Views on improving the integrity of global capital markets
24 April 2020

Data Analytics to Set Policy, Evaluate Investments, and More

Posted In: Data Analytics, Webinar

Practical investors, securities analysts, and policy setters have long known the value of good quality, timely, and granular data. Access to this kind of data has increased dramatically with the availability of structured, machine-readable (XBRL) data. The XBRL webinar Data Analytics to Set Policy, Evaluate Investments, and More explains how access to better data is generating new ideas and enabling better decisions for everyone from standard setters and government policy makers to hedge funds, other buy-side firms, corporations.



In this webinar, I talk about how we at CFA Institute, apart from advocating for the greater use of XBRL for the benefit of investors, use XBRL data to support the analytical content that we provide to policy makers in our comment letters and thought leadership pieces.

CFA Institute also encourages policy makers to use XBRL data as part of their analysis as well as to provide data sets to their constituents in the consultation process. Providing the data set should become a standard protocol in an era in which the SEC has substantial XBRL data.

Image Credit: © Getty Images/ Nipitphon Na Chiangmai/ EyeEm

Tags:

About the Author(s)
Mohini Singh, ACA

Mohini Singh was director of financial reporting policy at CFA Institute. She represented membership interests regarding financial reporting and disclosure proposals issued by the FASB, the IASB, and others. Singh holds the Associate Chartered Accountant (ACA) designation.

Leave a Reply

Your email address will not be published. Required fields are marked *



By continuing to use the site, you agree to the use of cookies. more information

The cookie settings on this website are set to "allow cookies" to give you the best browsing experience possible. If you continue to use this website without changing your cookie settings or you click "Accept" below then you are consenting to this.

Close