Structuring Investments in Nature: Leveraging Tech to evolve the risk-return profiles for Institutional Investors for Nature-based solutions

By Neelesh Agrawal

About the Author:

Neelesh Agrawal is the Founder and CEO of Calculus Carbon, a Temasek portfolio company dedicated to mobilizing institutional capital for large-scale forestry projects across the Global South, with an order book exceeding USD 80 million. With a background in managing a $2.2 billion Real Estate Private Equity Fund, Neelesh is committed to redefining forestry as an infrastructure asset class. An alumnus of IIT Kharagpur, he has authored four research publications in game theory and strategy and collaborates with nine asset managers across the EU, UK, and Singapore.

Nature based solutions (NbS) have increasingly come to be regarded as a valuable asset in climate finance for their potential to contribute up to 1/3rd of the mitigation potential required to meet the Paris Agreement goals by 2050. Consequently, NbS projects ranging from large-scale reforestation and restoration of wetlands to sustainable land-use practices represent a critical pathway to address climate change. However, NbS investments currently pose various underlying challenges that conventional asset classes do not: a wide range of returns driven by the governing technical variables, uncertainties driven by broader macro and micro economic factors and difficulties around creating standardized metrics of evaluation.

Achieving specific risk-return targets is crucial for institutional investors, especially in engaging with a new and complex asset class such as NbS. Data and technology are increasingly playing a key role in helping uncover the risk-return profile of various nature-based projects, thereby enabling institutional capital to find its way to large scale NbS projects. Deploying predictive algorithms, AI, machine learning, and cloud-based data analytics, ascribes structure to NbS project investments that better align with the existing investor expectations. This article reviews how technology is playing a role in evolving nature investments towards a mature asset class ripe for institutional capital deployment.

Complexity in the Investment of Nature-Based Solutions

As crucial an instrument they might be for climate mitigation, NbS projects often fail to align with the existing annuity investment models rooted in infrastructure and real estate economics. This is driven particularly by a lack of understanding of the underlying risks in these NbS projects and requisite levers to mitigate them, thereby impeding the deployment of institutional capital at scale. Below are other key challenges:

High technical variability: NbS projects significantly rely on their immediate ecosystem with changes in local weather and soil conditions invoking sharp rise in volatility of expected returns. This is easily apparent in case of an afforestation project which severely underperforms in terms of carbon sequestration when adversely affected by soil degradation or water scarcity. 

Sensitivity to regulatory challenges and evolving policies: Investments in NbS projects, particularly in emerging economies, are chronically prone to changes in the local regulatory landscape. In most instances, the local environmental legislations, land-use policies, and the national climate regulations continue to evolve, creating significant uncertainty for an investor in being able to predict, let alone capture the value derived from an NbS investment over its economic life.

Lack of standardized impact metrics: Most NbS projects are multifaceted in their impact, spanning biodiversity preservation to carbon sequestration and from water purification to local atmospheric regulation. The measurement of these ecosystem services is rather tricky, and suffers from lack of standardized industry-wide metrics unlike in case of traditional financial assets such as real estate, on the basis which a relative assessment of two projects can be undertaken. In this regard, investors often find it hard to define the success metrics and consequently use them to comparatively evaluate two different investment opportunities.

How Technology may unlock the Institutional appetite for NbS investments 

AI and predictive analytics can potentially play a key role in better estimating the risk-return profile for an NbS project. Leveraging these in tandem could allow for analyzing huge volumes of input data, including satellite imagery, local country environmental impact data, and climate models to evaluate the viability of a project at scale. This helps significantly increase the accuracy of project evaluation with a wider stream of information about the prospective carbon sequestration potential and biodiversity benefits. The use of machine learning algorithms in retrospectively analyzing historical data on how the project in effect has panned out, enables project developers to meaningfully predict the variability in carbon sequestration rates for future projects in the area, thereby lowering investment risks.

Predictive analytics further enables investors i.e. Natural Capital funds (NCFs) to align their investment strategies with their preferential appetite for certain risks over others. For instance, a certain investor could be open to evaluating projects in a geography with an otherwise evolving regulatory landscape, given the underlying project developer is capable with a proven track record and the proposed project offers particularly favorable risk adjusted returns at scale.

