IT professionals who are always looking to learn about trends and innovations in the corporate world are very interested in understanding the relationship between ESG (Environmental, Social and Governance or environmental, Social and governance in free translation) and the Artificial Intelligence, since efficient governance depends on cutting-edge technologies.
These concepts are transforming the way entrepreneurs, managers and investors analyze companies and make decisions. This is because they involve commitment, social and environmental responsibility, as well as innovation strategies aimed at productivity and competitiveness.
In this article, we will explain what ESG is and what is the relationship between this concept and Artificial Intelligence. We will also show the importance of investing in solutions and tools to optimize the use of these concepts in the corporate environment and how Venturus solutions they can help in this regard. Continue reading to learn more!
What is ESG?
The acronym ESG, which as mentioned means environmental, Social and governance, appeared in 2005 in the report of the Global Compact ” Who Cares Wins”. For the preparation of this document, the UN brought together 20 financial institutions to create recommendations on how to include these ESG issues in asset management, brokerage and related research services.
The report concluded that the adoption of ESG causes in the financial market encourages organizations to be more sustainable and contributes to a better development of society. In this way, the concept is used to demonstrate how committed an organization is to developing its operations in a more sustainable way.
In this sense, each letter of the acronym involves a large list of global concerns that are the pillars of this concept. Aspect environmental for example, it deals with sustainable development as well as the preservation of the environment, including topics such as:
- biodiversity conservation;
- energy efficiency;
- carbon emission;
- water scarcity (mainly drinking);
- climate change;
- air and water pollution;
- solid waste.
Already the social it cares about the relationship of the company with the people involved, such as employees, customers and communities, in the sense of:
- ethnic-racial diversity of the team;
- employee engagement;
- privacy and protection of sensitive data;
- respect for human and labor rights.
Finally, the aspects of governance they include the management of the company with regard to:
- fighting corruption;
- composition of the administrative board;
- complaints channel;
- corporate ethics and morals;
- strategies of data management master;
- relationship with governments, politicians and government entities;
- executive remuneration.
The relevance of the ESG concept
Second search on sustainability conducted in 2018 by Anbima (Brazilian Association of financial and Capital Markets entities), 85.4% of investment managers use ESG criteria in making their decisions.
This concept becomes increasingly relevant because managers, at a global level, see the opportunity to adapt to related practices and seek long-term sustainability, with the possibility of transforming the world into a better place for the next generations.
These are attitudes and postures that will lead to greater preservation of nature, improvement in interpersonal relationships and a healthier management of business, with the adoption of this concept in the present. At the same time, organizations that invest in ESG also gain from increasing their competitiveness.
What is the relationship between ESG and Artificial Intelligence?
To make ESG investments, asset managers are adopting ways to use Artificial intelligence (AI) and Big Data to optimize investment decisions. In this way, they consider that it is possible to limit the subjectivity and cognitive bias that sometimes arises from people-led analysis.
These innovations have begun to be applied in ESG sustainability insights as sources of” alternative data ” that complement key financial information, using information found on the Internet. In this sense, AI is already being used for social good, indicating that the joint use of the concepts of ESG and AI can generate several benefits to organizations, as we will comment below.
Guidance through data
The empirical and metrics-driven nature of ESG leads to the understanding that data and AI need to play a central role in the collection, verification and analysis of ESG performance. sustainability. However, regardless of a company’s sustainability goals, a data-driven ESG strategy can increase its level of transparency and trust if it follows some quality principles, such as:
- comparability-data can be grouped and compared on a relative basis;
- frequency-data can be collected in batch, almost in real time or this way for timely reporting;
- materiality-weightings are directed at various data points based on business relevance as well as industry or geography specific factors;
- objectivity – data collected from diverse and traceable sources to decrease biases and greenwashing.
Optimization of structuring
Considering the amount of text that needs to be analyzed for the disclosure of corporate sustainability or about the insights that need to be taken from social media, it is observed that it is impossible to handle the data manually, requiring the process automation.
To this, we can add the complexity of data collection to the needs to bring relevant (and material) external data sources as well as alternative datasets for ESG analysis. Thus, centralizing them in a cloud-based data lake with an agile data governance process is the most practical solution for organizations to optimize data access and the quality of ESG-related information.
Analysis of important metrics
Once the various data sources (structured, unstructured, and alternative) are managed and selected in the cloud-based data warehouse, companies can perform analytics to gain a holistic view and understanding of their ESG performance.
Why invest in solutions and tools to optimize these concepts?
By adopting processes and mechanisms that protect information throughout the lifecycle of each stakeholder, companies ensure good data governance. However, it is paramount that the information is accurate and that the protected data is reliable.
For this, it is essential for companies to invest in solutions and tools, since they allow better application of ESG and AI concepts in business development. Here’s how important these technologies are in this regard!
Prevention of fraud, tax risks and human failures
ESG practices related to governance optimize resources on several fronts, including the use of technologies for risk prevention. This is because if the administrative, tax and accounting processes are well mapped, the company can obtain ease to deliver its ancillary obligations. In addition, it prevents risks of irregularities in invoices, rework and human failures in cadastral and tax analysis operations, among others.
Attracting new investors
The main motivation for the elaboration of the ESG pillars was the incorporation of new principles for the analysis of financial investments. In this sense, by ensuring that environmental, social and governance principles are applied in the company (making this public to the market), the tendency is for the organization to prove interesting to investors and achieve good results.
Increased productivity and profitability
The pillars of ESG are also directly linked to reducing costs and, consequently, increasing profitability. Thus, investing in solutions that increase team productivity brings benefits to companies in these aspects. In addition, there is a gain in the confidence of consumers who come to see them as organizations that care about the well-being of society and the preservation of the environment.
But to obtain all these advantages and ensure good data governance, it is essential to choose a good provider of technological tools, such as Venturus, which offers cutting-edge technology in the development of applications and solutions for various industries, such as industry, segments of the welcome and logistics.
As we have seen throughout this article, there is a close relationship between the concepts of ESG and AI, since companies concerned with the socio-environmental impacts of their actions need to invest in technological solutions. This is because they are critical to ensuring the collection, treatment, analysis and storage of data securely.
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