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The future of ESG Reporting: How emerging technologies are revolutionizing Transparency


ESG Reporting
How emerging technologies are revolutionizing Transparency

If you are interested in applying to GGI's Impact Fellowship program, you can access our application link here.


 

1.INTRODUCTION


Environmental, Social and Governance (ESG) reporting has gained significant relevance for organizations, investors, and stakeholders in recent years. With the global focus shifting towards sustainability and responsible investing, there is a growing demand for accurate and timely ESG information disclosure. Voluntary disclosures by companies leave the room open to interpretation and raise questions about the accuracy and reliability of the data being disclosed. This is where emerging technologies such as Artificial Intelligence (AI) and Blockchain are expected to play a critical role in the coming years. Technology-enabled ESG reporting can address the limitations of low-quality data and manual errors, thereby enhancing the transparency and accuracy of the reported information. It can also support the sustainability efforts of companies through data-driven insights, benchmarking against peers, and forecasting. This white paper aims to explore the challenges associated with ESG reporting, as well as the promise of emerging technologies in transforming ESG reporting and disclosures.




2.Why ESG reporting is relevant: Investor versus Company Perspective


As an investor or a company, ESG mandates are becoming increasingly important in today’s world.


  • Investors are increasingly factoring in ESG aspects while making investment decisions. ESG-focused portfolios were nearly US $40 trillion in 2021, and this figure is projected to reach US $53 trillion by 2025, representing a third of the total global assets under management. Investors would need to determine whether they can rely on a company's publicly available data on sustainability and annual company reports to make informed decisions to minimize their risks.


  • On the other hand, for business leaders looking to showcase their company’s sustainability impact, ESG compliance builds trust and can improve access to capital. As per a study conducted by PwC’s Consumer Intelligence Series in 2021, consumers and employees are more likely to buy from and/or work for a company that stands up for ESG issues and found that over 76% of consumers would discontinue buying from companies that treat employees, communities, and the environment poorly. Therefore, for businesses, it is crucial to measure the progress of their ESG commitments, adopt suitable sustainability measures across their supply chain and benchmark themselves against industry standards, in order to maintain a competitive position. Further, increasing regulatory pressure may require companies to include ESG impact disclosures in their annual reporting.



3.ESG Reporting Frameworks and the Lack of Universality


While there are several ESG reporting frameworks, the standards are still evolving. The frameworks consist of guidelines and principles on the ESG metrics to be reported and the ESG strategy.


ESG performance is focused on the below 3 key criteria:


1.Environmental criteria: This measures the company’s performance with respect to safeguarding the natural environment, and is measured through greenhouse gas emissions, waste disposal, water, and energy use, etc.


2.Social criteria: Which examines the company’s commitment to the community, employees, suppliers, customers, etc.


3.Governance criteria: Which deals with the company’s leadership structure, CSR Strategy, internal controls, Shareholder rights, etc.


Companies make use of ESG reporting frameworks to ensure that they meet stakeholder expectations, adhere to regulatory compliance, and manage risks effectively. These frameworks are put together by nonprofit organizations, NGOs, and business groups and vary in their areas of focus and measurement metrics.


A few of the popular voluntary ESG Reporting Frameworks for disclosures of environmental, social, and governance information include:


Global Reporting Initiative (GRI) - Focuses on corporate environmental performance and provides guidelines for reporting. It is the leading standard for sustainability reporting, and over 73% of the world’s 250 largest companies report using the GRI framework.


Sustainable Development Goals (SDGs) - Established by the United Nations, the SDGs list 17 goals for addressing social and environmental challenges.


Sustainability Accounting Standards Board (SASB) – Covers five critical areas of sustainability, which are human capital, social capital, environment, business model and innovation, and leadership and governance.


Task Force on Climate-Related Financial Disclosures (TCFD) – Emphasizes climate change-related risks and opportunities and focuses on the short-term effect of climate-related information.


Carbon Disclosure Project (CDP) - This ESG framework focuses on climate change, deforestation, and water usage and maintains the disclosure data in an open database that can be accessed by companies and investors alike.


The large number of ESG frameworks to choose from results in a confusing landscape, and a lack of standardization in the ESG reporting. Businesses often choose the frameworks that align with their business strategy and can choose multiple frameworks in conjunction with each other for their voluntary disclosures. Hence, this may lead to an inaccurate representation and interpretation of the company’s ESG performance.




4.Challenges in ESG reporting


ESG data and metrics should capture a company's performance on a given ESG issue. However, the data accuracy associated with capturing a firm's performance remains a challenge, as most of the information available is self-disclosed by companies. Further, ESG metrics, data, and how companies report them are inconsistent. Interpretation differences among ESG data providers are considerable and there is a lack of consensus on what is “green” and “socially inclusive”.


