The new XBRL 2.1 conformance suite is now available, supporting the continued robustness and interoperability of XBRL implementations. This update ensures that software tools align with the base specification and behave consistently across different reporting scenarios.
XBRL International recently hosted a fast-paced 30-minute webinar diving into Calculations 1.1, the latest upgrade to XBRL’s calculation rules. If you missed it, no worries: the recording is now available.
Artificial intelligence promises to transform how we analyse financial (and other business) data, with major platforms launching ambitious tools to democratise investment insights. But behind the excitement lies a critical question: can AI actually understand what it’s reading?
We know AI is powerful. It promises big: critical insights from overwhelming data volumes, actionable findings from vague hunches, and the answers to the questions you didn’t even know you needed to ask.
Catch up on report packages now. If you couldn’t make it to our XBRL Directions webinar on 15 May, don’t worry, we’ve got you covered. The recording is now available, offering an insight-packed 30-minute overview of XBRL Report Packages and how to make the most of them.
Everyone’s experimenting with AI. LLMs are being thrown at everything (from earnings calls to ESG scoring to automated due diligence) and there’s a growing sense that we’re on the edge of something transformative in financial analysis.
The European Securities and Markets Authority (ESMA) this week closed its consultation on critical updates set to expand the EU’s digital reporting regime.
XBRL International has written to the European Securities and Markets Authority (ESMA) suggesting xBRL-CSV as the ideal format for disclosures on private securitisation.
The XBRL Standards Board has approved the release of a second Public Working Draft (PWD) of the Table Constraints specification. This modular enhancement to the xBRL-CSV format is designed to enable highly efficient validation of business rules, especially when dealing with very large xBRL-CSV reports.
How can large language models (LLMs) improve the way we work with XBRL taxonomies? In her latest blog, XBRL International Guidance Manager Revathy Ramanan explores how AI-powered tools can support taxonomy authors and software vendors, improving taxonomy quality, clarity, and usability.
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XBRL International is a global not for profit operating in the public interest. Our purpose is to improve the accountability and transparency of business performance globally, by providing the open data exchange standard for business reporting.
