This article was first published in the January 2019 UK edition of Accounting and Business magazine.

Late last year, the Financial Reporting Council’s Lab issued three reports.

The first two are must-reads for any professional accountant interested in improving business model and risk and viability reporting, and performance metrics disclosures, and are called:

  • Implementation study: Business model reporting: Risk and viability reporting – Where are we now?
  • Performance metrics – Principles and practice.

The third, Artificial intelligence and the future of corporate reporting, offers an insight into the role that artificial intelligence (AI) is playing and will play in the world of corporate information.

Lab publications have always placed emphasis on the practical. Where are we now? and Performance metrics are no exceptions. Both are grounded in the knowledge and experience of practitioners – in particular, investors, management and other key stakeholders. Both offer a wealth of pragmatic guidance to help companies provide shareholders with the information that investors value most highly. Both illustrate their recommendations with numerous examples of good reporting practice.

Where are we now? reports the findings of the Lab’s desktop review of the business model and risk and viability reports of 100 UK companies. The publication looks at how well today’s corporate reports stack up against the recommendations published by the Lab in 2016 and 2017. As part of this exercise, the team also circled back with investors to understand whether today’s disclosures work in practice. The result is a guide full of detailed observations on specific disclosures from a number of companies.

How does this sample of companies fare in the review? The scorecard is mixed. ‘There are opportunities for improvement in all the areas that we reviewed,’ says Lab director Phil Fitz-Gerald. ‘However, if I had to highlight just one, it would be business model reporting. This is perhaps the hardest of the three areas to get right. Done well, it has the potential to provide a backbone to the structure of an annual report. Done badly, it leaves investors asking fundamental questions, such as what does the business do and how does it make money? Our review found a number of examples of good practice, but there are still many that sit at the other end of the scale.’

Performance metrics – Principles and practice builds on the Lab’s June 2018 Reporting of Performance Metrics. The earlier publication was warmly welcomed for its pragmatic insight into shareholder needs and for its handy five principles for effective communication. The latest report builds on these principles, offering detailed guidance for companies, along with a wealth of examples of good reporting practice.

‘Performance metrics are a cornerstone of good corporate reporting,’ explains Hannah Armitage, the performance metrics project lead. ‘They’re vital to investors as they try to understand the quality and sustainability of performance. However, all too often investors can be sceptical about how the metrics are presented. In this report, we offer preparers practical advice on how to make their disclosures more useful, illustrated by examples of good practice.’

The role of AI

If the first two reports are grounded in the needs of today’s practitioners, the third looks towards tomorrow’s reporting world. As part of its digital future project, the Lab is exploring how technologies such as XBRL and blockchain might change the production, distribution and consumption of corporate information. In the latest of its ‘deep dives’ into technology, the Lab tackles one of the hottest topics today – AI.

In Artificial intelligence and the future of corporate reporting, the Lab discusses how AI affects reporting today and how it might be used in the future. The Lab’s conclusion: despite the hype, implementation of AI in this area remains in its infancy. Indeed, most of the current uses cited by those interviewed for the Lab’s study are less about AI and more about automating existing processes. Unstructured data becomes structured, structured data is restructured, sophisticated algorithms are developed to interrogate data – but in all cases, human judgment remains centre-stage.

Should we be disappointed by the lack of progress? Far from it. AI is firing imaginations across all walks of life, including corporate reporting. As Thomas Toomse-Smith, the digital future project lead, says: ‘AI is a magic word with incredible power to convene groups of people. It acts as a catalyst for change in organisations, encouraging them to identify opportunities to automate existing processes.’

The report argues that for AI to fulfil its corporate information potential a number of factors need to come together. For example, the comparability, consistency and availability of information need to improve for it to become digital-friendly. Perhaps more fundamental, however, is the need to change the set of skills within the reporting industry.

Today, there are those who are experts in accounting and reporting. Down the corridor are those who understand technology. Few straddle both worlds. Until we have multidisciplinary expertise at the table, our ability to rethink how information is created, disseminated and analysed will be constrained.

It’s nothing new. When presented with a new technology, people typically start by trying to improve the old ways of doing things. Figuring out how to start a revolution takes time.

Alison Thomas is a consultant.