The challenges concerning ESG data and reporting are summarized below.


Challenges in quantifying data: ESG metrics with respect to social and governance aspects, often consists of qualitative non-financial data. This data is usually captured in an unstructured, textual format, which adds to the challenge.


Lack of consistency and standardization in ESG reporting and metrics: Reporting frameworks differ in terms of what their focus is. Certain frameworks like TCFD provide guidelines for corporate environmental performance, while other frameworks like GRI value the company’s commitment to society’s overall well-being. Following only one framework could lead to a skewed focus on only one of the aspects of ESG reporting.


Materiality: Identifying which ESG metrics are material to ESG classifications may prove difficult since materiality (or financial significance) can vary from one business to the other.


Backward-looking approach: Reporting on the basis of only past non-financial information, without factoring in the potential impact of strategies to be adopted by the company in the future, can give an incomplete picture of the company’s ESG efforts.


Lack of transparency: Gauging the performance of companies becomes challenging when they resort to “greenwashing” – which is the use of deceptive or misleading marketing tactics in order to attract investors and bolster their reputation. This can lead to inaccurate assessments of the companies’ ESG classification.




5.How Emerging Technologies Are Transforming ESG Disclosure


Automation of ESG reporting through emerging technologies such as Artificial Intelligence (AI) and Blockchain have the potential to make ESG disclosure and transparency more effective and efficient. These technologies can revolutionize ESG reporting by improving accuracy, transparency, and efficiency by enabling companies and investors to gather and analyze vast amounts of data and facilitate informed decision-making.


AI and Machine Learning techniques can help aggregate and analyze massive amounts of information to gain valuable insights, detect material issues, and generate customized reports based on stakeholder interests. Blockchain technology offers many possibilities for driving transparency and trust in the reporting process, as it creates an immutable record of transactions, contracts, and reporting.


We take a closer look into the opportunities and risks of these technologies, below:


5.1 Artificial Intelligence (AI) in ESG reporting:


AI offers companies the ability to automate the collection and analysis of ESG data from diverse sources such as social media, news outlets, financial filings, and IoT sensors. This empowers companies to identify significant ESG risks and opportunities, track performance, and gain insights for informed decision-making.


AI can enable this through:

Natural Language Processing (NLP): NLP algorithms can analyze unstructured data from various sources such as regulatory filings, government studies, and industry publications to evaluate a company's ESG performance, thus helping investors make informed decisions based on reliable data.


Predictive Analytics: Utilizing historical data and machine learning algorithms, AI platforms can help identify trends, patterns, and future opportunities in ESG performance. Applying predictive analytics and AI to large datasets can help companies forecast future ESG risks, such as the likelihood of resource shortages. It can help companies benchmark against industry standards, and forecast future performance.


Deep Learning: Algorithms for identifying patterns in complex and abstract data using AI and Machine Learning can be developed to help companies uncover hidden relationships and trends in their ESG performance, leading to better decision-making.


Some potential use cases of AI in ESG reporting and compliance include the below:


Identifying ESG hotspots: By analyzing data from sensors, satellites, and other IoT devices, AI platforms can identify environmental “hotspots”, which are areas of high pollution, biodiversity loss, or resource scarcity. For example, satellite imaging using AI/ML techniques can identify hotspots for poor working conditions, which can be a data point regarding the social criteria for ESG. Similarly, AI-assisted data on air and water pollution levels can provide valuable insights for investors to detect whether there are communities facing health risks and also enable businesses to take course corrective measures. With AI-powered platforms which enable the regular monitoring of operations, companies can identify pollution events quickly and take corrective action to limit environmental damage.


Utilization of supplier data: Using supplier data, AI can help identify and mitigate ESG risks within their supply chain partners, such as labor violations or environmental non-compliance. This can help businesses identify sustainable supply chain partners within their production cycle.


Benchmarking Performance: AI can enable companies to analyze ESG metrics across locations, business units, and time periods. For instance, companies can compare their energy usage and waste generation metrics across their facilities in different geographies to identify best practices and underperformers.


An example of a company that leverages AI for providing ESG reporting solutions is Microsoft, which has launched Project ESG Lake, a data platform that collects and manages ESG data from multiple sources for reporting. It enables customers and partners to analyze their ESG data and create custom applications for tracking their sustainability progress. Users can utilize Microsoft’s AI-powered analytics platform, to predict the future emissions of their business operations. Additionally, Microsoft plans to introduce ready-to-use reporting templates for upcoming ESG regulations and standards, to ensure adaptability to emerging requirements in the field.


