Clarity AI statement related to ESG Rating and Data Products Codes of Conduct
Statement of the application of the ICMA and the Japanese codes of conduct, aligned with IOSCO Recommendations
Introduction
Below is Clarity AI’s statement related to its application of the International Capital Markets Association Code of Conduct for ESG Ratings and Data Products Providers (ICMA Code), and its endorsement of the Japanese Financial Services Agency Code of Conduct for ESG Evaluation and Data Providers (JFSA Code). Clarity AI supports both of these codes given they closely follow the International Organisation of Securities Commissions (IOSCO) 2021 Recommendations for ESG Ratings and Data Products Providers.
Clarity AI undertakes its business in a manner that is consistent with the principles underpinning the IOSCO Recommendations: transparency, striving for the highest quality, good governance, managing conflicts of interest and efficient data procurement. Alongside our endorsement of both the ICMA and JFSA codes, we stand ready to further engage with industry and regulatory groups on the development of similar initiatives going forward to ensure – via mutual reference to the IOSCO Recommendations – the maximum level of interoperability between different initiatives across different jurisdictions. Ultimately, the adoption of these principles across the board can improve outcomes at an industry level, and support trust in the ESG data and evaluation industry.
Background
Clarity AI is a leading sustainability tech company, serving the world’s most significant asset managers and institutional investors, as well as companies, consumers and other stakeholders. We are a digital-native firm offering a comprehensive, customizable, fully-packaged Sustainability Tech Platform. The platform consists of “building blocks” for every sustainability use case (including data, methodologies and tools) powered by advanced technology and AI, and its fully modular infrastructure allows users to take any or every piece of the sustainability tech kit.
Clarity AI’s software as a service (SaaS) model is data driven, not analyst driven. As such we offer data, as well as scores and analysis that are customizable by the end user depending on their preferred data, metrics, weightings and materiality approach. Alternatively our users can use our pre-set methodologies that are rules-based and grounded in internationally recognised evidence and research. As such, Clarity AI does not provide ESG ratings (defined as being subjective and analyst driven), but ESG data insights and scores (defined as being rules-based and data driven).
Clarity AI builds its products and solutions with data at its core, the vast majority of which is collected from public sources, such as companies’ annual and sustainability reports. Clarity AI also sources third party data to complement its offering. We also work with clients who integrate their own data into the platform, and utilize Clarity AI’s methodologies and/or tools.
For the investor segment, Clarity AI supports its clients end-to-end in integrating sustainability in capital allocation, risk management, impact assessment, and automated reporting (to clients, regulators and other stakeholders). This includes solutions like ESG scores, controversies and exclusions, regulatory and reporting tools, themed modules around eg., climate and nature, impact modules (eg., SDGs) and a mandate functionality: a fully customizable tool for enabling portfolio analysis, monitoring and reporting around sustainability.
Clarity AI’s business model is based on subscriptions. Clients can choose which information and level of detail they want to integrate into their system (via API calls or widget integration), or consume directly through the Clarity AI Web App.
Clarity AI has received numerous distinctions as an industry leader for its innovation, its vision and its offering of sustainability data and analytics. These recognitions cover many of the areas covered by the ICMA and JFSA Codes. A recent example of this recognition is from the independent analyst firm Forrester, which named Clarity AI a leader in The Forrester Wave™: ESG Data and Analytics Providers, Q3 2024. The report is an evaluation of the most significant vendors in the ESG Data and Analytics space.
In their analysis, we received the highest score possible in the current offering and strategy categories, including data coverage and quality, data collection, transparency of data and methodologies, system and workflow integration, customized data valuations, alignment to standards and frameworks, and customer service.
Application of the Codes
Below is a principle by principle analysis of Clarity AI’s business in relation to the ICMA and JFSA Codes of Conduct. There are seven principles in total: five are consistent across ICMA and JFSA, one is unique to ICMA (Good Governance), and one is unique to JFSA (HR Development).
