The role of artificial intelligence in sustainable finance

ABSTRACT

This Special Issue includes several articles on a variety of issues related to sustainable development, ESG investing and the role of Artificial Intelligence in helping creditors, investors and business managers in making optimal decisions to ensure long-term financial sustainability. In this context, it can be argued that it is necessary to consider the challenges and opportunities presented by AI in providing solutions to sustainability issues. In addition to outlining the articles in this Issue, this Editorial provides new insights from the literature on the importance of AI applications and models, for sustainable investments and understanding the value of AI beyond a problem-solving tool.

KEYWORDS:

• Sustainable finance
• artificial intelligence
• sustainability
• CSR reporting
• ESG

1. Introduction

Sustainability involves the adaptation of today’s business model to the dynamic nature of the current digitalized environments. In other words, corporations need to make sure that resources, especially technology, are being used responsibly and efficiently to improve the lives of the present generations and future generations as well as strengthen their relationships with the environment. In 2020, the United Nations estimates an investment in the range of $5 trillion to $7 trillion to achieve the SDGs (Craig 2021). This calls for a broader understanding of the behavior of investors, and how these investments are used towards solving sustainability-related problems such as poverty, environmental degradation, pollution and inequality.

Artificial Intelligence (AI) has the potential to address these societal problems including sustainability. The climate crisis and the degradation of the physical environment are complex problems that require the most innovative and advanced solutions. The real value of AI hence lies in its ability to facilitate and foster environmental and social governance, rather just as a tool to reduce pollution, poverty and resource depletion (Nishant, Kennedy, and Corbett 2020). The financial sector including institutional investors plays a substantive role in this challenge because they have the task of financing the investments and technologies needed to transform our economy into a sustainable one (Chayjan et al. 2020; Alonso and Marqués 2019). Accordingly, many countries around the world have developed their own plans to increase investments in clean resources which can develop the economy and have high contributions to sustainability goals.

In the age of Artificial Intelligence (AI), societies depend on big data, social media, knowledge management and data science to survive and achieve these sustainability goals. This rapid expansion of intelligent systems will increase the quantity of financial data produced, the demand for accounting and financial solutions for emerging issues, will increase demand on well-educated and skilled accountants who can operate the financial-based artificial intelligence systems (Musleh Al-Sartawi, Razzaque, and Kamal 2021; Shihadeh 2020). In this context, sustainable investment has grown in importance over the last several years and has attracted increased attention from academics, researchers and policymakers (Memdani 2020; Krüger, Sautner, and Starks 2020; Al-Sartawi 2020b; Barber, Morse, and Yasuda 2021; Bauer, Ruof, and Smeets 2021; Hannoon, Al-Sartawi, and Khalid 2021). Nonetheless, understanding why people invest sustainably is important not only to academics but also to institutional investors, who often invest on behalf of individuals, especially in the light of the growing importance of AI in solving sustainability issues. Therefore, this Special Issue extends on this need in the literature and provides a platform for debating several significant issues, considerations and mechanisms of AI for sustainable finance.

A thorough review of relevant literature indicates a rise in awareness surrounding AI and sustainable development investments. In this sense, various questions arise about the extent to which AI affects businesses and the role it must play in helping investors and stakeholders to take optimal decisions and supporting the organizational efforts in protecting the privacy of the users and customers through preventing cyber-attacks (Musleh Al-Sartawi 2022; Al-Sartawi 2020a). First, it is crucial to study the impact of AI on financial reporting (Türegün 2019). AI helps investors to collect, analyze and interpret more information than ever before when accounting for environmental, social and governance (ESG) related risks and opportunities facing companies as well investor portfolios. It also allows sustainable investors to process massive amounts of data, big data, that hold crucial information for ESG investing. Second, through AI, computer algorithms that have been developed and fine-tuned to find and analyze content can digest all of the information available about a company, which can be a huge and almost impossible task for human employees to do efficiently and in a timely manner (Kumar et al. 2022; Al-Sartawi et al. 2022). Similarly, sentiment analysis is currently automating tasks that would have been impossible to be conducted by humans even a few years ago giving rise to novel ethical considerations not excluding psychological and sociological effects (Al-Sartawi 2021). Hence, the discussions in this Special Issue should consider these areas, their opportunities and challenges, and list propositions for research and practice.

The reason for selecting this topic for the Special Issue (SI) is both professional and personal. It is my experience as an academic, researcher and editor, which urged me to choose the current topic in a technology-driven economy. I firmly believe, on the one hand, that sustainable investments and sustainable business models can be achieved by acknowledging the importance of CSR reporting, ethical considerations of AI, assessing ESG risks, and the future of AI and FinTech. Consequently, the major objective of this SI is to provide a platform for researchers to shine new light on these debates. This SI is structured as a comprehensive reference covering theoretical and practical aspects across multiple domains pertaining to the integration of AI into ESG reporting and its role in investment decisions. It provides an original contribution by prioritizing ESG factors in the decision-making process of investors based on AI algorithms. I hope that my Special Issue will encourage further research into the relationship between sustainable finance, Artificial Intelligence and economic growth without introducing long-term threats to environmental sustainability. Moreover, future research could examine the need for regulations and AI governance systems in corporations from multi-perspectives.

The rest of the Editorial is structured as follows. Section 2 reviews the importance of sustainable finance and the role of AI in helping investors in decision-making. Finally, Section 3 presents the main papers in this Special Issue and their contribution.

