Finance Minister Nirmala Sitharaman announced in her Budget 2024 speech that the government would develop a “taxonomy for climate finance” to enhance the availability of capital for climate adaptation and mitigation. While this is welcome, it is only the proverbial first step.
The future of climate finance revolves around AI. It can streamline operations, reduce costs, and make financial institutions more efficient.
The AI Knowledge Consortium, launched in March, convened a conference in Goa titled ‘Catalysing AI for Climate Action and Finance’. Discussing the escalating climate challenges and the increasing role of artificial intelligence as a tool for climate action, it was a timely initiative to bring the stakeholders on a common platform.
Complexities in climate finance
Recent data shows a worrying decline in the land carbon sink, with forests absorbing significantly less carbon in 2023. The Intergovernmental Panel on Climate Change (IPCC) has warned that limiting global warming to 1.5 degrees Celsius above pre-industrial levels would require greenhouse gas emissions to be reduced by 43 per cent by 2030. This necessitates a 9 per cent annual reduction, much higher than the current 2 per cent.
As they attempt this, emerging markets and developing economies (EMDEs), including India, face a steep challenge. They need substantial financial support to build climate-resilient infrastructure and meet their nationally determined contributions (NDCs) by 2030. Despite a 2009 pledge by advanced economies (AEs) to provide $100 billion annually to EMDEs for climate action, actual assistance remains sparse.
An IMF paper estimates that achieving the Paris Agreement’s goals will require $3-6 trillion annually until 2050. Currently, global climate finance stands at about $630 billion per year.
Increasingly engaging with climate change issues, the G20 adopted its report G20 Expert Group on Strengthening MDBs in June 2023. The report recommends a $3 trillion annual increase in multilateral development banks’ (MDBs) spending by 2030—including $1.8 trillion toward climate action. However, MDBs offer concessional loans and add to the global debt, which hit a record $307 trillion in 2023, a whopping 336 per cent of the GDP.
Private sector engagement is crucial, yet its capacity to finance green projects is limited. Between 2016 and 2021, only $120.8 billion was mobilised from the private sector, further highlighting the gap.
Also read: Climate financing could be key focus area at COP29. What it is & where India stands on negotiations
How AI can help
In this context, artificial intelligence (AI) emerges as a transformative tool for climate finance, offering solutions for better decision-making, resource optimisation, and enhanced financial mechanisms to support sustainable initiatives. It can analyse vast datasets to assess climate risks accurately, aiding insurers and financial institutions in pricing risk and making resilient investments. Thus, AI can drive climate finance by exponentially improving risk assessment and management.
AI algorithms can also help optimise investment portfolios by prioritising green investment opportunities over high-risk, carbon-intensive assets, balancing financial returns with environmental impact. Through its analysis of data trends, AI can uncover high-potential, underfunded areas for investment.
Financial institutions worldwide need to be more efficient, and AI can help by streamlining operations and reducing costs. This will ultimately speed up the approval of climate finance proposals.
One of the most critical areas of climate finance is risk pricing. AI can develop accurate pricing models for climate risks to reflect financial products’ actual costs. Green bonds and sustainable finance require a greater push to increase funds flow. AI can raise investor confidence by automating compliance and reporting processes, and ensuring that funds are used for their intended purposes.
Considering the need to design and promote innovative financial instruments to direct retail investments into climate finance through capital markets, AI can be most beneficial in promoting structures like infrastructure investment trusts (InvITs). Straddling the capital markets and institutional finance regulatory universe, InvITs are designed to unlock investors’ investment appetite through the instrumentality of capital markets in the form of debt and equity.
AI can optimise pricing for units of structures like InvIT, facilitating a smooth transition between debt and equity or public and private finance. It can also provide comprehensive real-time information on the performance (including financial) of projects held by these structures for robust forecasting and transparency. This can help tap into the vast global retail investor market.
With a creative and attractive tax structure and robust risk matrix, InvIT-type structures can create circularity between public and private finance, as well as debt and equity, which is one way to bridge the green resource gap in the foreseeable future.
Impact measurement and reporting are other areas in which AI can contribute significantly. It can enhance the measurement of climate finance initiatives’ impact, attracting more investors through transparency and accountability. It can ensure funds are used effectively by monitoring and verifying the impact of investments. Similarly, compliance with fraud detection and climate finance regulations can also be improved with AI.
Also read: Climate change doesn’t just affect poor people, farmers. Cities and banks aren’t safe either
Challenges to integrating AI
Leveraging AI for climate action also poses several challenges. Reliable AI models depend on accurate, comprehensive, and high-quality data, necessitating stakeholder collaboration. It is also vital to be aware of the ethical and bias concerns by ensuring that the AI algorithms used are transparent, fair, and inclusive, which is crucial to avoid reinforcing existing disparities.
The most glaring challenges, however, are technical and infrastructural. EMDEs may need vast resources for effective AI implementation, necessitating efforts to bridge the digital divide. Robust regulatory and policy frameworks are also required to guide the responsible use of AI and protect the interests of EMDEs.
Future directions for climate finance include interdisciplinary collaboration, public-private partnerships, capacity building, and scalable AI solutions.
Integrating AI into climate finance can enhance decision-making, resource management, and investment strategies, helping address climate change more effectively. But to realise this potential, concerns regarding data quality, ethics, infrastructure, and regulatory frameworks must be confronted.
With concerted efforts, AI can play a transformative role in creating a sustainable future. Policymakers in India and other EMDEs must accord this the highest priority.
Arvind Mayaram is a former finance secretary to the Government of India and chairman of the Institute of Development Studies, Jaipur. Views are personal.
(Edited by Prasanna Bachchhav)