Green finance is a primary focus for the many companies working toward emissions reduction targets. It involves making financial decisions with sustainable development in mind, such as investing in renewable energy or issuing loans tied to carbon offsets. In Southeast Asia, considerable attention has been paid to sustainable financing, as evidenced by the establishment of organizations like the Singapore Green Finance Centre (SGFC).

While there are a plethora of ways to “greenify” financial decision-making, one recurring theme is the use of Artificial Intelligence (AI). AI is used for anything from assessing a company’s climate risk to identifying instances of greenwashing.

Green Finance Initiatives

Financial institutions in Southeast Asia have been ramping up their green financing efforts. Three prominent examples come from UOB, OCBC, and RHB.

• UOB provides logistics companies with loan rate reductions of up to double-digit basis points for achieving emission reductions. In collaboration with Enterprise Singapore, UOB offers the Sustainability-Linked Advisory, Grants, and Enablers (SAGE) program, which provides sustainability-linked financing opportunities for Small and Medium Enterprises (SMEs).
• OCBC has launched the OCBC 1.5°C loan to encourage businesses to establish and pursue carbon emissions reduction goals aligned with internationally recognized, science-based net-zero decarbonization pathways specific to their industries. Companies that meet these targets will benefit from lower financing rates.
• RHB has introduced a Green Financing initiative, offering competitive interest rates and reduced monthly installments for new and existing customers who partake in sustainable practices such as purchasing an Electric Vehicle (EV), constructing an eco-friendly building, or adopting clean energy sources.

How AI Promotes Green Finance

As Southeast Asian companies increasingly link finances with sustainability, AI-based technologies will be critical. Climate tracking software infused with AI can facilitate Environmental, Social, and Governance (ESG) integration, perform climate risk modeling, identify sustainable investment opportunities, and accurately verify a company’s eco-friendly claims.

• Enhance ESG Integration: Before investing in a company, financial advisors can accurately evaluate the company’s sustainability performance with AI algorithms. AI tools can analyze emissions data and cross-reference them with ESG factors to determine the company's environmental risks. Moreover, AI-driven analytics help investors prioritize ESG when creating a portfolio or purchasing green bonds.
• Perform Climate Risk Modeling: AI and Machine Learning (ML) tools empower organizations to take a proactive approach toward addressing climate-related challenges. AI algorithms can unify vast sums of disparate data for simplified analysis. For example, banks can use ESG risk and due diligence software like GreenFi to eradicate more than 80% of false positives of potential clients based on company data analysis.
• Pinpoint Sustainable Investment Opportunities: AI can scan climate disclosure reports, news articles, and social media to better understand ESG practices and emerging trends. In turn, these AI-driven insights assist investors in aligning their portfolios with evolving dynamics and conditions. AI algorithms are also useful for identifying patterns, predicting future outcomes, and assessing the financial impact of green investments.
• Identify Green Washing Practices: Many companies claim to be green, with little to no evidence to support that claim. AI and Natural Language Processing (NLP) are adept at analyzing company information and detecting inconsistencies or contradictions regarding sustainability. This AI use case is essential for financial institutions that want to steer clear of companies that only speak of sustainability for marketing purposes and fail to implement emissions-reduction tactics.  

Financial Decisions Start with Sustainability Goals

Investors and potential customers alike are increasingly preferential toward companies that demonstrate their commitment to building a sustainable planet. Financial decision-making is the catalyst for every business project imaginable. Whether executives at a hedge fund are discussing potential companies to acquire or a manufacturing plant wants to transition to renewable energy, a transaction must be made. In this vein, it’s only natural to bake sustainability into all things finance to support climate goals. Where can your company improve in terms of decarbonization? How well does a potential partner adhere to climate regulations? Questions such as these, once a mere afterthought among upper management, are now starting points in many discussions.

But relying solely on human intellect is a mistake if you want to ensure the most optimal outcome. AI-based software tools can shed light on things that humans cannot. AI identifies trends and patterns that the human eye would never see. What might look like a great investment on paper could very well be a disaster lurking in the shadows. Whatever the goal may be, AI is an invaluable technology for any firm aiming to streamline finance decision-making and maximize its positive impact on the environment.

For a more thorough assessment of how companies’ sustainability goals, such as green finance, can be supported with AI tools, download the report: Leveraging AI and ML for Sustainable Growth in Southeast Asia. The report dives into the latest AI innovations, recent activities, key use cases, and notable solution providers.

About the Author

  Rachel Kong, Research Analyst

Rachel Kong is a Research Analyst within ABI Research’s Asia-Pacific Advisory team, focused on issues related to sustainable technology implementations and digital transformation. She conducts research and analysis on areas such as sustainable software and the carbon footprint of key emerging technologies driving sustainable growth. Rachel also monitors key technological developments within the Southeast Asian region as part of the Southeast Asia Digital Transformation Research Service.