top of page

Data + Methodology

GaiaLens optimises explainability to enable users to drill into and fully understand the detail behind the numbers. Our proprietary algorithm enables the system to aggregate a massive volume of data in order to calculate overall ESG scores.

We are flexible when it comes to data delivery and can deliver via our API, data dumps or sharing via a bucket.

GaiaLens Scoring Hierarchy

Scientifically Sourced ESG Scores

Calculate ESG scores for 19,000 companies in real-time using GaiaLens’ proprietary ESG scoring algorithm. The scoring system has four levels of hierarchy starting with transforming raw ESG data into Factor Level Scores, then calculating Theme Level Scores, Pillar Scores and finally Overall Scores. The platform currently has c.200 ESG factors that are used to calculate ESG scores and tracks well over 500 factors. Historical scores date back 20 years, giving a precise long-term view of performance.

Company overview 1.png
Pillar breakdown 1.png

Proprietary ESG Factors

GaiaLens has engineered proprietary data points that are inputted into the scoring algorithm. These
include Beneish M Score, Board Gender Pay Gap, Ethnic Diversity on the Board, Percentage of Independent Directors on Board, Percentage of Women on the Board, Employee Satisfaction Rating and Corporate Misconduct Penalties.

See how the GaiaLens ESG Analytics Platform can support with your ESG strategy 

GaiaLens multi coloured logo

Real-time ESG News

The technology reviews millions of articles, in turn generating signals using proprietary NLP models. This involves monitoring hundreds of thousands of news sources, social media, and NGO’s. Each article is heavily processed to extract as much value as possible, including calculating company relevance score (which measures how relevant the article is to the company). GaiaLens also calculates similarity and sentiment scores for over 50 different ESG topics including SASB themes and UN SDGs. Track key people/entities that get mentioned in articles such as CEOs and insider/outsider shareholders. News articles date back over 10 years, providing very clear patterns of company behaviour.

Controversies 1.png
bottom of page