VOGOSEN

AI-Powered ESG Opportunity Radar

In ESG, investors that can identify opportunities before they materialize to reap the most rewards. AI-Powered ESG Opportunity Radar leverages Big-Data at multiple levels to achieve real-time warning and forecasts on material ESG issues.
Published by Jiulin Teng on 13 Nov 2021 · Keywords: aibig-dataesgopportunity-radarvogosen
Opportunities and risks often come hand in hand. In ESG, investors that can identify opportunities before they materialize to reap the most rewards.
Decision makers who wish to be one step ahead of the competition need an information system that can help them ingest, process, and analyze large amounts of data from diverse sources.
The ESG Opportunity Radar is the most Big-Data-driven aspect of AI in ESG in the sense that three levels of data in multiple formats from the broadest set of sources are leveraged simultaneously, each in its own fashion.

Macro-Level ESG Opportunity Radar

At the Macro level, investors can leverage a setup similar to the Dynamic ESG Materiality Appraisal, which we discuss in detail in another section. The difference is that here we collect data with industry and geography focuses and run them with other macro data through a forecasting AI that is aimed to identify non-obvious patterns that human analysts cannot.

Meso-Level ESG Opportunity Radar

At the Meso level, investors can further delve into company groups. These are companies in the same industry with similar geographic presence (e.g. Coca Cola and PepsiCo) that share a similar ESG opportunity profile. This system can be set up similar to the ESG Sensor.

Micro-Level ESG Opportunity Radar

At the Micro level, investors can implement the most elaborate AI system in ESG. Single companies are continually monitored, and detailed data that can inform the system of the company’s R&D, business model, supply chain, marketing, and various other aspects of their operations are taken into account.

Next Steps

To read more on this topic, download our White Paper on AI in ESG.
You can also contact us to schedule a meeting to discuss a la carte implementation of the ESG Opportunity Radar for you.
Photo of Jiulin Teng

Jiulin Teng

Jiulin Teng has deep understanding of key topics in management science and new technologies. He also has broad knowledge in macroeconomics, business policy, and software engineering.
Upon completing his dissertation on the application of game theory in competitive strategy, Jiulin Teng worked as a consultant at McKinsey & Company (Belgium). More recently, he has launched and participated in a number of startups in blockchain, IT, and AI. He is a proficient database architect and is a full-stack developer with good command of modern programming languages. He has also taken an interest in Natural Language Processing.
Jiulin Teng holds a PhD in Strategic Management and Business Policy from HEC Paris (France). He also has a Master’s degree in Bioentrepreneurship from Karolinska Institute (Sweden) and a Bachelor’s degree in Biological Sciences from Nankai University (China).