XBRL, short for eXtensible business reporting language, is a global digital standard for exchanging business information. In the financial community analysts are most likely to experience its power when working with financial statements. This is because many of the major global securities regulators (e.g., the US Securities and Exchange Commission (SEC)) require reporting of financial results using XBRL. Once data is in this format, all of the power of connectivity facilitated by the internet and all of the power of computation facilitated by software — and even artificial intelligence (AI) engines — can be deployed to analyze and understand financial data. It truly is a whole new world.

Yet few firms are taking advantage of XBRL and its power. Calcbench is one firm utilizing XBRL in an attempt to change your life as a research analyst. Here is an interview conducted with its two founding members, Pranav Ghai and Alex Rapp, designed to help analysts learn more about XBRL.

Enterprising Investor: Why is XBRL so interesting for analysts?

Pranav Ghai and Alex Rapp: XBRL allows for digitally reporting all of the numerical facts and some textual information from the financial statements and disclosures within financial statements, including all 10-Ks and 10-Qs in the United States. Virtually all of the, roughly 9,000 public firms trading in the United States are required to do this.

XBRL is so interesting to analysts because for the first time you have a fully searchable database of as-reported, line-item detail from all of these reports. The original financials are there exactly as the company presented them. The hard-to-find facts are no longer hard to find. All of the detailed segment breakouts, schedules, and roll forwards are available for searching, analyzing, [and] comparing over time and across companies.

If applied properly, XBRL can help answer routine questions like:

• How did a firm’s revenues grow over the last quarter?
• How much in overseas profits are firms X, Y, and Z not repatriating into the United States?
• How do the net operating loss tax loss carry forwards affect the balance sheets of the pharmaceuticals industry?

And all of this data appears within minutes of the firm filing their report.

What is your estimate for how many analysts are currently taking advantage of the power of XBRL? Why is this number so low?

We’ve actually come across a number of analysts who have built their own XBRL solutions with varying degrees of success. Also, a lot of analysts are using this data without knowing it, as many of the large data providers have a small amount of XBRL now built into their collection process. But to really take advantage requires a very technical person with a lot of free time to build a database and other tools. This simply doesn’t describe most research analysts. They’re much better off letting someone else handle the technical aspects.

What motivated you both to dedicate huge swathes of your lives to creating Calcbench?

We each come from separate sides of the Street. Pranav spent years at Morgan Stanley in a largely quantitative role, and Alex worked as a qualitative analyst at a small hedge fund. But both of us were very interested in fundamental data, and the more the better. When we first were introduced to the XBRL data set it just seemed perfect for us . . . big, messy, and filled with extremely valuable hidden nuggets. Once you get hooked on it, it’s not possible to go back to the old way. Even the best of the big data providers have a tendency to look at the world as a set numbers in a two-dimensional spreadsheet with a predefined number of rows and columns. XBRL captures all of the dimensions, all of the granularity, without limitations on size or shape.

What are the future directions you imagine for XBRL? Any predictions for when adoption of it gains critical mass?

What will speed up adoption? People building more and more advanced consumption tools the way we are. The SEC XBRL data set now has five good years of history and is becoming very hard to ignore if you are serious, data-driven analyst. We don’t think it will be much longer before everyone analyzing fundamentals will have XBRL somewhere in their process.

In addition, the future for tagged data in general, of which XBRL is a subset, is very bright. Computers and computing techniques are getting more advanced by the hour, and there is clearly a need for the world to move beyond filing so much of this information on “paper” reports.

As the standard continues to gain momentum in the United States, other geographies will speed up their adoption rates and continue to open their data sets to the public. As soon as you see sovereigns like the United Kingdom and the European Union follow the lead of the United States, we expect that there will be a continued move for consumption of this information.

Plus, XBRL plays a prominent role as part of the Digital Accountability and Transparency Act of 2013 (DATA Act) that was signed into law by the President in May of 2014. So there is major federal support for electronic data standards in general. From our point of view, the tagging of information, whether it is financial or not, is the future. So our message to everyone is to get on board.

You have alluded to some of what makes Calcbench unique. What are some of the things your offering does that some of your competition, like Estimize and Iris, does not?

Calcbench is a research and analysis platform. Our specialty is making data come to life for anyone interested in researching fundamentals. We make it easy for people to take advantage of the richness and the interactivity of XBRL without even having to know what XBRL is. This is a platform that anyone can use, whether you have a basic knowledge of fundamental data or you are one of our expert analysts who sit on there all day long. You can dive deep into individual companies, or quickly compare and aggregate across companies and industries. Our customers use income statements spread out over time in as reported detail, and examine companies’ tax footnotes side by side.  You can do things like search geographical segment revenue for companies that report revenue in China, or fetch the detailed breakout of a bank’s financial instruments at fair value. These are just a handful of the things that our clients do. To date, we know of no other platform that can allow a user to drill into a footnote and then extract a concept from the same footnote and ask who else is reporting that concept and in what dollar amount.

Behind the scenes, we accomplish these things by employing a very powerful set of artificial intelligence–based tools combined with a deep knowledge of the accounting and finance topics, plus a willingness to roll up our own sleeves and get our hands dirty: in short: turning the messy, raw XBRL into a clean, easy-to-use dataset without giving up any of its power, and building our own innovative consumption tools on top of it.

Image credit: ©iStockphoto.com/erhui1979

Originally published on CFA Institute’s  Enterprising Investor.