In a recent enlightening webinar, the world of Environmental, Social, and Governance (ESG) analysis was brought to the forefront, emphasizing the transformative potential of Artificial Intelligence (AI). Here's a detailed look at the key takeaways from the session.

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The Lecturer

Webinar presentation and lecture was delivered by Qayyum Rajan, also known as Q, the visionary founder and CEO of ESG Analytics. With a rich background in financial markets and technology, Q has been a pioneer in merging AI with ESG sectors.

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ESG Analytics: A New Perspective

ESG Analytics, stands out as a beacon in the ESG realm. This software platform offers real-time insights into company ESG scores, leveraging ESG sentiment and other innovative AI techniques. The platform's unique approach provides insights often overlooked by traditional news and media.

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The Essence of the Webinar

The core of the webinar revolved around several pivotal topics:

The Power of Alternative Data: Highlighting the significance of data sources outside traditional company disclosures, such as social media insights, web scraping, and satellite imagery.

Demystifying AI: Q broke down the vast world of AI, explaining its subsets like Machine Learning, Deep Learning, and Natural Language Processing (NLP). He emphasized the importance of understanding these terms beyond their buzzword status.

AI's Role in ESG: The session delved deep into how AI, especially NLP, can be a game-changer in ESG analysis. By analyzing vast amounts of textual data, AI can offer insights that traditional methods might miss.

Real-world Applications: Using real-world examples, like the use of OpenTable data during the COVID-19 pandemic, Q showcased the transformative potential of alternative data in providing real-time insights.

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The Poll

To make the session interactive, a poll was launched to understand the audience's background. The diverse mix, from portfolio managers to fintech experts, showcased the broad relevance of the ESG world.

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Conclusion

The webinar "Applying AI to ESG Analysis" was not just an informative session but a deep dive into the future of ESG analysis. With experts like Qayyum leading the charge, the fusion of AI and ESG promises a future of deeper insights and more informed investment decisions.

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The Lecturer

‍

ESG Analytics: A New Perspective

‍

The Essence of the Webinar

The core of the webinar revolved around several pivotal topics:

The Power of Alternative Data: Highlighting the significance of data sources outside traditional company disclosures, such as social media insights, web scraping, and satellite imagery.

‍

The Poll

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Conclusion

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Why is ESG data expensive?

The costs of collecting, analyzing and storing data are not cheap. And unlike financial data, there is no standardized process for determining ESG scores.The complexity of ESG data and the lack of standardization in the process for assessing environmental, social and governance factors also makes it difficult to compare companies on these metrics. Regulators are trying to make ESG information more transparent by mandating that companies disclose them alongside their financials, but this is still materializing globally. Traditional providers such as MSCI or Refinitiv employ armies of analysts to get this data from corporate disclosures (if it exists) and then normalize that data and provide it back to you. This is a very expenive process, with lots of quality control, and importantly - because this data is not disclosed very frequently (companies typically disclose ESG related data annually), there is less incentive to have a continuous subscription to a ESG data feed, along with risk of information leakage. All of this results in very expensive, and limited annual contracts.

Artificial Intelligence is changing the way we create and consume ESG data, which address many of the issues above - but that is a topic for another day.

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Why is ESG data expensive? 6

The costs of collecting
The costs of collecting
The costs of collecting ation in the process for assessing environmental, social and governance factors also makes it difficult to compare companies on these metrics. Regulators are trying to make ESG information more transparen
The costs of collecting

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What’s a Rich Text element? 5

The costs of collecting
The costs of collecting
The costs of collecting
The costs of collecting ation in the process for assessing environmental, social and governance factors also makes it difficult to compare companies on these metrics. Regulators are trying to make ESG information more transparen
The costs of collecting

Deep Dive into the Webinar: Applying AI to ESG Analysis

The Lecturer

ESG Analytics: A New Perspective

The Essence of the Webinar

The Poll

Conclusion

Stay updated with our ESG insights and product updates.

Deep Dive into the Webinar: Applying AI to ESG Analysis

The Lecturer

ESG Analytics: A New Perspective

The Essence of the Webinar

The Poll

Conclusion

What’s a Rich Text element? 1

What’s a Rich Text element? 2

What’s a Rich Text element? 3

What’s a Rich Text element? 4

What’s a Rich Text element? 5

What’s a Rich Text element? 6

Why is ESG data expensive?

Why is ESG data expensive? 6

What’s a Rich Text element? 5

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