule type, can be seen here: https://xbrl.us/data-quality/filing-results/dqc-results/
Filers have immediate access to all final approved rules as well as the 19th Rule Set in public review so that they can check their filings prior to SEC submission. There are several options available to filers:
- Through software that has been certified to run with the ruleset: https://xbrl.us/certification
- Through the XBRL US checking tool: https://xbrl.us/check
- By downloading the Approved Rules and using them with Arelle – the open source version of the SEC’s EDGAR Renderer/Previewer: https://xbrl.us/dqc-releases
To access the approved rules and guidance, go to: https://xbrl.us/rules-guidance
Members of the XBRL US Center for Data Quality include Altova, the American Institute of CPAs (AICPA), Broadridge Financial Solutions , Certent, DataTracks, Donnelley Financial Solutions (DFIN), EDGAR Agents, RDG Filings, Toppan Merrill, and Workiva, Inc.
For more information on the XBRL US Data Quality Committee and the Center for Data Quality, go to: http://xbrl.us/data-quality
