Indirect influence - Direct Climate effect

Reference number
Funding from Vinnova SEK 500 000
Project duration October 2019 - June 2020
Status Ongoing
Venture AI - competence, capacity and capability
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Purpose and goal

The aim of the project is to develop a prototype of an AIsolution to identify how well companies are reporting on the climate issue, based on indirect and direct ghg-emissions. By evaluating the possibilities with AI to contribute to the access of available data, categorization and automation, the project can result in better access to comparable data and the opportunity for investors to influence companies in a more sustainable direction. The aim is also to promote knowledge about how AI can contribute to ensure better quality of analyzes regarding companies´ indirect emissions.

Expected results and effects

If investors have easy access to comparable data on how companies are performing based on the climate issue, both goals and actual outcomes, their opportunities to influence them in a more climate-smart direction increase. Expected effects of the project are that information can be made available and comparable. The result from the project provides knowledge to scale up the AI solution, we also predict that the result can be used as decision basis, both as an investment basis, but possibly also as a basis for communication around the climate issue.

Planned approach and implementation

The project is divided into three work packages. AP1. Scraping - Retrieving relevant data. Relevant data sources are identified and data is collected into a Data Lake. AP2. Categorization and documentation for Machine Learning. We integrate a cognitive search and content analysis engine with applications to identify patterns, trends and actionable insights for better decision making. AP3. Analysis and visualization. The result from AP3 is a decision basis that can be used both as an investment basis, but possibly also as a basis for communication around the climate issue.

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 23 September 2019

Reference number 2019-03276

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