1. Good Governance
ESG ratings and data products providers should ensure appropriate governance arrangements are in place that enable them to promote and uphold the Principles and overall objectives of the Code of Conduct. (ICMA Code only, Principle 1)
Clarity AI application
Good governance, transparency and accountability are at the core of Clarity AI’s business operations. Through this, Clarity AI ensures it can uphold the principles outlined in the Codes. Clarity AI has a clear organizational structure, with appropriate oversight of all ESG data and evaluation products, and minimizes any conflicts of interest that arise in the process of doing business.
When making significant decisions – such as developing new products, making changes to existing methodologies or onboarding new data sources – strict processes and procedures are followed to ensure the quality and independence of Clarity AI’s products.
Clarity AI strives for excellence in terms of hiring and training staff. Clarity AI hires and supports the continuous training and development of experts from a range of backgrounds including technology, sustainability, finance, and legal and regulatory to produce and market ESG data and evaluation products of the highest quality. For more information on Clarity AI’s approach to human resources, see “Principle 3 – HR Development” below.
Clarity AI’s oversight function is evolving against a backdrop of regulatory developments in the sustainability space. This ensures that Clarity AI maintains a robust approach to good governance and enables any future regulatory requirements to be implemented with minimum disruption to its business.
2. Securing Quality
ESG ratings and data products providers should adopt and implement written policies and procedures designed to help ensure the issuance of high quality ESG ratings and data products. (ICMA Principle 2)
ESG evaluation and data providers should strive to ensure the quality of ESG evaluation and data they provide. The basic procedures necessary for this purpose should be established. (JFSA Principle 1)
Clarity AI application
Clarity AI strives for excellence in terms of the quality of its data, methodologies and tools. It offers scientific- and evidence-based methodologies powered by research, and AI and data science expertise. Clarity AI leverages advanced analytics to collect and analyze data points, perform reliability checks and run estimation models at scale. All Clarity AI products are subject to rigorous policies, processes and standards that are regularly reviewed for improvements. Continuous learning is at the core of Clarity AI’s quality standards, and the company has multiple channels for clients to share feedback in order to drive improvements.
Clarity AI sustainability experts work together with tech experts to innovate, create, deploy and maintain reliable and transparent tools and scores by leveraging advanced technology (including artificial intelligence such as machine learning, natural language processing and generative AI). In this way, Clarity AI ensures that technology and human expertise work hand in hand delivering quality outputs for our clients.
Clarity AI regularly communicates publicly regarding our approach to ensuring quality, including via articles and webinars. Externally this has also been noted by various third parties.
According to Forrester’s evaluation: “Clarity AI distinguishes itself with the breadth, depth, granularity, and quality of its ESG data, using AI and machine learning to perform data collection, extraction, and mapping; execute quality assurance and reliability checks; and run estimation models.”
– Data
In our data collection process, Clarity AI employs comprehensive automated data quality controls, including machine learning-based reliability checks, developed and continuously improved by data science and sustainability experts. When assessing historical data trends, company data, industry peers, and proprietary models, our algorithms, combined with our human-in-the-loop approach, are able to identify, eliminate and correct inconsistencies. This approach allows us to provide our clients with high-quality and reliable data and sets us apart from other methods of data accuracy assurance. Our data points are also fully traceable to the source.
Where Clarity AI works with external data providers to complement its own data collection, it enforces the strictest standards with all of its providers and regularly and comprehensively reviews the quality of the data and services it receives, by applying quality assurance processes, leveraging artificial intelligence and machine learning.
– Methodology
Clarity AI has developed a number of different data and evaluation products that enable its investor users to assess the sustainability of different financial products and portfolios. As a software-as-a-service provider, Clarity AI tools allow its clients to customize any products to their use case, e.g. by using different data sources, metrics weightings, or materiality approaches.
Where customers choose to use products with pre-set methodologies and scores, Clarity AI’s assessments are rules-based and grounded in internationally recognised evidence and research. Detailed methodologies are made available to users in order to understand the formulae, data sources and assumptions underpinning any models. Our modular technology platform, connected to a single source of truth and integrating rule-based methodologies, ensures their consistent application.