5.2The Promise of Blockchain for ESG Reporting: Transparency and Trust


Blockchain, a distributed digital ledger, provides a permanent and transparent record of transactions. This technology has the potential to enhance transparency and accountability in ESG reporting by providing a secure and immutable record for ESG-related data and transactions and hence shows significant promise.


Benefits of using blockchain include:


Data accuracy: Blockchain’s distributed and encrypted ledger makes it nearly impossible to manipulate data. This could help address concerns over the accuracy and integrity of ESG data, which often relies on a company’s self-reported disclosures. With blockchain, companies would have a verifiable and tamper-proof record of ESG data that could be audited.


Traceability and Trust: Blockchain can enhance traceability in ESG reporting by providing a secure and transparent record of transactions, emissions, and other ESG-related activities. As it provides a transparent and permanent audit trail of data, blockchain-powered platforms could allow stakeholders to trace the origin and journey of ESG data, and provide clarity into how the data was reported.


Stakeholder engagement and collaboration: Blockchain technologies can provide a platform for multiple parties to access and verify data in real time. The automation of data collection can be supported with other digital technologies such as the Internet of Things (IoT), which makes it possible for various devices to communicate with each other and share data and information without the need for human intervention.


Thus, blockchain allows companies to track the provenance and sustainability attributes of materials and products in their supply chains. This gives companies and consumers visibility into where products come from and how sustainably they are sourced and manufactured. The immutable and transparent nature of blockchain can thereby build trust in companies’ ESG disclosures.


A few potential use cases for blockchain in ESG reporting are:


Carbon traceability: Companies report their emissions in order to track their environmental impact and demonstrate their sustainability commitments.

Businesses are looking to blockchain technology to track carbon emissions across all their supply chain participants, at every stage of their supply chain. It involves collecting data on various sources of emissions such as energy consumption, transportation, and waste management. Capturing carbon measurement across all supply chain participants into an immutable ledger powered by blockchain technology, facilitates audit trails, assuring traceability, security, and accountability. Such a platform helps to trace the life cycle of a particular product, verify its origin and measure how the carbon footprints increment at each stage in the supply chain.


Carbon credit trading: Carbon credits are a way to measure and reduce greenhouse gas emissions by assigning a value to the amount of CO2 or other greenhouse gases released into the atmosphere. Each carbon credit represents one metric ton of CO2 or its equivalent. Companies or organizations can earn carbon credits by taking action to reduce their emissions. Companies can then trade or sell their credits to other companies that need to offset their own emissions and compensate for their carbon footprint. Blockchain can create decentralized marketplaces for trading carbon credits. Such platforms can connect buyers and sellers directly, eliminating the need for intermediaries and reducing transaction costs. By leveraging blockchain's transparency and security features, the credibility of the credits being traded can be ensured.


Several companies, including startups, are exploring the promise of blockchain technology by coupling their sustainability initiatives with it.


OpsChain ESG, launched by a major consulting and accounting firm, is a blockchain-based enterprise solution for recording and reporting carbon data. The solution utilizes the Ethereum blockchain, to convert the data related to emissions into a digital token, which is then placed in an online inventory for purchase and exchange.


Similarly, the Spanish-based energy firm Repsol has launched BlockLabs, a blockchain-based web application, for improving the safety certification of its products. Users can request sample certification through the application, which generates a digital file and registers it on the blockchain. The digital samples and their information are permanently linked to the physical samples. Once testing and certification are completed, the certificate details are recorded in the digital asset with a unique code. This process ensures the integrity and immutability of the information, preventing unauthorized changes.

Implementing this technology is expected to result in significant cost savings of 400,000 euros per year for the Tech Lab. Further, the tokenization of its supply chains related to petroleum refining and petrochemical products, makes it traceable and enables the automation of ESG reporting.


Another example is Starbucks, the global coffeehouse chain, which is planning to utilize blockchain to enhance its ESG compliance within its coffee supply chain. Starbucks launched an effort to provide customers with information about the journey of their coffee beans from farm to cup, recognizing that customers are increasingly interested in understanding the origins of their coffee and the ethical practices involved in its production. By leveraging blockchain, Starbucks can create a digital record for each bag of coffee, documenting key information such as the farm where the beans were grown, their processing methods, and their journey through the supply chain. This enables customers to access this information by simply scanning a QR code on their coffee package, empowering them to make informed choices, and enhancing transparency and sustainability in its coffee supply chain among all stakeholders, including farmers, suppliers, customers, and investors.


