Negative Values – Additions to Existing Rule
Additional elements added.
This document is intended to add additional explanation to the FASB implementation guide on Dimensional Modeling for Disclosures of Consolidated and Nonconsolidated Entities. In addition this document identifies DQC rules to ensure that that the practices defined in the FASB implementation guide are implemented.
This rule evaluates whether a fact expressed with no dimensions is equal to the same fact expressed in a table with dimensions.
The IFRS Taxonomy is designed so that the majority of elements have a positive value. This rule tests whether the values for a given list of elements are negative. The rule does not test elements when a specified member is present which would allow the value to be negative.
Issue A filer’s financial report often includes data of a company other than the consolidated entity. This occurs when an entity reports information about another company because it is a subsidiary, a spinoff, an acquisition, the parent holding company, etc. The axis used to report values for a company other than the consolidated entity is […more]
This rule identifies if OCI items have been included in the calculation of net income. The rule was updated in version 21 to also identify if net income items are included in OCI.
SEC filers, investors, XBRL providers encouraged to comment, and to use approved Ruleset 9 The XBRL US Data Quality Committee (DQC) has published its 10th Ruleset for a 45-day public review and comment period, which closes on September 16, 2019. DQC rules are developed to aid issuers in preparing consistent, error-free financials, by providing automated […more]
The Data Quality Committee has approved and finalized IFRS validation rules, along with US GAAP rules in its 6th ruleset. Foreign private issuers and US GAAP filers should use the rules by the June 29, 2018 effective date.
XBRL US announced today that the XBRL US Data Quality Committee has approved and published the first set of validation rules to help public companies detect inconsistencies or errors in their XBRL-formatted financial data. The rules cover approximately 2,400 concepts and identify potential errors such as incorrect negative or positive values, improper relationships between elements, and incorrect dates associated with certain data.