The problem: Time-consuming ESG data extraction from unstructured data sources

For its EU Taxonomy, good governance, and impact analyses, Lightrock manually extracted data from excel sheets, websites, and pdfs. This took Lightrock over a day per target company it was assessing for due diligence purposes, and even longer for portfolio companies. Compliance with the technical screening criteria and do no significant harm requirements set out by the regulators, however, requires a high degree of technical and domain-specific knowledge and the firm often lacked crucial data from its earlier stage portfolio companies. As a result, its in-house assessment process became extremely time-consuming.

Lightrock is a global private equity platform that invests in businesses that contribute positively to society and the planet. It strongly believes in the role technology has to play in helping investors to make even better decisions and scale the value they provide with and for companies from their portfolio.

The solution: Briink’s ESG Scanning & Assessment tool

Lightrock adopted Briink’s AI-Powered ESG Scanning Solution and the Briink Taxonomy Platform to verify the Taxonomy eligibility and alignment of the economic activities performed by its portfolio companies. Briink enabled Lightrock to quickly identify the relevant activities, evidence the outputs and automate substantial parts of its data collection, document and evidence extraction processes.

We see a lot of value in Briink’s tool, particularly when looking at funds with a high number of investments, which allows for significant time savings.

Dr. Marc Moser, Head of Impact at Lightrock

Briink brings clearer insights & seamless decision-making

Thanks to Briink, Lightrock saw a significant increase in its operational efficiency, saving 30% of the time spent on ESG  assessments and providing clearer insights for more efficient decision-making. A feature that Lightrock loved was Briink’s flexible AI screening infrastructure, which helped it capture ESG and impact metrics that are of particular importance to the fund, without being boxed into a rigid and fully pre-set platform. 

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