AI and blockchain technology can open new avenues for companies to analyze extensive environmental, social, and governance (ESG) data. While this synergy enables the identification of opportunities and risks, the adoption of these technologies also entails certain risks and challenges that need to be considered.




6.Potential Risks of using Emerging Technologies


While AI algorithms are valuable for identifying patterns and trends, there are various concerns regarding potential biases within these algorithms such as:


Data selection bias: If training data does not accurately represent the population being assessed, the algorithm's effectiveness can be limited across different regions or industries.


Algorithmic bias: If the algorithm's design or programming introduces biases, it could potentially undervalue certain ESG risks or favor financial metrics over social or environmental ones.


Human bias: Biases introduced by those developing and training the algorithm can seep in, potentially overlooking relevant data pertaining to ESG issues.


These biases can result in inaccurate assessments of a company's ESG performance. To mitigate these risks, comprehensive and representative data should be used, regular audits of algorithms should be conducted, and human oversight of AI systems should be present.


Blockchain technology also faces challenges around interoperability, privacy, and adoption. Certain risks and challenges associated with Blockchain technology are listed below:


●The immutable nature of data on the blockchain raises concerns about privacy and security, as errors or outdated information cannot be easily modified or removed.


● A lack of centralized control can make it difficult to enforce privacy policies or protect sensitive data.


● There is the potential for data breaches or cybersecurity attacks, although blockchains are generally considered secure.


To address these privacy concerns, permissioned blockchains, encryption methods, smart contracts, privacy policies, and regular security audits can be implemented. It is important to continuously monitor and address potential risks to ensure the optimal use of these technologies and improve ESG data management and reporting.


Further, there are also concerns about the energy usage of these technologies due to their computational demands and data center operations. To offset these concerns, energy-efficient algorithms, renewable energy adoption, energy-aware smart infrastructure, and green certifications can be implemented to reduce energy consumption and make these technologies more sustainable.




7.ESG Reporting of the Future: A Vision


Technology innovations are enabling more robust ESG reporting and disclosures through automated data collection, in-depth analysis, and real-time monitoring and reporting. By leveraging tools like big data, AI, and blockchain, companies, and investors can gain data-backed valuable ESG insights to better manage risks and opportunities.


For companies to successfully incorporate the use of AI and blockchain into their ESG practices, they must remain adaptable and responsive to continuing changes related to compliance regulations. By closely monitoring regulatory developments, and taking proactive measures, companies can leverage the benefits of these technologies to enhance their ESG performance.


However, while technology does bring benefits, it also brings risks around data privacy, security, and bias that companies must consider. With a strategic approach, technology can be used to augment human judgment in ESG reporting and help companies, investors, and stakeholders gain a more complete view of ESG risks and impacts.


In summary, emerging technologies are enabling more robust measurement, data collection, and reporting on ESG topics. As tech innovations continue to progress, businesses and investors will have access to real-time, data-driven ESG insights to support transparent sustainability reporting and continuous performance improvement for businesses.




Meet The Thought Leader



Laboni Singh is a mentor at GGI and is currently working at The Bridgespan Group as an Associate Consultant. She takes keen interest in socioeconomic development issues, public policy, and equity across different vectors of gender, caste, class, and ability, which in turn fuelled her transition from working at a global bank to the social sector. She is an Urban Fellow from the Indian Institute for Human Settlements, Bangalore and has a bachelor's degree in Economics from St. Stephen's College, University of Delhi.



Meet The Authors (GGI Fellows)




Anju Ann Joseph is currently an Assistant Manager with the Digital Trust Practice of KPMG India and has previously worked as a Senior Consultant with EY India. She has a keen interest in technology, innovation, and entrepreneurship. Her experience encompasses Information Security audits and attestations such as SSAE18 and SOC2 audits, IT SOX audits, and Internal audits. She graduated from Govt. Model Engineering College, Kochi with a major in Electronics and Communication Engineering. Further, she holds a Post Graduate Diploma in Management from T. A. Pai Management Institute, Manipal. In her personal time, she enjoys reading personal development and literary fiction books, exploring music, traveling and practising yoga.



Tanya Anand has worked as a research professional with various organizations, particularly in the social sector development & policy domain.

She has a strong interest in international relations, marketing & communications. She wishes to build her career in government consulting and public sector advisory. She likes to read, and watch movies, is a fitness enthusiast, enjoys discussions on philosophical concepts, and advocates mental and physical well-being.



If you are interested in applying to GGI's Impact Fellowship program, you can access our application link here.


 

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