Clarity AI regularly updates its pre-set methodologies to ensure they follow the latest cutting-edge research, analytics and regulatory changes. The frequency of updates depends on the topics, use cases, and clients’ needs, ranging from daily to monthly. Clarity AI regularly engages with investment professionals, including through its Client Advisory Board, and with regulators through bilateral conversations and working groups to ensure our solutions are aligned with industry best practices. Any changes made as a result of this feedback loop are subject to a full assessment of their implications and communicated to clients.
– Tools
Clarity AI is recognised as a leader in terms of integration in its clients’ workflows and systems (see, for example, Forrester 2024). The Clarity AI Web App is the flagship product, offering clients a seamless way to visualize the sustainability of their portfolios via different sustainability and materiality lenses. Beyond the web app, Clarity AI offers additional integration methods, including APIs, widgets, and datafeeds, which further embed into clients’ existing systems. These tools are customizable, allowing clients to receive relevant and actionable insights in the most efficient way possible. A centralized platform approach ensures that all data is derived from the same reliable source, maintaining data integrity across different analyses. The processes that generate APIs and datafeeds are completely automated and undergo rigorous quality checks to ensure not only data integrity but also historical consistency. Clients can trust that the information presented is consistent and accurate, regardless of the perspective they choose to explore. For more information, see here.
3. HR Development
ESG evaluation and data providers should secure necessary professional human resources to ensure the quality of the evaluation and data provision services they provide, and should develop their own professional skills. (JFSA Code only, Principle 2)
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Clarity AI places great importance on the company’s culture when it comes to recruitment. Candidates go through a cultural fit screen, to evaluate their alignment with Clarity AI’s values of excellence, passion and ethics. The pillars of its culture are to be fact-based, diverse, meritocratic, transparent and flexible. For more info, please see here.
Clarity AI’s management recognises the importance of qualified personnel to deliver on our mission of bringing societal impact to markets. Our recruitment processes ensure all new hires are subject to a rigorous selection process. Once hired, Clarity AI assesses its staff on a continuous basis and performance review cycles. Staff are assessed against key performance metrics.
Our staff continually exchange knowledge and have access to resources provided by Clarity AI and third parties for continuous professional learning and development in their respective field of expertise. Many have extensive post-graduate studies in related fields. In addition to performance review processes that lead to the identification of growth opportunities that employees work with their manager to achieve, team members are developed continuously through continuous feedback and on-the-job learning, formal courses/training and attendance to global leading conferences and events which are subsidized by the company.
4. Ensuring Independence and Managing Conflicts of Interest
ESG ratings and data products providers should adopt and implement written policies and procedures designed to help ensure their decisions are independent, free from political or economic interference, and appropriately address actual or potential conflicts of interest that may arise from, among other things, the ESG ratings and data products providers’ organisational structure, business or financial activities, or the financial interests of the ESG ratings and data products providers and their officers and employees. ESG ratings and data products providers should identify, avoid or appropriately manage, mitigate and disclose actual or potential conflicts of interest that may compromise the independence and integrity of the ESG ratings and data products providers’ operations. (ICMA Principle 3)
ESG evaluation and data providers should establish effective policies so that they can independently make decisions and appropriately address conflicts of interest that may arise from their organization and ownership, business, investment and funding, and compensation for their officers and employees, etc. With regard to conflicts of interest, providers should identify their own activities and situations that could undermine the independence, objectivity, and neutrality of their business, and avoid potential conflicts of interest or appropriately manage and reduce the risk of conflict of interest. (JFSA Principle 3)
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– Business model
Clarity AI’s business model minimizes its exposure to conflicts of interest and any conflict is addressed with proper processes and procedures. In fact, Clarity AI does not provide ESG ratings, but allows users to build customized scores and provides pre-set scores and sustainability assessments. Clarity AI’s scores are based on three main types of information to qualify an entity’s sustainability performance: quantitative metrics, policies and controversies. The pre-set scores are quantitative outcomes of models and do not embed any qualitative assessment based on analysts’ views. These cannot be influenced by the companies subject to the scoring.
