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How Data Enables Sustainable Finance

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Governments around the world have committed to combatting climate change. Legislation is being introduced to target scope 1, 2 and 3 emissions, covering carbon emissions from direct business activities all the way to the most distant link in the supply chain.

As a result, businesses are increasingly concerned with ESG – monitoring and measuring their contribution to environmental and societal challenges. Investors are diversifying their portfolios through ESG investing, putting their money towards businesses that score well against environmental, social and governance criteria.

But banks are also invested in the transition towards a green economy, and now offer “green loans” or other forms of sustainable financing to encourage projects that seem environmentally progressive. This is another source of funding in the green building space, where the massive contribution of buildings to global greenhouse gas emissions has been a headline for many years (buildings still contribute around 40% of global carbon emissions). As a result, according to the World Economic Forum, green finance will be crucial in channelling investment to the growing number of young technology firms that are driving the transition to a sustainable economy:

We strongly believe that sustainable finance, combined with technological innovation and digitalization in banking, will be instrumental to sustainable innovation and growth and the transition to a less carbon-intensive economy.[1]

Technology will of course be central to any attempt at preventing or reversing global warming, and IoT in particular represents a chance for new business models and new operational processes to increase efficiency. It will also drive renewable energy adoption in areas that were previously monopolised by fossil fuels. It is therefore worth asking how sustainable finance can drive technology adoption as well as sustainability.

First of all in order to accurately assess the ESG credentials of a company, investors need access to reliable, high-quality data. There are increasing numbers of accreditation bodies and data providers offering to evaluate and score the ESG profile of companies (Sustainalytics, BREEAM and so on). But as an article in the Financial Timespoints out, there is still a wide variation in output from different assessors: the article notes that Tesla has been rated top by one firm, bottom by another, and middling by a third.[2]

This highlights the second and related point: that the great challenge for investors is to sift all this data and arrive at meaningful insight. Data analysis will be crucial here. Artificial intelligence (AI) and machine learning (ML) are already being used to a limited extent, along with natural language processing, to generate and understand ESG data. Over time, as the technology becomes more sophisticated, AI will help in sectors where data sets are often at first incompatible. It will also help to reduce the cost and time spent searching for information amidst a vast amount of unstructured data. Just as AI enables predictive maintenance in buildings, it will also, according to the WEF, enable predictive insights into sustainable investing.

Financial institutions will continue to create innovative financing models, and this will only increase as individuals become more aware of the importance of sustainable consumption on the environment and on society. In the meanwhile, the increasing availability of reliable data will help banks and other financial institutions advise clients on how to invest in line with their individual preferences.

[1] https://www.weforum.org/agenda/2020/11/sustainable-digital-finance-low-carbon-economy/

[2] https://www.ft.com/content/2e49171b-a018-3c3b-b66b-81fd7a170ab5

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