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Do we still need traditional financial metrics?

A panel debate in London's Guildhall earlier this month, hosted by the CFA Institute and the IFRS Foundation, looked at how the role of traditional financial metrics is changing with the adoption of new technologies. It asked whether financial metrics used today are still relevant and discussed some of the hopes and fears for the future of financial data analysis. Here are some of the key comments and questions raised in the debate.

The hopes...

  • The sheer amount of “unstructured” data now available to companies and investors is overwhelming, from data analysis of customer behaviour by tracking their mobile phones, to tracking trade via sensors in ship containers, to the movement of goods in and out of warehouses. These types of non-traditional data sets can be analysed to try to predict future movements. The event's moderator, Jane Fuller, writes in her summary of the debate: “It is an edge in active investing that can be quickly eroded, but which can also move on quickly to the next set of unstructured (and therefore previously underused) data.”
  • In contrast, traditional financial metrics are “structured” and, Fuller argues, the value of traditional financial data lies in the fact that it has “standardised definitions, in its comparative reliability and in the long run of evidence on links to price movements”.
  • New sources of unstructured data include monitoring the tone of voice of executives at analyst meetings, to detect emotion that could give some additional meaning to data. Did anyone know that the CFO is apparently more reliable than the CEO?
  • Technology will enable auditors to test the whole set of a company's data, rather than just a sample, which could have implications for companies.
  • The issue of data quality and integrity persists – analysis is only as good as the data used.
  • Automation in financial reporting (and in the gathering of data) could shorten the time taken to report financial information to investors.

… and the fears

  • Automated and algorithmic trading is already here – but could it increase the possibility of a flash crash? This could be caused by a systems failure or a programme design failure, which could create automated crowd reactions.
  • The panel asked whether the importance of data analysis and software programming make the professions of financial analysis and accounting more or less attractive. They noted that people interested in the human aspects of the subject could be deterred.
  • Does more data mean better data and does it actually eliminate human biases, seeing as these could be incorporated in algorithms?
  • Standardised definitions remain important and the International Accounting Standards Board’s project on the primary financial statements will produce more sub-totals, possibly including operating income and earnings before interest and tax.
  • The debate also touched on the problem of asset price bubbles. In her summary Fuller writes: “But with so much of the technological approach related to price movements and gaining a relative edge, the fundamental question is who is setting prices with an eye on fundamental value? All the developments of recent years have done nothing to allay fears of asset price bubbles.”
  • She concludes that, in the face of technology's amazing capabilities, humans have an important role: to exercise healthy scepticism when needed.  

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Best Practices & Benchmarking in Operations
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