The XBRL Challenge was a contest held in 2013 and 2012 to discover the top open source analytical tools that can mine XBRL-formatted corporate financial data from the SEC’s EDGAR database. The contest awarded $20,000 Grand Prizes in each year to the contestants submitting the most useful and user-friendly application conducting innovative analysis of public companies.

What kind of apps did we look for?

Tools that rely on XBRL data from public company financial statements and that provide highly functional, strong analytics, e.g., performing multi-company year-to-year comparisons and ratio analysis.

Criteria for judging:

  • Improves access – enables investor stakeholder access to corporate data
  • Usability – application quality, usability, and accessibility
  • Analytics – provides minimum multi-company comparison, year-to-year comparisons, ratio analysis or other functions designed to help investor decision-making
  • Design – originality and creativity, cannot be drawn from an existing design

Background

Over 8800 US public companies report their financial statements in XBRL format. Data produced in XBRL format is computer-readable which gives it greater portability, reliability, accuracy and timeliness, and can provide individual and institutional investors with better information for investment decisions. With XBRL, investors around the world, both individual and institutional, have access to data with greater functionality.

Given the increased volume of corporate data now available globally in XBRL format, marketplace demand for tools to access XBRL data is on the rise and now is the optimal time to raise awareness and encourage development of tools for analysis. This challenge is designed to encourage the development of tools that can take advantage of the XBRL specification.

Participants to the contest will contribute open source applications for investors that leverage XBRL data from public companies. The goal of the program is to raise awareness among innovators, technologists, software providers and data aggregators about the wealth of XBRL data now available, and to encourage the development of investor applications for commercial use. Successful applications must demonstrate the unique functionality of XBRL, including improved timeliness and accuracy, and most importantly, they must provide strong, useable analytics that help users make investment decisions. They must be open source and must be able to consume XBRL filings prepared by companies in the US.

Comment