Intrinio

A member of our Financial Services community since September, 2016.

Intrinio’s mission is to power the innovators defining the future of finance through modern data technologies. That means automating the data supply chain with advanced infrastructure and machine learning, delivering high-quality data through cutting-edge tools designed for developers and engineers, and getting it all in the hands of people who are challenging the system. We […more]


Workiva

A member of our Software and Services community since December, 2011.

Workiva (NYSE:WK) created Wdesk, a cloud-based productivity platform for enterprises to collect, link, report and analyze business data with control and accountability. Thousands of organizations, including over 65% of the 500 largest U.S. corporations by total revenue, use Wdesk. The platform’s proprietary word processing, spreadsheet and presentation applications are integrated and built upon a data […more]


2022 Florida Open Financial Statement Taxonomy

For fiscal years ending on or after September 1, 2022, local governments are to report financial data required by Section 218.32, Florida Statutes using extensible business reporting language (XBRL).


ACFR Taxonomy 2022

Government agency representatives, municipal analysts and investors, software providers, and other users of state and local government data are invited to review and comment on the data standards developed to represent sections of the Annual Comprehensive Financial Report (ACFR). This version of the ACFR Taxonomy was open for comment between July 15 and August 15, […more]


Michigan House Bill 5783 Appropriates IT Funds for Machine-Readable (XBRL) Govt Data

Michigan Governor Whitmer signed off on House Bill No. 5783 which includes appropriations for fiscal years 2022 and 2023. The bill includes funding for Michigan State Treasury to work in partnership with a public university located in Michigan to develop an IT strategy focusing on machine-readable financial disclosures for local units of government, and that […more]


The University of Michigan moves to modernize government financial reporting

Marc Joffe, Senior Policy Analyst at Reason Foundation (XBRL US member) noted in a recent blog post, “XBRL can make data from state and local governments more digestible and publicly available. In 2002, three academic researchers proposed applying eXtensible Business Reporting Language (XBRL) to state and local government financial reporting to make municipal data more digestible and […more]


University of Michigan and XBRL US Launch Public Review of Government Data Standards

Governments, standard setters, regulators, and analysts encouraged to provide input XBRL US, a nonprofit standards organization, and the Center for Local, State, and Urban Policy (CLOSUP) at University of Michigan’s Gerald R. Ford School of Public Policy, announced the publication of digital financial data standards for local government reporting entities, that can be used to […more]


Public Review: Annual Comprehensive Financial Report Taxonomy

Wednesday, June 15 - Monday, August 15, 2022
XBRL US Public Review
Get details and comment on the Release Candidate

The University of Michigan’s Center for Local, State and Urban Policy (CLOSUP) is working with the XBRL US Standard Government Reporting Working Group (SGR) to modernize and digitize Michigan local government financial reporting, with the City of Flint as the first local government partner and pilot site.


University of Michigan Partners with Flint, MI on XBRL Reporting Program

The University of Michigan announced a partnership with the city of Flint, MI, on a fiscal reporting pilot program to improve transparency and governance. The pilot centers on developing digitized data standards to represent the Annual Comprehensive Financial Report (ACFR), and will build on the XBRL Taxonomy developed by the XBRL US Standard Government Reporting […more]


Grants Reporting Case Study: College of DuPage

Executive Summary Reporting, collecting, and analyzing data about individual grants, and the grantees themselves, is time-consuming, labor-intensive, and costly. Grantees prepare multiple forms, and duplicate data reported. Federal awarding agencies and other users of grantee information manually extract data from inconsistently prepared PDF forms or text files. The GREAT (Grants Reporting Efficiency and Transparency) Act […more]