We are thrilled to let you know that XBRLAnalyst for Excel is now empowered with new algorithms for detecting and correcting typical errors made by SEC filers in XBRL reports, e.g. sign, scale or double negation errors. Now, your Excel-based financial models leveraging data provided by XBRLAnalyst will automatically load and show corrected data in Excel. The data is corrected in both, Document Viewer of XBRL reports and Excel spreadsheets using XBRLAnalyst’s built-in formulas.
In addition, with the help of our new algorithms, we identified typical financial concepts (XBRL tags) that have the highest number of sign errors or inconsistencies across several reports as well as observed that the number of sign errors was consistently decreasing in the last 2 years. Here are some examples from the list of top 50 concepts where filers make sign errors:
Results of this research will be presented in our next newsletter. These findings for sign errors re-enforce our previous study where we observed that the number of calculation errors in XBRL reports submitted to SEC decreases too (read more).
Here are some examples of sign errors detected and corrected by XBRLAnalyst:
If you need assistance building Excel models that leverage XBRLAnalyst tools, contact us at firstname.lastname@example.org. For video tutorials, visit https://findynamics.com/tutorials