Standardized Impact Measurement

As laid out earlier, standardization of impact metrics is crucial for scaling investments in NbS projects. There are emerging models innovating on unitising impact along a particular metric. Habitat banks, for instance, help structure a dedicated 25-100 hectare area with defined goals towards conserving biodiversity in the project boundary. This enables securitisation of the impact and thereby enables creation of a payment for ecosystem services (PES) market for private and institutional capital to fund nature.  to codify ecosystem benefits tangibly, for easier evaluation and comparison. 

Codifying ecosystem benefits tangibly enables converting abstract ecological information into quantifiable financial equivalents, such as carbon offsets or biodiversity net gain. Such standardization provides institutional investors consistent, comparable metrics across projects to facilitate due diligence and enables risk management via active tracking of these metrics over the investment duration. This in turn ultimately incentivizes more corporations to undertake voluntary capital commitments, driven by a measurable return on investment in the form of quantifiable impact on one or more of these ecosystem services.

Blockchain further has an opportunity to emerge as an outstanding MRV (Monitoring, Reporting, Verification) tool to robustly track these impact metrics over the investment tenure in a transparent manner, by all the relevant stakeholders including the registries (Verra etc), the project developer, the institutional investor and the offset retiring corporate. By observing the impact data in real time onto a decentralized private ledger, investors are able to trace the project outcomes, reconcile and dynamically update their assessment of the expected financial value of their investment. 

Customized Investment Models

AI-powered platforms similar to what we deploy internally at Calculus Carbon use an NCF’s investment 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.

Platforms also enable portfolio optimisation to achieve the intended risk-return profile of a particular institutional investor. A plethora of marketplaces exist that offer portfolios backed by multiple NbS projects, across reforestation, wetland restoration, and mangrove restoration among others. Such a mix provides a well-diversified investment base, reducing project specific risks in the portfolio and driving up the impact adjusted returns for a prospective investor.

These investment models can also be aligned to balance the regulatory exposure so as to manage the geopolitical and regional economic risks at the portfolio level . 

Real-Time Project Monitoring and Adaptive Management

Unlike their more traditional peers, NbS projects demand ongoing, intensive monitoring to ensure their performance meets both financial and impact objectives. Technology has thus far facilitated real-time monitoring data concerning project performance, environmental impact, and variance from projected outcomes. Investors have been afforded real-time insights on cloud-based platforms that enable adaptive management.

This would mean that if there are unforeseen drought conditions in the case, for instance, of a reforestation project, notice can be given to investors in a very short period, in which case they may decide to undertake further risk-mitigation measures, update their forecasted financial outcomes or altogether reallocate their allotment provisions for a project. This adaptability, driven by AI-powered insights, enhances the general resilience of nature-based investments, ensuring that projects can respond dynamically to changes in the multitude of underlying variables that define an NbS project.

The Future of Nature-Based Solutions in Institutional Portfolios

Technology invariably continues to make inroads into the NbS project landscape, making them not only more accessible  but also addressing certain structural challenges that have limited their investment appeal thus far. This evolution in quant-driven structuring will create pathways for more NbS investments that better match institutional risk-return profiles and allow new avenues for corporate investors to achieve their goals on sustainability and financial return in tandem.

The rapid evolution brings alongside its own set of challenges. As the market matures, all participating stakeholders- project developers, registries, auditors, and investors – alike need to continually refine methodologies for risk assessment, impact measurement, and project management. It is only through continued collaboration across these domains that a robust platform can be developed to support large-scale and high-impact NbS investments.

Conclusion

In conclusion, technology solutions are increasingly making NbS investments not only feasible but also increasingly attractive, given the aforementioned tools being brought to bear on the particular challenges of this asset class. Matching risk-return profiles through leveraging technology and deploying dynamic, transparent and standardized metrics incentivizes corporates to undertake institutional capital deployment in NbS projects.

As investments in NbS mature, a tech-enabled design and implementation would ensure that the projects are scalable, impactful, and achieve their required dual objective of requisite financial returns, alongside robust environmental outcomes. With appropriate structuring, monitoring, and transparency, NbS investments have a potential to  become a mainstay of sustainable institutional portfolios, generating returns for people and the planet alike.