From guidance to action: Assessing climate risk with spatio-temporal AI

The TranzAI platform addresses a common challenge faced by communities and organizations in complying with climate risk disclosure frameworks such as the IFRS S2 or ESRS E1 Climate change: the gap between high-level guidance and the practical, detailed methodologies needed to assess risk. While these frameworks provide a foundation for understanding the importance of analyzing climate risks, they often leave organizations searching for practical methods to accurately identify, measure, and manage these risks.

An extract from the EFRAG standard clearly illustrates the problem encountered by risk analysts:

The undertaking shall describe the process to identify and assess climate-related impacts, risks and opportunities. This description shall include:
(a) impacts on climate change, in particular, the undertaking’s GHG emissions (as required by Disclosure Requirement ESRS E1-6);
(b) climate-related physical risks in own operations and along the value chain, in particular:
i. the identification of climate-related hazards, considering at least high
emission climate scenarios; and
ii. the assessment of how its assets and business activities may be exposed
and are sensitive to these climate-related hazards, creating gross physical
risks for the undertaking.

Granular climate risk insights through advanced data integration

Our platform fills this gap by providing data-driven processes that use advanced data engineering and spatial analytics to assess climate risk at a granular level. We understand that the impact of climate hazards on critical infrastructure, assets, and industrial processes varies significantly by industry and location. Therefore, our approach begins with the collection and integration of high-quality, relevant data, including geospatial data, climate models, and infrastructure and asset databases. This data forms the basis of our risk assessment process.

Ontology-based insights

After consolidating local data, our platform integrates it into a feature store and a semantic layer based on a climate-risk specific ontology. This approach simplifies the consolidation of heterogeneous data and adds meaning to it by contextualizing each piece of information within the broader framework of climate risk analysis.

Spatial analysis for localized risk assessment

Our platform offers advanced spatial analytics tools to assist data analysts in identifying vulnerabilities in their assets and infrastructure networks. This allows them to pinpoint the processes most at risk from climate hazards such as flooding, sea-level rise, extreme heat, or storms. By analyzing the geographic and physical characteristics of each type of infrastructure and asset, we provide a localized view of potential impacts.

Quantifying risks

The process of quantification involves evaluating the potential severity of impacts, the likelihood of hazard occurrence, and the vulnerability of infrastructure, assets, and operations. By doing so, analysts can iteratively acquire a clear and global picture of where the greatest risks lie, enabling them to prioritize mitigation and adaptation efforts effectively.

Comprehensive scenario analysis

Our platform combines individual risk assessments to create comprehensive climate risk scenarios. These scenarios provide a complete view of potential future conditions by examining each individual risk. This process helps data analysts better understand the combined and interactive impacts of various climate hazards on their operations and value chain.

Our platform provides climate risk practitioners with a clear and methodical approach to climate risk analysis that goes beyond the high-level guidelines of frameworks such as IFRS S2 or ESRS E1 Climate change. Our data-driven processes, spatial analytics, and comprehensive scenario analysis enable organizations to meet the requirements of climate risk disclosure and actively manage and mitigate those risks. Our goal is to transform the challenge of analyzing climate risks into an opportunity for proactive and informed decision-making. This will help protect organizations and communities from the effects of climate change.