Overview of the Upright net impact model
This page introduces key algorithms used to quantify net impact.
The Upright net impact model consists of two main parts: the macromodel, and the company model. The primary output of the Upright net impact model is net impact. In addition, it also produces UN SDG, EU taxonomy, EU SFDR Principal Adverse Impact (PAI), and CSRD DMA metrics.

Macromodel
The macromodel integrates information from a variety of sources to produce estimates of the impact of all products and services.
Input data
The main data source used by the macromodel is a database of 200M+ scientific articles. Other data sources include databases from the World Bank, IMF, WHO, OECD, Eurostat, IPCC, CDC, USDA, IHME, and others.
When little quantitative data is available, the Upright net impact model relies mostly on the results of Upright's proprietary NLP deep learning algorithm that reads causal statements from hundreds of millions of scientific articles. When reliable, readily available quantitative data is available, the Upright net impact model puts a greater weight on this data.
Algorithms
The macromodel consists of three major algorithms:
Extraction of causal links from scientific literatureGeneralization of scientific knowledgeAllocation of impact across value chainsCompany model
The company model combines the information produced by the macromodel with information on specific companies, most importantly information on what those companies are doing (i.e. what their products and services are) to produce an estimate of the impact of each company.
Estimation of company product mixesLast updated
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