Transparency Commitment Charter

RepRisk believes in the power of ESG data to drive accountability and the responsible behavior of companies.

As a pioneer in ESG data science, we are excited about the growth and adoption of ESG data across financial market participants and corporates. At a critical time in the history of ESG, the industry and application of ESG data face scrutiny and challenges including lack of transparency, reliability, timeliness, and coverage of ESG data, as well as potential conflicts of interest and lack of independence of ESG providers.

RepRisk echoes the call for more transparency in the ESG industry. We encourage providers to be explicit about the purpose of their data and ratings, and to disclose their research approach, methodology, underlying data, list of services provided, and level of independence.

Our values underscore everything we do and how we do it. In line with our intellectual honesty, humility, and pioneering spirit, we have taken the lead when it comes to transparency by being the first to publicly disclose our methodology in November 2021 (we have always been transparent with our clients and partners). We welcome anyone to “look under our hood” and those of any other provider to better understand how datasets align with their strategies. We are dedicated to operational excellence and will continue delivering the highest quality in our processes, products, and services and improving them continuously.

In keeping with our values and appeal to the industry, RepRisk is committed to transparency with our clients, partners, and the public on:

  • Purpose of our data: The purpose of our dataset is clear and simple – to identify and assess material ESG risks. With that, we enable companies, investors, and others to proactively mitigate these risks that can lead to reputational, compliance, and financial impacts for the company and its stakeholders, as well as impacts on people and the planet. We have deep domain expertise built over 17+ years and our vision is to be the global standard for ESG risk data. We do not aim to be everything to everyone, e.g., an “ESG one-stop-shop.”

  • Methodology: To make it easy to understand what our data can and cannot do, we are transparent about our research approach, methodology, and underlying data. With that, we publish the rules-based process of how we gather and analyze the data, what machine learning models we use, how we define the ESG risk factors included in our research scope, and how we construct our metrics. We do not publish the data and the metrics themselves.

  • Timeliness and coverage: Our combination of machine learning and human intelligence results in the world’s largest dataset on ESG risks, updated on a daily basis. While technology enables the speed, scale, and breadth of our dataset, our human analysts ensure the quality and consistency of our data.

  • Reliability: Since the official launch of our dataset in 2007, we have used a consistent methodology to enable rigorous backtesting and quantitative analysis. We communicate data maintenance and enhancements proactively with our clients and partners in order to continue meeting their expectations of quality and consistency.

  • Potential conflicts of interest and our independence as a provider: RepRisk exclusively focuses on ESG data and research, and does not offer any other services or products such as indexes (based on ESG ratings that are informed by the needs of index clients) or credit ratings. Furthermore, RepRisk is fully financed by the data subscription fees from our clients and does not offer bespoke assessments, assurances, second-party opinions, proxy-voting or engagement services, or advisory. Lastly, as our research is exclusively based on information external to a company, a company in our dataset cannot influence its score or risk profile.

We keep pursuing our vision of being the global standard for ESG risk and due diligence, delivering best-available data, from sensing to sentiment, to leading organizations across all industries.

Clarity for the purpose of our data

Transparency on our methodology

Ensuring reliability, timeliness, and coverage of data

Free of any conflicts of interest