Synthomer

Moving Beyond Compliance. How Organizations Can Gain Data-Driven Climate Insights to Inform Corporate Strategy.


From collecting data to creating a digital twin for climate-related physical and transition risk assessment and comparison. Discover why Synthomer appointed Risilience and how they leveraged the Riise platform to extract key results and analysis delivering business value.

“Partnering with Risilience enabled us to prioritize key actions supported by robust evidence for our strategic planning. The process moved us beyond compliance, providing actionable insights for both operational and strategic decision-making. Financially quantifying climate risk has become a catalyst for advancing our risk management, business strategy and financial planning.”
— Chris Brown, VP ESG, Synthomer


The Brief

Synthomer, a leading global supplier of high performance, specialized polymers and ingredients, engaged climate and nature analytics firm, Risilience to develop a comprehensive, data-driven climate scenario analysis solution capable of identifying, quantifying and integrating both physical and transition climate risks.

The objective was to embed these insights into enterprise risk management, strategic planning and financial decision-making – moving beyond regulatory compliance reporting towards strategic value creation. In addition to complying with mandatory and voluntary climate reporting requirements, Synthomer partnered with Risilience to complete a second phase of climate risk assessment and scenario analysis aiming to strengthen corporate strategy and prioritize climate action:

• Develop a robust climate-scenario risk and opportunity solution
• Enable assessment and comparison of physical and transition risks
• Develop a standard financial quantification tool
• Identify the most material risks and opportunities
• Provide actionable insights to inform decision making and strategic planning
• Support the integration of risks and opportunities into risk management, business strategy and financial planning


The Approach


Leveraging Digital Twin Data Across Climate Risk Models


The digital twin enabled the company to create a data-driven representation of Synthomer using company data. It defines exposure to risk:

• To build a digital representation using provided data, publicly available data and/or industry averages, any data gaps are bridged using assumptions
• Each component of data is used to generate climate risk results across different climate risk models


Financial Quantification of Climate-Related Risk

Climate-related physical risk is quantified as the total revenue impact from sites exposed to climate hazards, as well as revenue at risk due to projected climaterelated disruptions. Transition risk is expressed as five year and ten-year earnings value-at-risk (potential loss in a company’s future earnings due to adverse events) under different Network for Greening the Financial System (NGFS) emissions pathways, with future carbon taxation emerging as the most material potential risk overall. These insights are now feeding directly into Synthomer’s risk management process, ensuring that risk mitigation measures are aligned with financial exposure and operational priorities.


Business Impact

In meeting the objective to leverage climate risk assessment and scenario analysis to support corporate strategy, the collaboration surfaced several specific priority actions for Synthomer, backed by rigorous data and financial evidence:

• Incorporate site-level climate assessments into due diligence and business continuity planning •
Engage insurance providers on specific risks and mitigation and/or adaptation plans
• Continue to drive Scope 1, 2 and 3 emission reductions across Synthomer’s own operations, product portfolio and value chains to reduce both the company’s and its customers’ exposure to rising carbon tax costs

The ability to translate climate risk into financial terms has strengthened strategic decision-making and provided a clear pathway for integrating climate considerations across the organization.

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