Reduce the regulatory burden, while there are still humans to notice!

The Canadian Securities Administrators recently published CSA Consultation Paper 51-404 Considerations for Reducing Regulatory Burden for Non-Investment Fund Reporting Issuers, seeking “comments on potential options for reducing regulatory burden for non-investment fund reporting issuers in the public markets.”

Nothing in the paper would affect the application of IFRS in Canada, but it certainly might change aspects of the overall structure within which investors access IFRS-compliant information. Here’s how the accompanying news release summed up the exercise:

  • “Regulatory requirements and the associated compliance costs should be proportionate to the regulatory objectives sought,” said Louis Morisset, CSA Chair and President and CEO of the Autorité des marchés financiers. “The purpose of this consultation is to identify potential ways to reduce regulatory burden in the public markets without compromising investor protection or the efficiency of the capital markets.”
  • The Consultation Paper identifies and seeks input on potential options for reducing regulatory burden associated with capital raising in the public markets and the ongoing costs of remaining a reporting issuer. These options include:
    • expanding the application of streamlined rules for smaller reporting issuers;
    • reducing the regulatory burden associated with prospectus rules and the offering process;
    • reducing certain ongoing disclosure requirements;
    • eliminating overlap in potentially duplicative regulatory requirements; and
    • enhancing the electronic delivery of documents.

Many reasons exist for reexamining these kinds of issues on a periodic basis – technological change being preeminent among them. Among much else, a recent article in the Financial Post cited an announcement by Blackrock Inc. that “it is replacing human stock pickers with machine-run algorithms for some of its equity funds,” going on:

  • “Whether it’s Apple Inc.’s Siri intelligent assistant or IBM Corp.’s Watson supercomputer, AI-driven programs use enormous amounts of data to solve increasingly difficult problems.
  • For investors, that could include the extraction of sentiment from SEC filings and social media, or using satellite and location data from parking lots and mobile phones, according to David Andre and Conrad Gann, the respective CEO and COO of San Francisco-based Cerebellum Capital.
  • Many quantitative funds now use big data derived from a growing number of asset classes and economic indicators, and some even utilize computer models to track social sentiment found on platforms such as Twitter and Facebook.
  • A recent study by the CFA Institute found that only 20 per cent of CEOs at asset management firms believe analysis skills will be important over the next five to 10 years…”

It’s not really clear whether the CSA’s initiative will attempt to grapple with this kind of evolution, and (say) to consider to what extent the disclosure regime should attempt to identify and address the interests of these AI stock pickers. As far as one can tell, the main focus of the exercise will be on the opinions expressed by, uh, humans, whether individuals or in groups, based on their own experience and doctrine. This can be a good basis for getting some stimulating input, but one shouldn’t overlook its severe limitations. For an almost exact parallel, consider a theoretical public consultation on how to reengineer the tax code – people would respond based on their views of the stimulative effect of lower taxes, the relative importance of deficits, concepts of social equality and justice and so on, but none of this would or could provide an objective basis for determining the best thing to do. Such judgments, inevitably, are ultimately as much a function of morality as of science. (In a very interesting and useful recent paper, the OSC explored various behavioral issues which also point to the problems of such exercises – for example, respondents might be biased to make the arguments which seem most consistent with their self-image, regardless of the underlying facts.)

To illustrate, the paper mentions in the context of quarterly reporting that “Some academic commentators and business leaders have suggested that quarterly reporting encourages reporting issuers to focus too heavily on short-term financial results, to the detriment of the reporting issuer’s business over the longer-term.” Indeed, I’ve cited that debate here a couple of times. But as I wrote before, whether that’s a problem is surely as much a ideological determination as anything else (it’s not obvious by the way that discouraging reporting issuers from focusing on the short-term is at all part of the CSA’s mandate, as long as the issuers clearly disclose their strategy as being such). The paper might have been more likely to draw contemplative responses, it seems to me, if it had tried to bring out such matters of context and to better define the structure within which to assess the questions being asked. Likewise, as the very choice of the term “reducing regulatory burden” suggests a predisposition to find burdensome things that can be reduced, the paper might have asserted more definitively which of the existing requirements seem to the CSA to be unnecessary, and asked for specific commentary on why that’s the wrong determination. After all, they probably know as well as anyone else does.

For my own part, I think a large chunk of existing requirements could potentially be reconfigured as reference material underlying the type of “comply or explain” approach deployed by regulators elsewhere. For example, the paper largely acknowledges that the rules for preparing business acquisition reports are merely an arbitrary cookbook, from which issuers regularly apply for and are granted various forms of relief. I think it’s worth considering whether to leave it entirely to issuers to decide to what extent they provide any of the BAR information, subject to prominently disclosing what they choose not to provide. After all, if investors think this leaves an unacceptable information gap in any particular case, they can draw their own conclusions on its relative significance. Even artificial investors…

The opinions expressed are solely those of the author

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