News October 2018 Blog: A day with XBRL

Blog: A day with XBRL

10 October 2018

By an intern with the Financial Reporting Lab

Over the summer, I joined the Financial Reporting Lab at the Financial Reporting Council  to complete a
one-day work experience. I sought out this position because investing and programming fascinate me and I figured that this would be a good way for me to experience the intersection of these two fields. Prior to the day, I was told that I would be looking at a technology called XBRL (extensible Business Reporting Language). 

When I arrived, I was told a little bit more about XBRL, its use by the US Securities and Exchange Commission since 2009, and how it will be introduced as a requirement in Europe in 2020. The directors of the Lab explained the way the Lab had been looking at XBRL as part of their ‘Digital Future’ project. They then pointed to some background sources and set me the challenge to build an investment analysis tool using this technology, to see what could really be achieved in a single day.
I spent about half the day trying to understand more about XBRL and how it worked. I watched some YouTube videos that did a good job of explaining XBRL, as well as reviewing some interesting background information on XBRL US’s website. I specifically found the Data Analysis Toolkit page useful.

So, what is XBRL?

XBRL is a language based on a set of standards used to “tag” reporting terms in financial statements so that anyone can consistently and easily extract financial data digitally.
The primary benefit of XBRL to investors and analysts is that financially reported data is easily accessible and usable, which can help to save time and drive efficiencies when analysing company financial statements. The benefit to reporting companies is that their data is more widely available and more easily accessed. To use an analogy, XBRL aims to modernise traditional paper-based financial reporting in the same way that Google has digitised traditional paper maps (paper and PDF reports) and converts them into digitised maps available on its Google Maps platform. In addition, once digitised, the XBRL platform will allow developers to build applications on top of XBRL (similar to how ‘Uber, ‘Find my Friends’ and planefinder’ are built on top of digital maps) providing more and better tools for investors

Using XBRL to build an investment analysis tool

I spent the other part of the day developing the tool. I discovered that you could quite painlessly pull financial data via XBRL to Google sheets. XBRL US has two templates that I used together with the provided documentation to figure out how it works. I built on top of these templates for balance sheet comparisons and margin calculators to develop my investment analysis application. This analysis was based on old-school Benjamin Graham value style analysis with the following criteria taken from the investment bible 'Security Analysis'. Using XBRL you can create an Analysis tool to fit your style of investing.

Automating the investment process

The beauty of this system is that once it's set up, you just have to change the ticker symbol to see all of this data for any company that complies with XBRL regulation. To be honest it blew my mind that I could just enter the ticker symbol of a stock and see my analysis of the company. I designed this tool, not as an all in one investment analyser, but as a tool that might significantly accelerate one of the larger and more tedious parts of the investment process – valuation; is this stock cheap, expensive or fairly priced? This tool handles a large part of the quantitative side of the investment process. It is still up to the investor to figure out how good a company it is.
Of course, all of this would be possible manually but it would mean trawling through the annual report to find the required data and then physically calculating the ratios and averages. This is not only time consuming, mundane work but it is also prone to human error.

Some issues I found with XBRL

So what did I learn? XBRL has the potential to be an incredibly useful tool for the retail investor. It gives them easy access to accurate data that to date has typically only been available to institutional investors who are able to use tools such as the Bloomberg and Thomson Reuters. However, in my short time with XBRL, there are three things holding it back from truly becoming the standard for digital business reporting.
The main issue is currently quality of data. For example, some companies have no value for earnings of the past year even if the annual report shows that the earnings are there. Currently, the lack of consistently reliable data means that the data must be looked over by humans to ensure accuracy which defeats the purpose of the language.
Second, it is slow to pull data when compared to other financial platforms. From my testing, it took on average about four seconds to pull a company's balance sheet from the XBRL database, while other platforms I’ve used are far faster. However this is not a big issue for smaller data sets but could be for larger ones.
Lastly, XBRL is not particularly user-friendly at this stage of its development and I would suspect that many would find it difficult to extract data and use the language effectively.  


Digitally enabled financial reporting (using XBRL) has the potential to become a revolutionary technology, particularly for the retail investor. Legislation will drive a step change in the use of XBRL for the production and consumption of the annual reports for thousands of European listed companies and if implemented effectively, it will facilitate the use of corporate communication and data across Europe, truly digitally, for the first time. In the future, I am confident that new investment tools of all shapes and sizes will then be developed on the back of the XBRL platform providing financial information that can be easily analysed, compared and transformed to other formats without extensive and burdensome manual processing. This will give investors a key tool to streamline their investment analysis process without sacrificing quality. Overall, this will make company financial data more comparable, transparent and digitally accessible.