Welcome to Impact Insights, the podcast series of Astaire Investment Managers.

Overall, AI and big data analytics are powerful tools that aid investors, both public and private,

in making their investment decisions.

In today's episode, Triscorney, Investment Manager at Assyria, highlights the importance of big data technology in ESG and impact research.

Big data is already commonly used to create data-driven investment models. Such models typically evaluate public companies on fundamentally based or economically motivated

investment themes and use company-specific data such as financial statements, returns, volumes,

internet web traffic, patent filings and its contents to guide investments.

It's only natural that investing with impact in a data-driven environment is only possible

using systematic impact data. Regardless of its merits or shortcomings, the search in ESG investing

made it clear that for proper portfolio to portfolio comparisons, reliable, environmental, social and governance data

is required for a very broad universe.

Because if coverage and quality are too low, any comparisons are completely meaningless.

Taking it one step further to the recent focus on environmental and social impact investing,

the same conclusion holds. Only with broad, good quality

coverage can meaningful comparisons be made. It follows that for targeted impact investing,

this data is crucial even when evaluating the impact of a single company. Because, for example,

if you have good data on only a single company, but not on any other company in the world,

there is no way to evaluate how the impact of this single company ranks with respect to the full universe.

And hence, you don't really know if what you perceive as good is actually good compared to what else is available.

This means that even for high conviction portfolios,

big data on impact metrics is required

to properly position the portfolio.

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