VANCOUVER, British Columbia — ESG Data Services Inc (“ESG Analytics”), today announced the release of ESG Analytics, a next generation AI powered ESG data, analytics and research platform. ESG Analytics is a web-based solution and API that uses broad-based alternative data sources and artificial Intelligence (AI) to uncover risks and opportunities in the environmental, social and governance (ESG) practices of countries, companies and ETFs. ESG Analytics’s continuously updating big data platform allows researchers, analysts, funds and companies to get new and timely insights as they integrate ESG as part of the investment management process and company decision making.

As a team of highly experienced finance and technology professionals, the technology behind ESG Analytics was developed out of frustration with the existing status quo in the market. It has been in stealth mode development for the past year and the team is excited to finally bring their innovative solution to market.

“The environment for ESG could not be at a bigger transition time in history. We are at the crossroads of 3 major trends – ESG, AI and Alternative Data. Providers of ESG data today continue to have abysmal coverage of the investable universe, with most covering less than 10,000 companies. This is further impacted by slow or delayed analysis, outdated data sources, low-quality self assessed data and inherent biases, all of which impact investor decision making negatively. We believe investors need to look at the problem differently; it’s not enough to say that a company is ESG because it is in a certain industry, or that a fund is sustainable because it has ESG in its name. That’s why we built our system from scratch, enabling the next frontier of ESG analysis.” said Qayyum Rajan, CEO of ESG Analytics.

ESG analysis today is reliant on company disclosures. By going outside of these traditional means, and looking at alternative data using tools such as Natural Language Processing (NLP), it is possible to understand things differently, and paint a different profile of entities that exist today.

“ESG Analytics opens up a world of deep and meaningful analysis for the investors looking beyond the surface details everyone else uses. By tuning the model based on what the individual investor is passionate about, they are creating the possibility of uniquely aligned investment portfolios that truly empower investors to impact the global market in ways they care about.” said Patrick Audley, CTO of ESG Analytics.

ESG Analytics AI-driven approach allows for users of the software to:

● Compare and contrast 80+ ESG indicators for over 193 countries

● Analyze negative and positive screens for companies globally

● Use AI to sift through the universe of unstructured media to determine potential ESG risks and opportunities for over 60,000 companies across 22 different stock exchanges

● Aggregate and view screens and AI flags for 1200 ETFs globally

The platform is available today at esganalytics.io

About ESG Analytics

ESG Analytics was founded in 2020 and is an alternative data provider that creates and tracks non-traditional sources to measure how companies, countries and investment funds are implementing environmental, social and governance practices.

The company is based in Vancouver, British Columbia.

ESG Analytics AI-driven approach allows for users of the software to:

● Compare and contrast 80+ ESG indicators for over 193 countries

● Analyze negative and positive screens for companies globally

● Use AI to sift through the universe of unstructured media to determine potential ESG risks and opportunities for over 60,000 companies across 22 different stock exchanges

● Aggregate and view screens and AI flags for 1200 ETFs globally

The platform is available today at esganalytics.io

About ESG Analytics

The company is based in Vancouver, British Columbia.

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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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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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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

ESG Analytics Announces Launch of Next Generation ESG Platform

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ESG Analytics Announces Launch of Next Generation ESG Platform

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