About a-team Marketing Services
The knowledge platform for the financial technology industry
The knowledge platform for the financial technology industry

A-Team Insight Blogs

SEC Publishes Upgraded XBRL Taxonomy for Mutual Funds Risk/Return Reporting

Subscribe to our newsletter
As part of its work to support the reporting of risk/return summary information in XBRL by mutual funds in the US, the Securities and Exchange Commission (SEC) has finally completed a series of required updates to its technology infrastructure this week. Mutual funds can now create and fully test their XBRL documents in preparation for the 1 January 2011 compliance date.

To this end, the SEC has upgraded three specific technology infrastructure items: the risk/return summary taxonomy, its previewer/viewer and an XBRL validator. The 2010 risk/return summary taxonomy has been updated from its 2008 release primarily with technical changes to enhance the rendering of XBRL-tagged documents. The 2010 taxonomy is accompanied by sample tagged documents, an architecture guide, and a rendering guide. The SEC’s previewer/viewer has been updated to support this new taxonomy and accordingly, mutual funds can now preview how their risk/return submissions will appear.

Lastly, the Edgar system has been updated so that the XBRL validator will now test the risk/return summary XBRL exhibits to ensure compliance with the requirements of the Edgar Filer Manual Chapter 6.

The SEC is now asking mutual funds, filing agents and software vendors to begin the process of tagging their risk/return summary information, submitting test filings to Edgar to validate their documents, and previewing the documents in the previewer to help prepare for the compliance date.

The regulator has also recently been championing the use of XBRL in other areas such as corporate actions and in establishing a single data standard in the mortgage backed securities (MBS) market. Mark Bolgiano, president and CEO of XBRL US, spoke about the idea of XBRL tagging in the asset backed securities (ABS) markets last month.

“XBRL US has developed a prototype dictionary of terms for residential mortgage backed securities (RMBS) which could be a starting point to a broader development of XBRL data in the ABS market,” he explained. Philip Moyer, XBRL US board member and CEO of Edgar Online, has been heading a team at the standards body to develop the XBRL dictionary for mortgage data, which Bolgiano indicated is now ready for use.

Subscribe to our newsletter

Related content

WEBINAR

Recorded Webinar: Unlocking value: Harnessing modern data platforms for data integration, advanced investment analytics, visualisation and reporting

Modern data platforms are bringing efficiencies, scalability and powerful new capabilities to institutions and their data pipelines. They are enabling the use of new automation and analytical technologies that are also helping firms to derive more value from their data and reduce costs. Use cases of specific importance to the finance sector, such as data...

BLOG

Bloomberg BQuant Wins A-Team AICM Best AI Solution for Historical Data Analysis Award

When global markets were roiled by the announcement of massive US trade tariffs, Bloomberg saw the amount of financial and other data that runs through its systems surge to 600 billion data points, almost double the 400 billion it manages on an average day. “These were just mind-blowingly large volumes of data,” says James Jarvis,...

EVENT

AI in Data Management Summit New York City

Following the success of the 15th Data Management Summit NYC, A-Team Group are excited to announce our new event: AI in Data Management Summit NYC!

GUIDE

Regulatory Data Handbook 2025 – Thirteenth Edition

Welcome to the thirteenth edition of A-Team Group’s Regulatory Data Handbook, a unique and practical guide to capital markets regulation, regulatory change, and the data and data management requirements of compliance across Europe, the UK, US and Asia-Pacific. This year’s edition lands at a moment of accelerating regulatory divergence and intensifying data focused supervision. Inside,...