Nowadays, rational investors are challenged by inaccuracies of ESG-data, where data is unstructured and subject to many data gaps. In a world transforming into being more sustainable, the challenge of business leaders is to understand how to create meaningful Key Performance Indicators and select adequate frameworks for ESG reporting. This is where artificial intelligence comes in. AI will give these leaders a vital tool for implementing next-generation KPIs and enabling them to illustrate how they want to create long-term value through trust.
Advanced analytics and AI can change the way we understand the data by creating trust, integrity, consistency and openness. Which at the moment is a major issue related to ESG-data according to Boillet (2020) author at EY. This trust is vital for companies because people’s trust in the firm will impact their position towards the company. These people can be in the first instance investors. But also suppliers, customers, employees and many other stakeholders.
Currently, companies and capital markets already use numerous systems to demonstrate a tangible relationship connecting behavior that instills trust and delivering the financial results that are wished. This relation between trust and financial performance also concerns investors and asset managers; which at the moment majorly focus on traditional financial metrics. Platforms such as Arabesque AI are allowing investors to customize and automate the ESG-data up to their requirements. To understand how these platforms really make a difference, below are listed a couple of capabilities that AI brings to ESG:
- AI offers real-time information that traditional sources simply cannot compete with.
- The amount of data collected through AI will evolve over the years, as the adoption rate and the adeptness will increase.
- AI makes it possible to analyze and forecast risks related to human rights issues among suppliers way faster, which makes it possible to identify risks sooner and increase the accuracy of the ‘Social’ and ‘Governance’ metrics in ESG.
- AI is able to aggregate information related to ESG which is at the moment provided in unstructured and inconsistent reports. This will enable decision-makers to make accurate comparisons and key performance indicators.
- Resolve the issue related to data gaps between conventional ESG rating agencies.
To make this analysis nuanced, note that AI brings also a large number of challenges, including its cost and its struggle to identify unreliable sources in accordance with fake news. But I want to let this part open for debate.
References:
Arabesque (2021) Arabesque AI. Retrieved from https://www.arabesque.com/ai/
Boillet, J. (2020) How AI will enable a better understanding of long-term value. EY. Retrieved from https://www.ey.com/en_us/assurance/how-ai-will-enable-a-better-understanding-of-long-term-value.
Boillet, J. and Cobey, C. (2021) How do you teach AI the value of trust? EY. Retrieved from https://www.ey.com/en_nl/digital/how-do-you-teach-ai-the-value-of-trust.
