The Need to Make Data Endogenous Challenges the Traditional Professions
David C. Donald – The Chinese University of Hong Kong
-- This has happened before, decades ago, and it has little to do with privacy. In the early 1970s when securities exchanges could no longer manage increasing volumes of transfers, policymakers decided to give central depositories ownership of all securities and control over the data regarding ownership of those securities. Ownership information was made financial system endogenous and a new era of transactional efficiency through data processing was born. Since then, both investors and securities issuers have tried to wrest back control of their own data, but have failed. Services based on that data – referred to as “corporate action services” – are still sold to them so intermediaries can profit on the inability of owners and issuers to otherwise exercise their basic rights and duties.
What happened at the core of the financial market in the creation of this “indirect holding system” for securities settlement is similar to what is now occurring in the burgeoning data services enabling efficient management of information from marketing to law. In the field referred to as legaltech, a typical provider of data analytics for pre-trial discovery reminds customers that organizing the data for analysis is one of the hardest parts of the job, but if law firms sign up for their platform managing all internal data, the analytical services will be available at a moment’s notice.
Such efficient processing of data comes from making it system endogenous. If the data service controls a client’s data, the service can organize, store and process it in ways that are amenable to undertaking analysis more efficiently. However, this means a transfer of some level of control over that data from owner to analyst. In the financial industry, it essentially meant a division of ownership between registered (the intermediary) and beneficial (the investor) ownership of the securities and the data they contain. Once control has been transferred and the system is up and running providing a service on which market participants rely, a reversal is next to impossible.
So, with the same type of data absorption that has revolutionized securities settlement entering all aspects of business, as well as law, medicine and any other activity where a value proposition can be made, what will endogeneity look like? Essentially, archive, staffing, work product and accounting data will be aggregated and become available for analysis and this would be tied in with external resources and data necessary for the generation of services. The sum of data aggregated falls into categories ranging from completely and unproblematically public (laws and regulations) to information that traditionally has been exploited rather secretly (contracts or solutions designed for previous clients and used in advising another) to outright confidential or privileged information (information about a specific client, its business or its assets).
Unlike when shareholder and bondholder data was transferred to depositories in the 1970s, many jurisdictions now at least have the concept of “private data” and some rules regarding its protection. Moreover, professions like law and medicine have their own, rather old and well-established, rules for dealing with information about and received from their clients and patients. These rules on the protection of information will lead to a major point of stress in the coevolution of the professions and the new data services being generated to make them more efficient. On the one hand is transfer of control over the data to a service that can aggregate, categorize and exploit this data to offer cheaper and probably better services, and on the other are the rules for the collection and processing of that information considered “private”, “confidential”, “proprietary” or “privileged” as coming from clients or patients.
In the still-dominant fashion of industry, age-old rules on protection of private data will be questioned as standing in the way of innovation. Newer data protection rules will be subjected to cost benefit analyses to justify their adoption. A coalition of conservative professionals and newer advocates of data privacy could contest the use of data science in the professions. The real force guiding how this data will be used is the profit incentive: in many areas of law, at least, it appears that data analytics will soon be able to perform tasks better and cheaper than lawyers. This is very good news for law firm partners, who in the past have leveraged their revenue through use of paralegals and other less expensive forms of staffing. Automation would be superior to such down-streaming in many ways. However, once the organization of law starts to shift toward data analytics platforms, network effects will take hold as they do for all such platforms. At this point, bigger will definitely be better and will continue to be preferred even if monopoly power eventually leads to overall distortions of the justice system.
The future development in this area could thus revolve around endogeneity of data. Data analytics models will naturally seek to bring data within their control and organization in order to achieve an efficient product at a manageable cost. Traditional notions of data – from client or patient privilege to fiduciary confidentiality – will stand in the way. When the profit incentive moves professionals to seek a loosening of data protection in order to provide more, better and cheaper services, a transition will begin toward platform business with strong network effects. Once this reaches the tipping point at which network benefits make use of such model a necessity, the professions as we have conceived them historically will disappear as economically significant entities. Professional bodies should start planning their response to this process.