AI in ESG Analysis: How AI is Transforming the Way We Assess Environmental, Social, and Governance Factors

Environmental, social, and governance (ESG) factors are becoming increasingly important to investors, as they can have a significant impact on a company's long-term performance. However, assessing ESG factors can be complex and time-consuming, especially for large companies with global operations.

Artificial intelligence (AI) is transforming how we assess ESG factors by automating many manual tasks, such as data collection, analysis, and reporting. AI can also help to identify patterns and trends that would be difficult to detect manually, and it can be used to develop predictive models to assess future ESG risks and opportunities.

Here are some of the ways AI is being used in ESG analysis:

• Data collection: ESG data collection from company filings has traditionally been a manual exercise, due to the unstructured manner in which the data is presented. Now, AI tools are available to extract data in an automated manner from all kinds of sources like PDFs or websites. Decimal Point Analytics has developed fully an automated tool that extracts quantitative data, plus qualitative information, with an amazing degree of accuracy.

• Data analysis: Harnessing the power of technology, extensive ESG datasets can be scrutinized to unveil patterns and trends that would be challenging to discern manually. For example, AI can be used to identify companies with a high risk of environmental litigation or companies with poor labor practices.

• Reporting: Streamlining the ESG reporting process, automation tools can significantly streamline operations, saving companies valuable time and resources. Moreover, these tools can generate tailored ESG reports for diverse stakeholders, including investors, regulators, and customers.

• Predictive modeling: AI can be used to develop predictive models to assess future ESG risks and opportunities. For example, AI can be used to predict a company's carbon emissions or to identify companies that are at risk of supply chain disruptions.

Benefits of using AI in ESG analysis:

• Improved efficiency and accuracy: AI can automate many of the manual tasks involved in ESG analysis, freeing up analysts to focus on more strategic tasks. AI can also help to improve the accuracy of ESG assessments by reducing the risk of human error.
• Deeper insights: Advanced analytics can aid in identifying patterns and trends in ESG data that would be challenging to detect manually. This can lead to a more profound understanding of a company's ESG performance and risks.
• Better decision-making: AI can help investors and other stakeholders to make more informed decisions about ESG investments and corporate governance. For example, AI can be used to identify companies that are well-positioned to benefit from the transition to a low-carbon economy.

Decimal Point Analytics (DPA) offers a comprehensive suite of ESG solutions, including:

• Green Invest Pulse (GIP): This is DPA’s TCFD reporting tool for funds. It is a web-based tool that calculate a portfolio’s emission metrics like Carbon Footprint, Financed Emissions and WACI (weighted average carbon intensity). It also reports the share of portfolio aligned to Net Zero. The fund can use this tool for generated TCFD reports, and also to track progress against Net Zero targets.
• Decimal News Pulse (DNP): DNP provides ESG Assessment of companies based on news analytics. DNP is tailored to each client’s holdings, and provides investors with a personalized feed of ESG news on their portfolios along with the ESG assessment based on DPA’s proprietary assessment framework. It is built on DPA’s news monitoring platform that tracks news on a real time basis. Then we deploy AI-ML scripts to categories news into various ESG Key Issues, attach polarity and scale to the news and then arrive at the ESG assessment for a company. The tool then rolls up the assessment of portfolio holdings to come up with an ESG Assessment at fund level.
• ESG for PE Funds: PE funds typically have portfolios of unlisted companies that are not in the habit of declaring ESG information. DPA has a comprehensive data gathering solution for PE funds, offered as a managed service. We have sector aligned templates that are used to collect data from portfolio companies. This data is then warehoused, where it is also processed and standardized. The output is presented in reportable format via online dashboards. Funds can simply export out relevant charts and tables for reporting to their LPs.
• ESG Consulting: DPA also offers ESG consulting services to help funds develop and implement ESG strategies. DPA's consultants can help asset managers identify their ESG goals, develop internal ESG frameworks, and track and report the ESG performance of their portfolios. We have also ventured into corporate consulting, helping companies with EU Taxonomy reporting, and ESG data collection.

DPA's ESG solutions are used by a variety of clients, including asset managers, pension funds, and corporations.

In conclusion, the integration of artificial intelligence (AI) into Environmental, Social, and Governance (ESG) analysis is revolutionizing the way we evaluate companies' sustainability and ethical practices. This transformation is driven by AI's ability to automate data collection, enhance data analysis, streamline reporting, and develop predictive models for future ESG risks and opportunities. The benefits of AI in ESG analysis are manifold, ranging from improved efficiency and accuracy to deeper insights and better decision-making.

Contact us today, and let's revolutionize ESG analysis through AI-driven solutions.