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BUSINESS TODAY 31 August 2023

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8 OPINION 31.8.2023 Machine learning practices into ESG strategy Mohammad Reza Mousavi Mohammad Reza Mousavi is an Advisory Intern at PKF Malta, an audit and consultancy firm, and has over 25 years' experience in accounting, taxation, financial and consultancy services M achine learning, a subset of AI, enables computers to learn from data and predict outcomes without explicit programming. It encom- passes supervised (labelled data for pre- diction), unsupervised (finding patterns in unlabelled data), and reinforcement (learning through actions and rewards) learning. It powers diverse fields like language processing, computer vision, and auton- omous driving, continually advancing with more complex algorithms and larg- er datasets. As businesses and industries embrace its potential, machine learning drives innovation, from personalized recommendations to medical diagnoses, revolutionizing how we interact with technology and data. On the other hand, ESG stands for En- vironmental, Social, and Governance. It's a framework used to assess the sustaina- bility and ethical practices of a company or organization. ESG criteria are used by investors, stakeholders, and analysts to evaluate how well a company manages its impact on the environment, its relation- ships with employees, communities, and other stakeholders, and the quality of its governance and leadership. Environmental factors include things like a company's carbon emissions, wa- ter usage, and waste management. Social factors encompass issues like diversity, employee treatment, and community en- gagement. Governance involves assessing the company's leadership, ethics, trans- parency, and overall management prac- tices. e integration of machine learning (ML) with ESG strategies holds the prom- ise of reshaping corporate sustainability practices. ML, with its ability to process and analyze vast amounts of data, has in- deed revolutionized business operations, providing insights that were previously unattainable. Concurrently, ESG consid- erations have become integral to corpo- rate strategies, reflecting the growing ac- knowledgment of businesses' societal and environmental responsibilities. is essay delves into the intersection of ML and ESG strategies, exploring the potential benefits and strategies for amalgamation. ESG data, crucial for measuring a com- pany's sustainable performance, often suffers from data collection inefficiencies and inaccuracies, as mentioned in the provided text. Traditional methods like surveys are labor and time- intensive and subject to human errors. ML addresses these issues by efficiently collating and processing diverse datasets from sources such as social media, news articles, and financial reports. ML's impact is particularly pronounced in the realm of investment decisions, where ESG factors play an increasing- ly influential role. As stated in one of the provided texts, investors recognize ESG indicators as valuable predictors of a company's long-term sustainability. Machine learning algorithms scrutinize multifaceted ESG data, revealing hidden patterns and correlations. is capability empowers investors to make informed decisions aligned with their values and financial interests. Additionally, research from MSCI demonstrates that companies with strong ESG performance tend to ex- perience lower volatility, suggesting that integrating ML-enhanced ESG insights could lead to more stable investment re- turns. Predictive modeling, facilitated by ML, further amplifies the impact of ESG strat- egies. By analyzing historical ESG data and external variables, ML algorithms predict a company's future performance in ESG domains. For instance, a compa- ny aiming to reduce its carbon footprint can utilize ML to identify areas with the greatest potential for improvement. e resulting data-driven insights inform stra- tegic decision-making, aligning business operations with sustainability objectives. Research by Harvard Business Review affirms that predictive modeling through ML enhances the efficacy of ESG strat- egies, aiding in identifying high-impact sustainability interventions. Moreover, ML can bolster transparency and accountability, crucial facets of effec- tive ESG reporting. Advanced analytical capabilities of ML algorithms ensure ESG data's accuracy and reliability, building trust among stakeholders. Additional- ly, ML facilitates real-time monitoring of ESG metrics, enabling companies to promptly identify deviations from estab- lished targets. PKF Malta, a trailblazer in ESG initia- tives, has taken the proactive initiative to orchestrate a series of ESG conferences. ese conferences have been strategi- cally structured to navigate the path to- wards fostering a more sustainable local economy. e E and S facets of ESG were already comprehensively addressed on April 12, 2023 and June 27, 2023, respec- tively, while the forthcoming months will witness the focused deliberation on the G aspect of ESG. e core intention driving these confer- ences is the creation of a dynamic and in- teractive platform that facilitates substan- tial dialogues. is platform serves as a catalyst for stakeholders to not only iden- tify potential solutions for the future but also to engage with the imminent social issues and challenges. is engagement occurs within the broader context of both macro and micro perspectives. Diversity is paramount in our selection of speakers, who represent a spectrum of fields. ese include prominent fig- ures from the business sector, esteemed scholars, perceptive sociologists, and influential policymakers. Among the distinguished speakers were Dr Michael Falzon, the Minister for Social Policy and Children's Rights, and the esteemed Hon- orable Claudette Buttigieg, the shadow minister overseeing Civil Liberties, Social Dialogue, and Diabetes. PKF Malta is also leveraging its mem- bership with PKF International to further learn and contribute within the field of ESG reporting, auditing and advisory ser- vices. PKF Malta also boasts that one of its staff members forms part of the PKF international ESG Steering committee. PKF International is setting forth a holis- tic approach with respect to its members' service offering which will enable PKF members to offer their clients a global outlook when it comes to ESG, covering most of their requirements. is is espe- cially useful with multinational compa- nies which would be required to report non-financial data in different jurisdic- tions in a comprehensive manner. PKF International's bringing together experts in different fields of ESG pillars from within PKF members to create a database of information and subject matter ex- perts. ere are also efforts underway to identify software and subscription based online ESG tools for all its members. With this system, member firms can then take on clients with different and complex needs, having the knowledge that they can reach out to subject matter experts from within other member firms. When it comes to ESG services, collaboration is key and PKF Malta has already collabo- rated with members of other PKF firms when it comes to ESG. In closing, combining machine learning and ESG strategies holds great promise for companies wanting to bolster sustain- ability. ML's precision with data, predic- tive modeling, and transparency aligns seamlessly with multifaceted ESG con- cerns. is union empowers better deci- sions, engaged stakeholders, and sustain- able operations. As tech advances, their synergy will drive positive change for a more sustainable future.

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