Pushing municipal finance toward open data
- By Matt Leonard
- Dec 10, 2018
What: “Transparent State and Local Financial Reporting: The Case for an Open Data CAFR,” a report from the Data Foundation and Workiva.
Why: Open and machine-readable Comprehensive Annual Financial Reports (CAFR) – documents that a state or municipal government uses show its financial position – offer several benefits. They allow citizens to track spending and streamline municipal bond financing, making it easier for investors to determine creditworthiness. Having this data more readily available would also help the government itself meet its many reporting requirements.
Findings: While there are best practices and models to follow for open-data CAFRs, the two-phase transition is not an easy one because of the cost and learning curve, the report says. Participants must agree on an information model so the words in the reports always refer to the same concepts in the same way. Many governments already use the Government Finance Officers Association’s Governmental Accounting, Auditing, and Financial Reporting or “Blue Book” to create their information model. Documents following the information model would be encoded in a machine-readable syntax, usually eXtensible Business Reporting Language, or XBRL, before they are released as machine-readable open data.
Benefits to municipalities include more immediate access to financial data and savings accruing from no longer needing to translate CAFR PDFs into machine-readable data, which could spur development of new applications to improve management, public confidence and oversight. With an open data CAFR, governments could more easily uncover anomalies and compare financial information with jurisdictions having similar characteristics to their own.
Verbatim: “There are no technology barriers to prevent the movement to an open data model for governmental reporting. The only impediments to forward progress are human and institutional factors.”
Read the full report here.
Matt Leonard is a former reporter for GCN.