Clarity AI allows its users to view their portfolios through different sustainability lenses, including in terms of risk, impact and exposures, or thematically in terms of biodiversity, climate or regulatory use cases. The models underpinning Clarity AI’s scores can be customized by our clients to reflect their own sustainability views, especially regarding the relative weights of the KPIs contributing to the aggregated score. Clarity AI provides transparency on the raw data underlying its scores and metrics, along with its sources. The user always has full transparency to see and tailor how different weightings or materiality approaches impact the overall picture of the portfolio.
– Structure, processes and procedures
All personnel working on the methodologies underpinning ESG evaluations and data are separated from the sales division. Input from companies subject to our scores is only integrated where it relates to raw data values at the metric level. Clarity AI will correct errors in the underlying raw data that drive the scores only when these errors have been confirmed through publicly available evidence.
Clarity AI staff involved in research and analysis are not able to tamper with methodologies and data in a way that favors their own private financial transactions. Specific guidelines around staff own investments apply to all employees.
Nevertheless, conflicts may arise in the course of changing industry dynamics or further growth of the company. Clarity AI monitors conflicts throughout its business and continuously updates its policies, including regarding the management of conflicts of interest as necessary.
– Out of scope
Clarity AI does not provide any ancillary services, such as credit ratings, index provision or audit.
5. Ensuring Transparency
ESG ratings and data products providers should make adequate levels of public disclosure and transparency a priority for their ESG ratings and data products, including their methodologies and processes to enable the users of the product to understand what the product is and how it is produced, including any potential conflicts of interest and while maintaining a balance with respect to proprietary or confidential information, data and methodologies. (ICMA Principle 4)
ESG evaluation and data providers should recognize that ensuring transparency is an essential and prioritized issue, and publicly clarify their basic approach in providing services, such as the purpose and basic methodology of evaluations. Methodologies and processes for formulating services should be sufficiently disclosed. (JFSA Principle 4)
Clarity AI application
As the company’s name suggests, transparency is one of the core values of Clarity AI. Clarity AI is a market leader in terms of offering full transparency to its clients on the methodology used (including customized methodologies by the user) and the source of each underlying data point. Clarity AI also provides clients with the ability to have a view at the portfolio level, including both the entities and the investment funds that the client is invested in.
Clarity AI provides transparency to its users at every level possible:
- Methodological documents are published for all products. These explanations are also embedded into our software platforms.
- For calculated metrics (e.g., exposure to controversial activities) Clarity AI includes an explanation of how the metric has been constructed and the inputs that went into that calculation.
- Type and source of raw data specified: e.g. for quantitative metrics, Clarity AI flags whether the data is reported or estimated and whether the data is from Clarity AI or an external provider. For reported Clarity AI data, the platform provides links to the company report where the data can be found and in some cases extracts from the report are included in our platform.
- For Clarity AI estimated data, we provide the confidence level of the estimate.
Clarity AI is known as a market leader in transparency: “Customers can access methodologies and data sources for increased transparency. Clarity AI is lauded for its technology, the breadth and transparency of its data and methodologies, the usability of its web interface, and the responsiveness and expertise of its customer service,” Forrester.
Clarity AI investigates any queries on its data or outputs with the utmost diligence. Our outputs are based on data collected directly from reported entities or trusted third parties. Where estimates are used, the assumptions underpinning them are well documented and shared with users, along with the relevant confidence interval of the estimate. Users of Clarity AI’s tools can, via an automated feedback loop, notify Clarity AI of any perceived errors in the data that are fully investigated.
Any updates to methodologies or changes to underlying data are fully communicated in advance to impacted clients, along with an explanation of the change and its implications. Clarity AI also maintains a data change log that tracks any such changes to ensure they can be reviewed and audited at a later date as required. Clarity AI keeps an accurate track of every change in its data sets over time. Every sustainability measure, such as ESG Scores, can be reproduced at any point in time upon request.
