Transparent methodology enables investors and others to make better informed decisions for sustainable capital allocation
RepRisk, a leading ESG data science firm combining machine learning and human intelligence to identify ESG risks, takes a major step forward in enabling more sustainable capital allocation by making its ESG data methodology publicly available on the RepRisk website. Additionally, RepRisk’s Jupyter notebooks, a public online resource, provide access to Python code, algorithms, and sample datasets that can be used to build and customize ESG scores and portfolios.
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“This is a pivotal day for transparency in ESG and for RepRisk by being the first and only ESG data provider to publish our detailed methodology, publicly, on our website,” said Philipp Aeby, CEO of RepRisk. “While we have always been transparent with our clients and partners, we now want to make it available to the world. Being transparent enables our clients to make better informed decisions – and it’s the right thing to do. As a pioneer in the ESG data industry, we are excited to see the growth, acceptance, and adoption of ESG data.”
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With this step, RepRisk effectively addresses the barriers to ESG integration and risk management for investors and other financial professionals. Since 2006, RepRisk has built a consistent dataset with a rules-based and transparent methodology that goes back 15 years – the longest time series in the industry. And through the combination of AI and machine learning with human curation, investors and others leverage reliable data with the speed and breadth of coverage they require. RepRisk’s outside-in approach exclusively looks at a company from an external perspective, which serves as a reality check for how a company manages ESG issues and conducts its business on the ground.
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