This is the first in a series of articles exploring XBRL. Our next article will consider how XBRL was developed and the wider advantages and disadvantages of XBRL as a financial reporting tool
The Fourth Industrial Revolution (4IR) era is characterised by an advanced interconnectivity of electronic data that has enabled machine learning to such an extent that computers make autonomous decisions without human intervention. It is an era that allows our knowledge processes, and not just our production processes, to be automated through the fusion of an array of technologies.
eXtensible Business Reporting Language (XBRL)-based structured digital financial reporting is one of the key technologies leading the charge of accounting application systems into the 4IR. The others are knowledge-based system applications of artificial intelligence, and blockchain-based distributed ledgers.
While XBRL does not change the rules of financial reporting as prescribed by accounting regulatory bodies, it changes the manner in which financial reports are prepared and used globally. One of the key factors driving this change is the fact that XBRL -structured and -tagged financial information is machine readable and can therefore be analysed by computers. In contrast, paper-based financial reports, including PDF financial reports, have to be read, interpreted and analysed by humans.
But what is XBRL?
Now, while this all sounds great, one is still left with the question: what is XBRL actually? In essence, XBRL is a process through which a defined taxonomy, or library, of computer readable data tags is electronically attached and coded to financial information and values reported by entities. This results in richer and more meaningful financial information that is read and interpreted by machines for data analysis, validation and programmed decision-making with little or no human intervention required.
This is illustrated using a simple example. Assume two companies in an industry sector. Company X presents revenue as ‘gross income’ and Company Y presents revenue as ‘turnover’ in their respective statements of profit or loss. Both companies add a computer code <Revenue/> to these reported values using an XBRL application tool. An analyst can now use an application instructing it to read the value <Revenue/> from all published XBRL-tagged financial information in an industry, ideally located in a central repository. The application can perform a real-time comparison of revenue as soon it has access to appropriately tagged data and potentially alert investment analysts based on predetermined coded parameters to enable fluid and near instantaneous investment decisions.
Without XBRL, individual financial statements in various unstructured data formats will have to be identified and manually entered for comparison, requiring significant human intervention with the associated risk of human error being introduced when making investment decisions.
By generating machine readable financial information in XBRL formats, financial reporting processes are performed more efficiently and effectively. Analysis and comparison of XBRL -tagged financial information is automated and performed by computers or other machines, resulting in more efficient investment management decisions and regulatory oversight of reported data.
Current application of XBRL in South Africa
In South Africa, the Companies and Intellectual Property Commission of South Africa (CIPC) changed their submission regulations for reporting financial information. From 1 July 2018, all South African companies registered with CIPC no longer submit their minimum statutory compliance documentation as PDF documents to CIPC. Instead these entities are mandated to use an inline-XBRL (iXBRL) digital format for filing purposes to embrace international best practices and improve regulatory efficiencies at CIPC.
CIPC filers upload their minimum statutory compliance documentation tagged digitally (using an XBRL reporting solution) via a web-based portal on the CIPC website. CIPC uses computerised automated data validation to evaluate the uploaded data sets and can potentially verify all data submitted to them as opposed to sampling documentation for verification, which was required pre-XBRL due to capacity constraints. A significant amount of information on the processes and data models can be accessed at http://www.cipc.co.za/index.php/xbrl-programme/.
Why is this potentially beneficial to you?
Following the successful roll out of the XBRL filing program by CIPC, more regulators in South Africa, like SARS, are actively investigating the application of XBRL as a tool to potentially streamline statutory reporting to achieve compliance. As more regulators adopt XBRL reporting for statutory submissions, a single set of data can potentially be prepared and uploaded to comply with multiple statutory reporting requirements, resulting in a reduction in the cost and time associated with compliance.
In the investment analyst space, the benefits of XBRL should be apparent from the earlier discussion on how XBRL works. Improved efficiency and accuracy in data collection, interpretation and decision-making processes are expected.
Considering the financial reporting space, the potential benefits of using XBRL technology could be substantial and contribute to the quality of data available, resulting in more useful financial reporting. For instance, one can conceive that the wide-spread adoption of XBRL-based financial reports will result in increased comparability and understandability of financial statements between companies when these are coded using the same taxonomy or dictionary of tag items. A standard layout according to the IASB’s taxonomies could remove bias from reporting as all items will appear with equal prominence once coded into a structured format. Lastly, information will be able to be distributed more efficiently in a computer-readable, standardised format that will result in more timely financial information being available to users for decision-making purposes.
During the COVID-19 pandemic, we have seen companies accelerating their reliance on technology. From remote working tools and cloud-based services to automation and analytics, companies are seeking to ensure productivity today in search of relevance tomorrow. Wide-spread adoption of XBRL will ensure relevance in the 4IR, renewing confidence in the quality of data available for decision-making.
Yvette Kulik CA(SA) MCom, Senior Lecturer at UJ, and Ahmed Mohammadali Haji CA(SA) MCom, Associate Professor at UJ