“ESG,” stands for environmental, social, and corporate governance. The term was first coined in 2005, although similar initiatives can be traced all the way back to the 17th Century. To put it succinctly, it’s the idea that corporations don’t exist in a vacuum.
Corporations create ripples in the world around them. Their processes have an effect on the ecology, society, communities, and people. Once we are aware of this fact, we can take action to minimize harmful influences as well as to promote positive change around us.
ESG is commonly used to refer to ESG scores, an evaluation of a corporation’s conscientiousness in regards to their social and climate effects. It’s a score compiled from data collected from indicators of the company’s processes as well as their outcomes.
ESG scores fall under the definition of intangible assets and are actively used by investors to measure a company’s value in terms of its social responsibility. Think of it as a sort of “social credit score”.
This kind of investment strategy is known as ESG investing. And while putting your money where your values are isn’t a new practice, the way how ESG is measured definitively is. It’s one thing to hold values, and quite another to use indicators to show that you are acting following those values.
Investment in ESGs has quickly become a very important asset class. By 2018 sustainable investments reached over $30 trillion, a 34% increase in contrast to 2016. The message couldn’t be more clear: Investors are seeing value in socially responsible corporations.
The Problem with ESG Measurements
Unfortunately, to say that ESG ratings have a bad reputation would be an understatement. You’ve probably heard about cases like Boohoo’s, the fashion retail overnight phenomenon. The company received overwhelming positive ESG scores only to later be accused of worker abuse.
In fact, they were formally accused of enforcing modern slavery, underpaying their workers in the UK, and not providing adequate biosecurity measures to protect them from COVID-19. That’s one example out of many, but they all point to the same conclusion: ESG measurements can be extremely unreliable.
One study by the University of Zurich found that the correlation between the scores of 5 different ESG rating agencies was 0.61. That’s not a promising result. In fact, the error margin is big enough that 2 different agencies can have vastly different assessments of the same company.
The researchers proposed 2 hypotheses to explain such a gap. First, the fact that each rating agency is measuring a different number of indicators to calculate their score. And second, that ESG rating agencies base their evaluations on data provided by the companies.
At worst, this means that companies can cherry-pick which data to hand over for evaluation. At best, even the most honest of companies can unwillingly share biased data that was collected with an unreliable gathering method.
This creates 2 very important problems for investors. First, establishing comparisons between companies becomes nigh impossible without standardization across ratings, which in turn means that ESG scores lose their value as an assessment tool.
Secondly, investors who rely on these scores to make decisions may later find that the scores don’t align with the company’s ethos. However, and until we can find better ways to approach ESG scoring, traditional assessments are slightly more reassuring than a crystal ball.
AI and Qualitative Assessments
Perhaps one of the biggest hurdles for improving ESG measurements is the fact that a lot of the information is qualitative in nature. News stories, social network discourse, and up-to-date reports are all sources of third-party information that can give an insight into the effect the company is having.
Unfortunately, the process of manually gathering and processing qualitative data is both time-consuming and error-prone. But thanks to AI and, more specifically, Natural Language Processing, it’s possible to speed up this process and automatically generate reports in real time.
An AI can be trained to identify keywords and phrases covering different topics from social perception to environmental consciousness and community integration. This is useful for both rating agencies and managers who want to incorporate ESG as a Key Performance Indicator.
Thanks to speech-recognition videos can also be scrutinized. This is very useful for companies that are part of a news cycle. Consider that television tends to have a broader reach than other forms of media.
This means that AI can bolster faster and more integral qualitative analysis that can be generated in real time. For managers and companies concerned with their ESG, this can help them track how their policies are affecting the score as they are being implemented.
IoT and ESGs
Data gathering has always been a pain in the neck. Ask any data scientist what their least favorite part of their job is and they will answer either data gathering or data cleaning (or both). Thankfully, the Internet of Things (IoT) is helping us in ways we couldn’t have imagined.
ESG data is scattered across various departments, sites, and geographical regions. On top of that, most corporations don’t have protocols for data collection, so the datasets are prone to errors.
Thanks to intelligent devices, data collection can be automated and centralized. Corporations can have one data engineer handling all the processes from anywhere on the plate, and as long as all the connected devices are calibrated and maintained, data can be collected reliably.
Just like AIs, IoT also allows for a certain level of real-time adjustments. Since measurements are being taken in real time, changes can be made as soon as certain thresholds are reached. You don’t have to wait until a post-mortem report to make the necessary changes.
Building Trust
The relationship between corporations and investors is built on trust. Investors will only provide as much capital as they are willing to risk. In this sense, information is a bridge, a way to form strong bonds between both parties.
Investors will feel safer knowing that ESG scores are based on reliable methods. Technology is predictable, it can be audited, it’s safe, and it helps us reduce human error. Obviously, the human eye and our experience will never be substituted by machines. Rather, it’s complemented by it.
With better ESG indicators, not only can investors make informed choices but managers and corporations can use this information to double down on their values and help create a better world.
