Dynamic ESG Materiality Appraisal

The specific environments that two companies operate in are heterogeneous even in the same industry sector and same geographic region. An understanding of these specifics is critical for an assessment of the ESG performance of a company.

Further, ESG material aspects and factors are becoming increasingly interconnected as business models, market conditions, and technological envelopes evolve. The assessment of a company’s ESG performance through the lens of materiality needs to reflect this evolution.

Hence, it is critical to identify and prioritize ESG factors that become material on a dynamic basis. Materiality appraisal, likewise, needs to adapt to the unique, evolving context, while providing a granular grasp of the signals and triggers that may lead to unsuspected risks.

Currently, the major barrier to this end is the limited capacity to access and process timely information that is fragmented, unstructured, and heterogeneous. This is where Big Data and AI can shine.

These technologies can be applied to harness a wide variety of data sources, based on models’ ability to identify relevant ESG information and capture underlying relationships, especially with regards to financial materiality as well as risk management.

In particular, Natural Language Processing (NLP)11, a subset of AI techniques, can be used to analyze data feeds (i.e., news, tweets, financial data, etc.) in real-time and to forecast aspects that may become material for a company in a given context, taking into account static and slowly evolving information.

Crucially, AI can perform such an assessment in a way that human analysts cannot, in terms of speed, quantity, granularity, and consistency.

To see how we at Vogosen approaches this subject, please see our White Paper. You can also contact us and schedule a meeting to discuss your specific needs.