2. The importance of AI for sustainable finance

There is little doubt that humanity has taken a huge leap forward in the field of robotics and Artificial Intelligence. During the 1950s, after World War 2, the research on Artificial Intelligence (AI) started emerging when scholars tested the extent to which machines could compete with the processes of human beings (Al-Sartawi et al. 2022). The 1960s brought about a decade of intensified research on AI, reflected in projects pertaining to chess games and robotics (Haenlein and Kaplan 2019). Recently, research studies have introduced the Expert Systems and Neural Networks which imitate human behavior, such as learning, cognitive logic rationalizing, problem-solving and computational intelligence, and using mathematical tools mimicking the natural surroundings (Benetti 2014). Within the context of businesses, financial reporting will see a stronger change thanks to machine learning, artificial intelligence, blockchain and big data usage in the next 20 years. That is with the intersection of artificial intelligence and blockchain, it is now clear that in the near future the work of the accounting profession will be supported by automation (Türegün 2019).

Despite AI systems not being able to replicate human intelligence, it can provide accurate outputs that can far replace human efforts (Duan, Edwards, and Dwivedi 2019). In accounting, we need to analyze the strengths and the limits of AI systems to make it useful in solving accounting and business problems and to determine the training and skills needed to allow accountants to easily control intelligent systems. When accountants start operating the related AI systems, they will be capable to enhance their competences and produce quality financial reports for investors. In particular, the potential of AI, by combining algorithms, fuzzy models, prediction models and data analytics, to support sustainable finance is ripe. Investor groups demand more comprehensive financial reporting from firms and accountants. This act of integrating ESG data in the investment management business has come to be known as sustainable finance or investing (Berg, Fabisik, and Sautner 2020). Sustainable finance has emerged as an important concept at the convergence of finance and the sustainable development goals (SDGs). However, according to (Kumar et al. 2022) this definition, which is limited to ESG factors, is very narrow. Accordingly, this SI proposes that the term sustainable finance should incorporate all activities and factors that would make finance sustainable and contribute to sustainability including Artificial Intelligence systems, applications and models.

AI systems will increasingly be part of daily lives raises in the near future, and this raises the question of whether regulation is needed and in which form. Haenlein and Kaplan (2019) argue that regulations need to be considered from multiple perspectives. These include micro-perspectives (regulation with respect to algorithms and organizations), and meso-perspectives (regulation with respect to employment). This SI identifies this as an area for future research which could be examined further in terms of AI’s roles in sustainable finance, its impact on both organizations and societies, and the considerations of the automation of the accounting profession.

3. Outline of articles in the Special Issue

This Special Issue presents various papers that aim to address some of the issues highlighted in the aforementioned sections. The papers published in the Special Issue use a variety of methods, including literature reviews, prediction models, indices and quantitative checklists. In addition, the papers cover multi-disciplines, including Information Technology and systems, Computer Science, economics and finance; and provide policy recommendations for promoting AI and big data analytics for sustainable finance. However, each paper complements the other as they are all focused on using AI for sustainable finance.

The paper ‘Fuzzy Confrontations of Models of ESG Investing versus Non-ESG Investing Based on Artificial Intelligence Algorithms’ (Doubravsky 2022) examines the Environmental, Social and Governance (ESG) parameters used by investors in decision-making from a fuzzy model perspective and based on AI algorithms. The study found that there is slight compatibility between dominantly ESG-related investing tools and non-dominantly ESG-tools. Moreover, the researcher concluded that most similarity is shown by stock indices that are in line with usable investing.

Another paper ‘The Role of Blockchain Technology in the Integration of Sustainability Practices across Multi-tier Supply Networks: Implications and Potential Complexities’ (Najjar 2022) attempts to explore the management and integration of sustainable practices amidst complex multi-tier supply networks through implementing blockchain. The results of the literature analysis indicate that by using blockchain, managers will have increased transparency and traceability of their multi-tier supply networks. This leads to reduced information asymmetry, limit opportunistic behaviors and mitigate uncertainty across their lengthy supply networks. In addition, the connectivity and the information-sharing features associated with blockchain will increase suppliers’ predictability. Thus, creating robust multi-tier sustainable supply networks.

On the other hand, the paper ‘Application of Artificial Neural Networks in predicting financial distress in the JSE financial services and manufacturing companies’ (Muzindutsi 2022) aimed to explore the role of artificial intelligence (AI) in predicating the financial distress of companies using Artificial Neural Networks (ANN). The sample included financial services and manufacturing companies listed on the Johannesburg Stock Exchange (JSE) for the period 2000–2019. This study presents important theoretical and practical contributions to the current literature by highlighting the potential role of AI models in solving financial problems. Furthermore, the models built in the study could be used by creditors, investors and business managers as a tool for decision-making and ensuring long-term financial sustainability.

Moreover, the paper ‘The pertinence of incorporating ESG ratings to make investment decisions: A quantitative analysis using Machine Learning’ (Sharma 2022) aimed to determine if including ESG data points is conducive to profitable investments while promoting sustainability. The researcher collected unique ESG and financial data of 1400+ companies from 34 stock markets internationally. The study follows employed quantitative analysis with the aim of determining whether the qualitative aspect of sustainable investments is equivalent to financial parameters that are considered while making decisions about investment. The dataset is unique as it houses other measures of sustainability along with general ESG scores available online. The study concluded that better ESG scores indicate better financial performance.

Disclosure statement

No potential conflict of interest was reported by the author(s).