Moreover, Clarity AI provides visibility on the changes that it performs over its data through a Data Log functionality accessible upon request or directly in the transparency panel available through the Web App. This functionality informs precisely when a given data point has been updated and what is the scope of the change.
6. Confidentiality
ESG ratings and data products providers should adopt and implement written policies and procedures designed to address and protect all non-public information received from or communicated to them by any entity, or its agents, related to their ESG ratings and data products, in a manner appropriate in the circumstances. (ICMA Principle 5)
ESG evaluation and data providers should establish policies and procedures to appropriately protect non-public information obtained in the course of business. (JFSA Principle 5)
Clarity AI application
In the instances where Clarity AI receives any confidential information, we have policies in place to ensure it is handled to the highest possible standards. Clarity AI processes any sensitive information in line with confidentiality obligations and ensures all of our providers do the same. In addition, Clarity AI has a code of conduct and information security policies which also contain obligations to maintain confidentiality of the information that employees need to abide by. Clarity AI also has internal policies regarding data classification and data handling already in place.
We have been awarded the globally recognised ISO 27001 and SOC 2 Type II accreditations, demonstrating our commitment to exceptional quality and robust information security management.
The ISO 27001 certification is the international standard for Information Security Management Systems (ISMS). It provides a framework for managing information security risks, including legal, physical, and technical controls that involve an organisation’s information risk management processes. The team’s achievement of ISO 27001 accreditation testifies to their dedication to ensuring the security and integrity of the confidential data entrusted to them.
SOC2 Type II is a Service Organization Control (SOC) audit on how a cloud-based service provider handles sensitive information. For cloud service companies, having an independent assessment of their security safeguards is a cornerstone of trust, covering three out of the five total trust service principles (TSPs) for Clarity AI: security, availability and confidentiality.
Our Information Security team has also obtained CSA Star Level 1 accreditation to showcase our cloud security governance in line with the Cloud Security Alliance’s latest cybersecurity framework requirements. Information on security practices is made available from our Trust Center.
7. Engagement and Communication with Companies
ESG ratings and data products providers should regularly consider whether their information gathering processes with entities covered by their products leads to efficient information procurement for both the providers and these entities. Where potential improvements to information gathering processes are identified, ESG ratings and data products providers should consider what measures can be taken to implement them. Where feasible and appropriate, ESG ratings and data products providers should respond to and address issues flagged by entities covered by their ESG ratings and data products and by users while maintaining the independence and integrity of these products. (ICMA Principle 6)
ESG evaluation and data providers should devise and improve the way they gather information from companies so that the process becomes efficient for both service providers and companies or necessary information can be sufficiently obtained. When important or reasonable issues related to information source are raised by companies subject to evaluation, ESG evaluation and data providers should appropriately respond to the issues. (JFSA Principle 6)
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– Data Collection
Clarity AI leverages technology – including AI and ML – to perform data collection and extraction, and to perform quality analysis and reliability checks. In doing so, Clarity AI minimizes errors inherent in manual data collection processes (see for example here). This procurement also ensures the quality of the derived sustainability scores and insights.
– Interaction with companies
Clarity AI methodologies are rule-based, not analyst-based. Moreover, the majority of Clarity AI’s business is undertaken on a subscriber-pay basis and the vast majority of the data is obtained via public sources. Hence, Clarity AI does not systematically engage with all companies. However, in those instances where Clarity AI communicates with companies, we ensure those communications are open and never influence the outcome of pre-defined, rules-based assessments. Clarity AI welcomes any relevant, factual feedback on raw data from companies and offers (free) access to any inquiring companies to review all collected data and scores. Clarity AI is developing tech-based capabilities to proactively contact companies to ensure their data is up to date and streamline the engagement and collection process. Data errors or missing data points can be reported in an automated way directly to Clarity AI within its Web App.
