11 Jan AI and ESG: the growing trend in climate reports
Applying AI to ESG reporting and assessments is on the rise, and regulators are struggling to maintain pace with this growth. Lenders must focus on the new governance risks that could potentially be difficult to identify.
AI is fast becoming a popular term in ESG reporting, and as disclosure rules evolve, businesses and their associated partners are exploring alternative data sources and how to use AI technology to enhance financial reporting.
For the financial industry, AI’s main feature is its efficiency. Machine Learning can determine trends in large datasets. Natural language processing (NLP) provides computers with the ability to recognise and respond to textual and voice data. These two solutions combined can automate the long ESG assessment process. Alternative data incorporates measurements from other areas, like satellite imagery, supporting the structure of climate data and enhancing climate risk estimations.
Data-focused financial organisations are harnessing the potential of these resources to enhance their assessment of corporate sustainability credentials for investment and lending decisions. With new technology solutions, however, come new challenges, and users must recognise the features and potential of AI-powered ESG reporting.
Enhanced ESG Ratings
AI-combined with alternative data, could enhance the work done by rating agencies that assess and classify businesses based on their ESG credentials. Marie Briere, head of investor intelligence and academic partnerships at Amundi Institute, explains that AI is not a revolution but a way to create a more sophisticated analytical methodology. As AI tools become more widely available, agencies and financial services businesses believe it will become easier to assess more companies more quickly.
More knowledge is power
In ESG reporting, data blind spots represent a weakness for companies and investors. Having access to AI solutions can present a competitive advantage. Any technology that strengthens and accelerates data extraction is beneficial.
AI will also widen the scope of raw data used in ESG assessments performed by investors. The main concern, however, that many industry analysts point out is the potential risk that companies and investors rushing to meet disclosure regulations adopt a technology they don’t understand.
AI and alt data sourcing technologies are progressing so fast that regulators are struggling to maintain pace. As a result, there are potential governance risks that industry specialists have little visibility over. When harnessing a new and innovative solution to gather data, it’s easy to believe that measurements will be completely accurate, but in reality, the margin of error can be significant.
The governance risk is making lenders keep an eye on how AI and alternative data are growing within core industries. Yannick Ouaknine, head of sustainability research at Societe Generale, sums it up perfectly, explaining that we require a holistic view of the consequences of using this technology, its limits and risks, and what the integration of these solutions into business processes means.
Users of AI technologies are responsible for verifying and ensuring any possible bias and controlling risk. AI users must also consider that these new solutions are supporting tools and not a replacement for the overall ESG assessment and decision of an investor.
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