Emerging markets are ripe with opportunities for large-scale forestry, afforestation, and nature conservation projects amidst growing demand for nature-based solutions (NbS). How would those projects be effectively scalable and economically viable for institutional investors? This article talks about how AI changes the landscape in efficiently sourcing, evaluating, and managing high-quality NbS projects, especially in emerging markets, as investments for the Natural Capital funds (NCFs) based in the Global North.
With more than a decade of experience in investment banking and asset management in particular, I bring a singular perspective to climate finance as the founder and chief executive officer of Calculus Carbon, a Temasek-backed company focused on mobilizing capital for large-scale NbS projects across the Global South. My work has always focused on scaling innovative investment solutions in asset-heavy industries, having managed a USD 2.2 billion Real Estate Private Equity Fund, and currently working with leading asset managers across EU, UK, and Singapore, having built an order book of over USD 120 million.
Unlocking the Potential of Nature-Based Solutions in Emerging Markets
Afforestation, mangrove restoration, and peatland preservation are some of the nature-based solutions that will have high relevance in the fight against climate change. These can cumulatively contribute 1/3rd towards achieving the mitigation outcome required to meet the Paris Agreement goals by 2050. However, for these projects to attract institutional capital, they will need to be identified as a stable class of investment with measurable impacts and returns. That is particularly pertinent for emerging markets, which do hold distinct advantages regarding land availability and biodiversity but can also pose some significant challenges regarding regulatory and operational risk.
Artificial Intelligence and Market Efficiency
There is no doubt that artificial intelligence offers significant tools to address some of the principal inefficiencies in the predominantly voluntary market of nature-based solutions. This results in a preference for rich economies, particularly UK, EU, Japan, South Korea, Singapore for investing in projects in the Global South (SE Asia, Africa, Latin America) owing to reduced costs of achieving a unit of climate mitigation.This geographical dispersal however adds significantly to the informational asymmetry between the institutional investors in the Global North (NCFs) and the NbS project developer.
AI-powered platforms help simplify sourcing, risk assessment, and stand-alone project quality to meet the threshold standards to be bankable by institutional investors. Here are a few ways:
- Data-Driven Project Evaluation
It can consume huge volumes of data, including satellite imagery, local country environmental impact data, and climate models to evaluate the viability of projects at scale. This helps significantly increase the pace of the project evaluation with more accurate information about the carbon sequestration potential and biodiversity benefits. The use of machine learning algorithms in automatically analyzing historical data of how the project has panned out, helps further improve the predictability of project success, thereby lowering investment risks.
- Efficient Demand-Supply Matching
The very concept of a two-sided marketplace depends on accurately matching supply i.e. NbS projects and demand i.e. NCFs. AI-driven platforms similar to what we deploy internally at Calculus Carbon help achieve just that via using an NCF’s investor thesis, along with an understanding of their ability to underwrite certain risks, in real time to identify NbS projects across the globe that fit those criteria. This affords us a more dynamic, data-driven and accurate matchmaking, reducing the time and cost of searching for suitable projects for potential investors.
- Quantifying Risk and Impact
AI helps quantify certain specific macroeconomic risks which are inherently qualitative in nature. These include socio-political factors and environmental threats to regulatory framework, in particular. Deploying AI in analyzing these factors helps create a relative quantitative risk profile of the project, enabling an investor to understand and manage those risks more efficiently. These macroeconomic risks are particularly relevant given the scope of investment opportunities and NbS projects are predominantly based in emerging economies in the Global South, often in countries which historically haven’t been the beneficiary of institutional investments at the scale of individual projects, which are now seen in carbon markets. possible at a much finer level, mainly in projects dealing with emerging markets where regulatory environments might constantly be changing..
Furthermore, leveraging AI helps standardize the impact metrics in the NbS projects highlighting not just the relatively easier environmental objectives (carbon sequestration) but also the investor expectations of qualitative environmental, social and governance standards, reflected increasingly in the premium pricing of NbS projects that meet one or more additional of the UN’s 17 Sustainable Development Goals (UN SDGs).
Building traction in a two-sided marketplace involves specific nuances, further amplified in the case of climate finance, where buyers (NCFs) and sellers (NbS projects) are structurally dispersed geographically. Aligning the two on multiple qualitative components of each project can be helped to an extent via AI. Calculus Carbon, for instance, uses its proprietary investment framework to provide NCFs with detailed insights into the risks inherent in their pipeline projects and ways to mitigate them, while supporting project developers in designing their project to better align with the investment thesis of the individual NCFs.
Key Strategies in Building Traction
Investor aligned sourcing (powered by AI): AI allows us to customize our pipeline to align with the needs of a particular NCF, thereby helping retain them on the platform. Each NCF places varying weights on different components of their thesis, which we incorporate into our algorithm post each of our NCF interactions.
Building trust via dynamically parameterizing key factors: Trust is paramount in the context of a marketplace, further accentuated by serving institutional clients on either side of the platform . We enable trust among NCFs and NbS projects alike through intelligent project sourcing and baking in crucial aspects of each client’s requirement in our algorithm.
Documenting insights from successful case studies: Demonstrating past successes, in placing projects successfully with various NCFs, and sharing learnings for the process, helps derive credibility and showcasing the scalability of the platform.
Overcoming Obstacles to Scaling Up Investments in Nature-based Solutions
AI thus happens to be critical in overcoming some of the key challenges underlying deployment of institutional investment in large-scale NbS projects, pertaining to lack of standardization, geographical dispersal, and scalability. These are bridged at least to an extent with AI-powered platforms that add a layer of intelligence and automation via predictive analytics, data standardization and quantification, enabling easier evaluation of projects and their feasibility for raising institutional capital. It consequently helps scale building of an investable pipeline through sourcing and assessing projects across a variety of project types, from mangroves to agroforestry, thereby unlocking potential supply of high quality assets that could raise institutional financing, generating requisite returns while providing sufficient avenues for risk mitigation.
Real-World Applications and Case Studies
At Calculus Carbon, we’ve been fortunate to witness encouraging traction with 12 institutional investors, as documented in some of our recent case studies involving large-scale forestry projects in Latin America. Such instances specifically underline how AI could power intelligent market making, while helping reduce aforementioned macroeconomic risks and capture key commercial, sustainability and biodiversity impacts, all of which work together to contribute towards making NbS projects mainstream institutional capital-friendly.
Looking Ahead: Scaling NbS with Technology
It is apparent that as with AI, the landscape of climate finance is still in its infant phases. However there’s limited doubt that both shall evolve at an astronomical space for us to be in a meaningful position to achieve our climate and nature targets. AI will power market efficiency and accelerate creation of a new asset class that is NbS investments, driving capital mobilization into under-forested geographies by leveraging various sector specific tools and processes, helping scaling the impact of NbS projects in such a way that benefit the investors as well as the planet.
Conclusion
Leveraging tech for enabling nature is indeed the way to our future, evolving into a well-orchestrated interplay between technology, finance, and sustainability. At Calculus Carbon, we are evolving nature-based solutions into an investable asset class of the future, incorporating structures from mature asset classes such as infrastructure and real estate, while leveraging AI driven market-making, project sourcing and evaluation. As we continue to innovate, I eagerly look forward to the evolution of NbS projects across emerging markets into infrastructure-akin commercial assets, unlocking long term climate and ecosystem benefits for local communities as well as the global populace.
