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Covalence SA

Service Providers Framework 2020

You are in Research and Data Provision » Research/process level

Research/process level

RDP 02. Sources for research and/or rating

02.1. Indicate the types of sources you use for research and/or ratings of companies/sectors/geographies or similar. Tick all that apply.

02.2. Indicate how ESG factors are incorporated into your research and/or rating methodology

02.3. Describe how you define materiality and how this is captured in your research and/or rating methodology as well as final product.

          The data has been analyzed in terms of keywords, criteria and topics to identify which business impact is at stake. This approach is inspired by the Value Driver Model developed by The UN Global Compact and The Principles for Responsible Investment (PRI):
Growth: New markets and geographies, New customers & Market Share, Product & Services Innovation, Long-term Strategy
Productivity: Operational Efficiency, Human Capital Management, Reputation Pricing Power
Risk:  Operational & Regulatory Risk, Reputational Risk, Supply Chain Risk, Leadership & Adaptability

02.4. Additional information. [OPTIONAL]

RDP 03. Stakeholder input

03.1. Describe how you actively include input and information, wherever possible, from relevant stakeholders or interested parties, in the research process or in reaching assessment conclusions.

          The Covalence approach is based on a diversity of sources of information and relies on web monitoring and artificial intelligence together with human analysis. We compare ESG data publicly reported by companies (disclosure) to online narrative content reflecting the perceptions of stakeholders such as the media and NGOs (reputation). This approach allows users to track inconsistencies, monitor changes and benefit from timely alternative data. The information is delivered in an actionable format to support ESG risk exposure mitigation and long term value creation.
Stakeholders such as NGOs, governments, trade unions and the media describe the role and activities of companies in positive and negative terms generating either endorsements or controversies. Since 2001, Covalence has specialized in the semi-automated analysis of such narrative content. This expertise materialized in the award-winning EthicalQuote reputation index.

We use data collection and classification tools relying on artificial intelligence techniques (machine learning, natural language processing) in order to analyse the narrative content. This process is reinforced by human interventions to classify the content in terms of polarity (positive/negative) and criteria. Our team of analysts thoroughly checks entries proposed by the software, thus ensuring high curation standards. Only sources that are publicly identified and available online are considered.

Today, the Covalence database includes more than one million documents from over 50’000 different sources on 6000 companies that have been classified and curated by more than 600 analysts in collaboration with over 30 universities.

The database leverages the use of machine learning techniques thanks to the expertise of our Scientific Advisor Prof. Patrick Ruch, field expert and professor at the University of Applied Sciences and Arts Western Switzerland. The use of classification algorithms allows us to fully automate the collection and pre-classification of information including complex information such as polarity – or sentiment – as well as multiple criteria.

03.2. Additional information. [OPTIONAL]

RDP 04. Up-to-date assessment and ratings

04.1. Indicate how you ensure that your ESG assessment of companies/ sectors/ geographies or similar is up-to-date and that new information is incorporated or new assessments are conducted at reasonable intervals.

04.2. Additional information. [OPTIONAL]

RDP 05. Balanced research and assessment

05.1. Indicate how you typically ensure a balanced approach to your research methodology and assessing/rating of companies/sectors/geographies or similar. Tick all that apply and explain your approach to each option.

Type of indicators

Explain your approach

          We oppose ESG data publicly reported by companies (disclosure) to online narrative content reflecting the views of stakeholders such as NGOs and the media (reputation).

Explain your approach

          We use a daily ESG news monitoring system; ratings are updated on a monthly basis.

Explain your approach

          We oppose ESG data publicly reported by companies (disclosure) to online narrative content reflecting the views of stakeholders such as NGOs and the media (reputation).

05.2. Additional information. [OPTIONAL]

RDP 06. Consistency and comparability

06.1. Describe the control processes in place to ensure quality of research.

          Analysts check semi autmated coding of information relying our our in-house algorithm. Then experienced analysts check and correct entries made by other analysts. This enables to fine-tune the algorithm on a regular basis.

06.2. Additional information. [OPTIONAL]

RDP 07. Emerging ESG issues and trends (Private)

RDP 08. Client use of outputs (Private)

RDP 09.