Reindustrialization and ESG do not have to be incompatible. AI can enable you to accomplish both. This article only focuses on the “Social” or S part of the ESG.
The ESG movement has a strong emphasis on environment. ESG stands for Environment, Social, and (corporate) Governance.
This whole area is so new that when CNBC interviewed Jonathan Bailey, Head of ESG Investment at Neuberger Berman, the CNBC analyst commented that Bailey’s position would not have existed a year ago. (interview aired on 08/24/2020)
Clearly, getting the E part is easier. It has 40 years of advocacy by people like Al Gore, well-defined global standards, and tradable products such as Carbon Credits.
But what about S in ESG? In an era marked with Black Lives Matter protests, rising nationalism across the world, increasing global tensions, and higher awareness about these issues – how to bring S into ESG without feeling the guilt of insincerity?
“Guilt of insincerity” … what’s that?
Claiming to start an ESG focused fund is easy. Defining the standards in accordance with which the fund will operate is much harder. What makes it extremely difficult is that you must deliver reasonable returns to the shareholders.
To posit that great returns will only come from companies with the highest ESG performance is still unproven. To claim that firms with higher standards deliver great value, is also empirically unverified.
But what is provable is that if a strong movement exists in the investment world – a movement that can help transition investment from assets that exhibit low ethical standards to those that show strong ESG traits, the needle will move. The obvious question is: what are the standards for “S” – social concerns?
Without having such standards – fund managers are trapped in a debate that precedes Al Gore’s save the planet campaign by a few thousand years. The question of what is good for society is as old as the human civilization.
If ESG fund managers pay lip service to social concerns, they are being insincere to the cause. If they don’t do anything – then it is not much of ESG. If they create goals that are too tight, it may reduce the breathing room for delivering returns. This is the dilemma and a source of guilt.
Without more elaborate frameworks, asset managers tend to lean upon some obvious areas such as diversity, human rights, consumer protection, and animal welfare.
The United Nations provides further guidance on the sustainability development agenda by establishing 17 goals. But these are cookie cutter approaches. A fund needs a competitive advantage.
While these standards are clear, the following three problems become a source of concern for investment managers:
The problem of variable inclusion: What constitutes as social concern? Which social value driver variables to include and which to exclude? For example, would running clinical tests on animals be considered as a concern about animal welfare? Would running clinical trials in Africa – where populations may not really understand what they are getting into – constitute as human rights violations? Would capturing personal information of users be considered a human rights issue?
The problem of measurement: Once variables are defined – questions arise about how to measure the social impact? Would the measurement be against an absolute standard or would there be some flexibility?
The problem of definition: This is close to the first problem – but it captures a different perspective. While the first addresses which variables to include, this problem addresses that once a decision is made to include a variable, how do you define that variable. For example, if you have selected weapons manufacturing as a (negative) social value driver variable, does all weapons manufacturing violate human rights or only selling weapons to countries that violate human rights constitutes as bad? It is questions as that which help us define the variables.
The above three considerations impact the real problem faced by fund managers: delivering returns above the expected cost of capital.
This means that answers to the above should somehow be linked with returns – and that means answering various strategy and goals of fund questions. For example: Is the fund operating with the goal of behavior modification for a target firm – or is the goal to reprimand offenders? Does the firm establish internal goals or abide by external goals? And most fundamentally: how does the ESG-enabled strategy translate into a competitive advantage?
The answer to the above question lies with artificial intelligence.
How can AI help?
Artificial Intelligence provides the most comprehensive way to implement “S” and “G”. In this article I will only address S – as G will be discussed in a separate article.
I believe that every firm needs its own internal standards and the ability to analyze target investments. This gives maximum strategic flexibility and can help firms establish standards that can be unique.
A system for achieving that is based upon 5 Social Value Discovery drivers – which are followed by a CRISP-DM type model development and deployment process (Figure 1).The first four steps are what helps define the overall social value creation model.
The fifth step – Return Linking – establishes a hot link between social value drivers and returns to enable dynamic fund management. The word dynamic refers to having the ability to evaluate the link between social value creation and returns. This strategy can work for both passive and active investment styles.
The outcome of the first five steps establishes the data requirements and scopes out the preprocessing requirements – keeping in mind that your data and algorithms can themselves be a source of bias.
You must avoid these mistakes
To secure solid returns and keep your “social” a strong contributor of value – you must avoid the following five mistakes:
Do not go with a cookie cutter approach. Your investors will be able to smell the insincerity associated with the cookie cutter approach. Make social value creation a competitive advantage for your firm. This means you must have a framework.
Do not leave the 5th Step as a loose end. Make sure to link returns with your social value drivers – and do so at a lower level in fundamentals-based value creation. Do not use indefensible models of social value creation. Make sure to have clear and defensible framework which clearly defines what value creation means.
Do not proceed without properly understanding the data and algorithms: Your data and algorithms can be a source of bias. You must have a clear strategy on how to deal with bias.
Make sure to test your strategies: Make sure that you have a way for testing your strategies. And this opens a new can of worms. Your model must work in active and live settings – and making it work is not easy. Good investment strategies often come to die on the altars of overfitting.
Do not ignore that your target investments can use AI for good and bad: One of your critical evaluations need to be whether your target investments (firms) are using AI to create or destroy social value. These days AI is the top agenda item for most firms – and they can use it for good or for bad – and your knowledge of that can make all the difference.
Next Steps
Based upon the above, here are the five steps to put a solid S in your ESG:
1. Understand your strategy; identify your social value drivers, measurements, and definitions.
2. Establish a hot link with returns. Study what that means. Test, test, and test. Do not use a cookie cutter approach.
3. Data is expensive. Do not just get all the data. Get data that is meaningful for your framework. Establish best practices for data management and preprocessing.
4. Establish models – and you would need multiple – to work together to identify and manage value creation for you. This means to get a synchronized value-creation framework implemented.
5. Things are never constant. Know and proactively manage when change happens. It can happen when the underlying distributions have changed – or the set of features you used to define the social context have been altered.
You mean well. But this is investment business and having goal excellence is one thing – making it work another. Social value creation is important and while we cannot change everything – as Dylan Thomas said, we must “rage against the dying of the light”