Other parts of this series:
At present, the lack of disclosure of environmental, social and governance (ESG) data by many corporations creates asymmetric information. Research from Accenture, Hermes and non-profit disclosure advocate CDP identified environmental risks with a combined potential impact of $699bn. Despite the immense value at stake, 40 percent of businesses fail to capture or report the financial impact of strong environmental performance.
The ‘greenness’ of a financial instrument is not obvious. While progress has been made in some areas, for instance, the Loan Market Association’s Green Loan framework, there is often a lack of standard criteria to judge which assets and investments are green.
Search costs are high because most companies do not report ESG data in the same way they report financial data. The dearth of ESG information makes pricing and risk decisions difficult—investors may have to extrapolate from the firm’s ESG target figure if an actual figure is not reported.
Data as a driver of sustainability
- 63% of companies have a policy to reduce emissions but only 35% have specific reduction targets
- The average company has a recycling ratio of 63% but only 29% of companies report this metric
- Between 2014 and 2019, there was a 25% increase in companies with water-efficiency policies and 34% more companies setting specific water-efficiency targets
Governments and policymakers are essential and should focus on the outcomes of their regulations
Our 2019 CEO Study on Sustainability, conducted in conjunction with the UN Global Compact, recognizes that consumers and employees are key drivers of sustainability, however, CEOs highlighted regulation as a critical requirement for accelerating progress.
Just 21 percent of CEOs believe business is playing a critical role in contributing to the Global Compact’s goals. Therefore, governments and policymakers are integral in driving further progress.
CEOs from the banking and insurance industries believe the stakeholder group that will have the greatest impact in managing sustainability over the next five years is regulators.
While the private sector has started to embrace sustainable ESG practices, new regulations are likely to be implemented in the next couple of years, requiring players to provide new indicators.
- The European Commission announced its action plan on sustainable finance in May 2018. Proposed regulation includes the establishment of a framework to facilitate sustainable investment and disclosure obligations in order to integrate ESG factors into corporations’ risk management processes. A Technical Expert Group on sustainable finance was set up to assist it, notably in the development of a unified classification.
- The UK’s Green Finance Strategy has the overarching goal of ensuring every financial decision takes the environment into account. On February 27, 2020 the Governor of the Bank of England, Mark Carney, launched the COP26 Private Finance Agenda in the lead-up to the 26th UN Climate Change Conference of the Parties in Glasgow. The preview of the strategy focused on reporting, risk management and return. The UK government expects all listed companies to be disclosing in line with the recommendations of the Task Force on Climate-related Financial Disclosures by 2022.
- Big data can be used to provide more effective environmental regulation. Rather than the existing command and control approach that often burdens companies without achieving environmental progress, Big Data can allow governments to focus on results rather than rules. For example, governments can benefit from improved sensor technology and real-time reporting to monitor greenhouse gas emissions.
Leveraging big data and AI to support the sustainable agenda
Companies facing sustainability challenges can leverage big data for tasks such as assessing environmental risks and resource optimization. Moreover, the combination of big data and advanced analytics will generate hyper-transparency of corporate activity and extra-financial performance.
Pirelli is using SAP’s big data software management system, HANA, to “accelerate data collection, processing and distribution, and make decision-support data available to the business in near-real time”. Sensors in tires generate data that allow Pirelli to more efficiently manage its inventory, resulting in fewer defective tires going to landfills.
Big data enables Pirelli to achieve its triple bottom line—which considers profit, people and the planet—by reducing waste and increasing profits.
Computers working for and with people
Trade finance processes are typically time- and labor-intensive. Therefore, they are suitable for technological disruption.
ING has used optical character recognition to increase efficiency and reduce errors by digitizing the documents and feeding analyzed and extracted, typed and handwritten data into banking systems as a full data set.
Robotic process automation (RPA) is another valuable tool. Working alongside Blue Prism, we provide RPA to accelerate processes.
“We’re not experimenting with AI, we’re really doing it.”
—Roman Regelman, Senior Executive Vice President and Head of Digital, BNY Mellon
BNY Mellon has deployed over 300 bots using RPA across the business to execute five million processes. Common use cases include clearing US Treasury bonds and classifying client inquiries. The bots are doing routine, repetitive work so staff can work with clients. Regelman describes this as “computers working with people.”
Automating repetitive tasks optimizes resources and increases employee engagement by allowing people to focus on the more interesting aspects of their jobs. Employees’ attention is diverted to creating customer value and innovative sustainability efforts.
Measuring and communicating sustainable financial performance
There are several companies offering ESG ratings to protect investors from financially material ESG risk. Sustainalytics and MCSI are market leaders and both use an analyst-based methodology.
However, Arabesque leverages big data to assess the performance and sustainability of companies worldwide. Its S-Ray tool employs algorithms that eliminate human biases. It relies on a diverse data set comprising over 200 ESG metrics and news analysis from more than 80,000 sources in 15 different languages to create the Arabesque universe, a portfolio of global, sustainable equities.
Arabesque S-Ray is designed to predict long-term financial performance. More than 7,000 of the world’s largest listed corporations are analyzed using self-learning quantitative models—the algorithms driving S-Ray learn over time as new data sources become available.
“We have built Arabesque on the two disruptors of finance, sustainability and AI, to deliver a new experience to investing.”
—Georg Kell, Chairman, The Arabesque Group, Founding Executive Director of the UN Global Compact
Measuring the right metrics
Arabesque offers four different metrics rather than one single score.
The ESG Score measures how well companies are managed. Based on the theory of financial materiality, sustainable companies will outperform competitors in the long run.
The GC Score is based on the four core principles of the UN Global Compact: human rights, labor rights, the environment and anti-corruption. Arabesque S-ray quantifies these principles, allowing assessment of companies for increased reputational risk.
The Temperature Score evaluates a company’s contribution to the climate crisis through greenhouse gas emissions. Companies receive a near-term and a long-term temperature score reflecting the temperature pathways they are on, given their current behavior—only 20 percent are expected to remain below the 1.5°C growth pathway by 2050.
Clearly, to achieve the UN Global Compact’s ambitious but necessary Sustainable Development Goals, companies and governments must ensure data is widely reported.
Using this data, technologies—including machine learning, artificial intelligence and blockchain—must be leveraged to see the full potential of sustainable finance and ESG investing. This will lead to innovation and the fostering of new green products, which I’ll discuss in my next article.
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