James Hawley is Professor of Management, School of Economics and Business, and Senior Research Fellow, Elfenworks Center for Responsible Business at Saint Mary College of California. He is also Head, ESG Research at TruValue Labs, San Francisco, California, which provides advanced analytics to create sustainability metrics using real-time ESG data. He is the author of two books, the first on international banks and the global monetary system, and also of The Rise of Fiduciary Capitalism (2001).

Christopher P. Skroupa: Is the space for sustainability, corporate responsibility and environmental, social, governance ripe for disruption?

James Hawley: There has been a disruption in the way we handle information. A pivotal development has emerged in transparency and information timing throughout all fields. A voluminous number of initiatives has risen: there is environmental, social and governance (ESG), there is responsible and sustainable investment (RSI), corporate social responsibility, corporate shared value, impact investing, and a slew of others. Although distinct in some useage, there is much overlap in meaning. These are fundamentally information dependent categories. From both the corporate side and the investor side, a plethora of information can be gained from the non-investor stakeholder, from news and social media, and from governmental and other sources. Most critical information is now web based.

The emergence of big data and big data analytics has had a paramount impact. Social media platforms, such as Twitter and Facebook, make big data easily minable to source  what the crowd is thinking. However, this is not the most useful source for corporate social responsibility (CSR) or sustainable and impact investing (SRI). It would be more useful to throw the net very wide throughout the gamut of the web and automate the analytics for current trends based on up-to-the-second information.

This is possible thanks to cognitive computing, a key component of which is based on natural language processing (NLP) algorithms. This enables the computer to process text just as a human would. It is not a question of simply positive or negative sentiment, but it compiles semantics contextually to understand the nature and subtle meaning of language. This creates a sentiment index which captures many shades of grey, rather than just a Facebook thumbs up or thumbs down. Another element to cognitive computing is machine learning. This provides the ability of the computer to learn autonomously. The sidebars are set by humans, and the algorithms process and analyze with these boundaries. The more NLP runs it progressively gets better, more accurate and more nuanced.  A leap within cognitive computing is artificial intelligence. This provides the capability to assemble quantified data from qualitative analysis to make probabilistic predictions, to locate patterns, and the like. Although the element of artificial intelligence isn’t quite there yet, progress is advancing rapidly. The scalability of real time data contributes to this progression. Once the initial investment is made, it is quite simple and inexpensive to add a multitude of additional sources and multiple languages. Human capabilities cannot compete in terms of time and scope, however, artificial intelligence can not replace human cognition. Yet it will replace a lot of essential drudge work so that humans can do what we are best at—thinking critically.

Skroupa: Who is leveraging the disruptive technologies capabilities?

Hawley: I wear two hats, one academic and one commercial, as the head of research of TruValue Labs. However, these two sides are aligned in a profound way. Nobody aside from TruValue Labs is explicitly leveraging these capabilities for a commercial purpose in the ESG and responsible investment space, as far as I know. It is my understanding, however that some developments have occurred in-house at some of the bigger banks or investment firms like BlackRock or CitiGroup. Currently these technologies are proprietary and have not been applied to sustainability issues, ESG or corporate social responsibility. Truvalue Labs is using that full blown piece of technology. Another aspect of these disruptive technologies, is the ability to monitor critical stakeholders. From a corporate point of view, you want to follow what those stakeholders are saying and doing, or what is being said about them. There are also stakeholders which the firm might not see as critical stakeholders. You probably want to monitor these as well. This is old school stuff, often talked about as “environmental scanning”, not around the physical environment but just the environment in which the firm is living. Any way you can automate that is to your benefit. These technologies will be more prevalently used as they become available and more cost effective.

Skroupa: How can big data analytics be applied to financial technologies? Why is this happening, what are the potential risks involved in the ESG, responsible investing, and social investing spaces? What’s driving this change?

Hawley: These financial technologies, labeled as “fintech,” have been applied to a wide spectrum of the financial sphere. The term of fintech is quite vague, it can incorporate everything from automating accounting to very complex algorithms for automatic flash trading. Fintech also can mean an array of things for the ESG responsible investment space. The use of big data analytics have driven this change.

If there are alpha returns to be found, there is initial evidence that it can be found in the  sustainable investment space. But we should keep in mind that “sustainable” investment definitions do vary a lot. These algorithms can source the backlog of very high quality academic literature, theoretical and empirical, to focus on specific elements and materiality of CSR and SRI. Investment funds have the potential of using this technology to seek alpha efficiently. Of course, like all alpha, once alpha is found and publicized, it will regress to the mean in a relatively short period of time to create a new standard. This demonstrates that advancing the sustainability idea is actually a better way to derive beta. By definition beta then will shift the market as a whole. The crux of this issue is creating a market with visible benefits in regard to sustainable investment about environmental and corporate governance. This would result in a less volatile market with a focus on firms that mitigate their negative externalities. Negative externalities by definition create a suboptimal economy; companies and investors should endeavor to eliminate this, even if for a specific firm a negative externality can be profitable. This would result in a more productive market which does less harm. The ability to act on real-time information is a crucial innovation for investors. These capabilities can be utilized to assess short-term strategies, to build portfolios and to focus on marketed efficiencies found in long term strategies. We invest in companies that have these long-term growth potentials which result in an overall sustainable strategy and enterprise. Technology simply facilitates this process, it lowers the transaction cost while it increases both scale and scope. Corporates have an interest in these technologies to constantly monitor their own reputation and that of their competitors. They can monitor the thoughts of investors and key stakeholders.

I wish I had a complete answer in regard to the risks involved. A potential risk would be to implement these capabilities without human interpretation, you are just driven by the data without any significance of meaning. However, Artificial Intelligence can be a partial substitute for that, when done right.  A question to consider: the dynamic role of analysts, they will see their jobs shift so they become more analysts, less researchers. This is due to big data driven research that allows comprehensive analysis. Their jobs will change, but will they ultimately be displaced? I don’t know but I doubt it. In my mind, the jury is still out but the real question is both degree and what the work of future analyst will actually be. Obviously bad algorithms create bad data, garbage in garbage out, by definition, garbage interpretation results will pose a risk. Technology always needs oversight.

Skroupa: What do these technologies imply about future integrated reporting trends for corporates?

Hawley: I think integrated reporting can be done better. What we are seeing now is a really interesting movement globally. In the United States we’ve been somewhat of a laggard, but we are starting to catch up. There has been a movement toward integrating stand-alone CSR reports into the annual report. That takes many forms, and as they stand now, integrated reports have a lot further to go. Part of the problem with the annual report is the same problem with the integrated report, they are annual. This yearly status check does not keep up with the constant change that data develops. The financial updates in a traditional annual report need to be updated in a relatively real-time way, currently the closest is done with quarterly U.S. federal filings and for those firms still playing the quarterly earnings projections game. For example, on corporate websites, the annual integrated report should be posted with updates that are algorithmically driven. If you’re not going to do it, someone else will. Annual reports become out of date as rapidly as they are published. Publicly accessible reported information and other material is incorporated into the so called “non-financial” part of the integrated report. That information is available increasingly in close to real time and the idea of the report needs to catch up. The Sustainability Accounting Standards Board (SASB) states that the essence of an integrated report should already be incorporated into the 10-K. For example, last month the Harvard Investment Fund declared that they would not address firms individually, but rather request the information to be reported in the company’s 10-K, so it is fully accessible to others as well. Some of that can and should be extended to be done on a real time basis.