Welcome to our blog series where we delve into the intricate process of executing a climate risk scenario analysis within SAP Profitability and Performance Management (PaPM) efficiently and robustly. Leveraging the What-if scenario analysis feature of PaPM's report section, we empower users to assess financial risk Key Performance Indicators (KPIs), such as Climate Value at Risk, across diverse climate scenarios and portfolio assets in a single model run.
Meet Ankit Pal, a developer for SAP PaPM, leading the development of Climate Risk Scenario Analysis models within the Content and Add-on teams. Ankit holds two Master of Science degrees, one in Mathematics and another in Climate Change and Sustainability Studies, from the esteemed Tata Institute in Mumbai. With over four years of experience in Climate Change and Financial services, particularly in Reinsurance, Ankit is committed to driving sustainable solutions and fostering resilience through mathematical innovation.
Joining Ankit is Seyedsaeed Hosseinioun, a sustainability data analyst for SAP PaPM. Educated at the Technical University of Berlin, Saeed holds dual M.Sc degrees in Industrial Economics (with focus on Climate Economics), as well as Financial Engineering. With more than four years of expertise in Climate Risk, Decarbonization, and Sustainable Finance, Saeed brings a wealth of knowledge to the table.
Our blog series will unfold in three parts:
- Part 1: Climate Risk Management Introduction.
- Part 2: Methodology and assumptions for the implemented scenario analysis.
- Part 3: Financial KPIs and calculation steps.
Introduction
Climate risks, categorized as physical and transitional, impact economies through various channels. The Taskforce on Climate-related Financial Disclosure (TCFD) identifies four key impact channels: Macro Environment, Supply Chain, Operations, and Markets.
Figure 1 - Climate Risk impact channels (Source: Vivid Economics based on I4CE, 2018)
Climate risks arise from changes in weather patterns, affecting sectors like energy, agriculture, and manufacturing. Climate change adversely impacts human life, causing extreme weather events, health risks, and food insecurity. Rising temperatures lead to heat-related illnesses, altered precipitation agriculture disruptions, and water scarcity. Economic disruptions exacerbate poverty, and climate-induced conflicts add to challenges. Beyond physical impacts, climate change affects mental health. A mere one-degree Celsius increase can lead to economic disruptions ranging from 1 to 1.7% (Carletion and Hsiang, 2016). Addressing these impacts requires global cooperation, emphasizing emission reduction, adaptive measures, and community resilience. Equity perspective on climate change calls for tailored approaches across economies, with developed nations committing to emission reductions and supporting adaptation, while developing nations seek technology transfer and capacity building. The Global North-South divide emphasizes differentiated strategies, especially for vulnerable regions like Small Island Developing States.
Understanding the complex relationship between climate and the economy is crucial for informed financial decision-making. Climate risk, a threat multiplier, affects macro-financial risks. Power and insurance companies rely on advanced methodologies for risk management. In the power sector, climate modeling assesses impacts, while insurance firms use actuarial models for underwriting. Real estate companies use valuation models, and the reinsurance industry relies on risk models for catastrophic events. Technology evolution enables innovative approaches for risk mitigation.
Integrated Assessment Models and Scenario Analysis
Advances in data processing methods enable empirical investigations into the economic effects of climate change. Integrated Assessment Models (IAMs) play a crucial role in quantifying potential economic costs and damages. IAMs are expected to focus on scenario analysis, exploring diverse climate scenarios, considering emissions, adaptation, and global policy responses. Integration with artificial intelligence and machine learning enhances predictive capabilities. IAMs are anticipated to become more interdisciplinary, providing a comprehensive understanding of climate change and socio-economic systems, guiding sustainable development.
Scenarios are useful tools to understand the path from one point in time to another in the future. They are not predictions but highlight central elements of possible futures. TCFD defines scenarios as paths leading to a particular outcome. Socio-economic scenarios address economic and societal impacts, emissions scenarios display GHG concentrations, climate change scenarios demonstrate alterations in weather patterns, and climate impact scenarios show changes in climatic events. Mitigation and adaptation scenarios illustrate pathways for emission reduction initiatives and adaptation measures. Integrated scenarios capture a combination of these variables.
Climate-related scenarios include parameters like carbon price, energy demand, weather patterns, demographic variables, technological development, and policy. Analytical choices involve quantitative vs qualitative analysis, timeframe, assumptions, and scope of application. Outcomes and Key Performance Indicators (KPIs) encompass profitability, costs, and supply chain interruptions.
Conclusion
In conclusion, impact economies through physical and transitional channels. It affects human life, leading to extreme events, health risks, and food insecurity. Understanding the relationship between climate and the economy is crucial for financial decision-making. Advanced methodologies and IAMs play pivotal roles in managing climate risks. Scenarios are valuable tools for understanding potential future outcomes, and their elements encompass parameters, analytical choices, and outcomes. The future of IAMs involves enhanced scenario analysis, interdisciplinary integration, and collaboration for sustainable development.
Stay tuned for the next 2 parts in which the methodology and calculation steps of the physical climate risk analysis will be elaborated in more details.
References:
- TCFD Technical Supplement 2017. The Use of Scenario Analysis in Disclosure of Climate-Related Risks and Opportunities https://assets.bbhub.io/company/sites/60/2020/10/FINAL-TCFD-Technical-Supplement-062917.pdf
- IPCC Special Report 2000. Emissions Scenarios https://www.ipcc.ch/site/assets/uploads/2018/03/sres-en.pdf
- Carleton, T.A. and Hsiang, S.M., 2016. Social and economic impacts of climate. Science, 353(6304), p. aad9837.
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