The emissions credits transacted in climate and sustainability markets are probably the most complex financial instruments in the world. They are segmented based on the individual characteristics of their respective underlying projects, for instance, types of emissions reduction technology (renewables, forestry, etc), jurisdiction, certification standard, project’s contributions to the UN’s Sustainable Development Goals (SDGs), etc. This level of complexity makes it extremely hard for the market participants to appreciate the fair value of these assets.
Climate and sustainability markets suffer from a lack of price transparency due to their over-the-counter (OTC) nature. OTC transactions happen on a bilateral manner among market participants and makes it difficult for market participants to benchmark prices against in order to assess market value.
Apart from SDG 13, which relates to climate action mitigation, none of the UN’s Sustainable Development Goals (SDGs) carry an explicit market value. However, many the underlying projects producing emissions reduction credits make real contributions the other 16 SDGs (no poverty, zero hunger, etc). As a result, the assets originated from such projects have a higher intrinsic value as compared to baseline emissions reduction credits which is currently very difficult to assess explicitly.
The highly complex nature of assets coupled with market opacity makes valuation and risk management of emissions reduction credits intractable through traditional finance techniques. This creates major obstacles to the flow of urgently needed large-scale capital toward climate and sustainability initiatives. This is compounded by the added intrinsic value brought by the contributions to SDGs which are usually overlooked in monetary terms.
Artificial Intelligence (AI) is a highly effective technology for dealing with data in highly complex problems. This makes AI an obvious technology applied to creating transparency in the value of assets in climate and sustainability markets. Our AI models offer transparent fair valuation for the most comprehensive range of emissions reduction assets.
Our models are trained on unique datasets of over-the-counter (OTC) market transactions against benchmarks such as energy markets, compliance carbon markets, systemic economic factors, etc. With AI technology our models “learn” all inherent complexities and variations of emissions reduction credits and properly establish their respective fair value. This includes explicit fair valuation for not only climate action mitigation, and all the other 16 SDGs.
We believe our technology is an indispensable tool for any participant in the climate and sustainability markets. For instance:
Our AI-based Valuation and Risk Engine (VRE) provides simulated fair prices and risk management features for a wide range of voluntary markets offsets by: