MWB Case Study: Climate-Driven Blind Spots

Jul 21
6 min read

Using Forward-Looking Cat Modeling to Address Rising Climate Risks

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MWB Global Risks' Case Study: Turning Complex Risks Into Practical Solutions

Please note: This article is a summary of the case study. To download the full case study, click below

Case Study Overview

This case study examines the challenges organizations face when assessing climate-related risk using traditional, backward-looking catastrophe models. As climate patterns evolve and insurers increasingly rely on forward-looking assumptions, historical loss data alone may fail to identify emerging exposures, hidden concentrations of risk, and long-term vulnerabilities.

The case study also demonstrates how forward-looking climate modeling and risk intelligence can help organizations identify future risks, improve resilience, strengthen insurance strategy, and support more informed operational, financial, and capital planning decisions.

CASE STUDY TABLE OF CONTENTS:

This case study has been structured using the standard, traditional case study format that is used throughout the MWB Global Risks Case Study Series. This consistent approach provides a clear, step-by-step overview of the client's challenges, objectives, recommended solutions, implementation process, and key outcomes, allowing readers to easily navigate and compare each case study in the series.

The Purpose
The Context
The Problem
The Objectives
Key Priorities
The Assessment
- A Structured Multi-Phase Approach to Climate Risk Assessments
The Assessment Results: The Blind Spots Delaying Progress
The Results: Explained
The Implementation
- 4 steps to implementation
The Implementation: Explained
- 8 phases of implementation
The Outcome
The Takeaway

This document is for informational purposes only and is not intended to be exhaustive. No discussions or opinions in this document should be inferred as legal advice. Contact MWB Global Risks for insurance advice customized to your business needs. MWB Global Risks does not accept responsibility for the content of the information provided or any actions made on the basis of the information herein.

Case Study Subject

AURELIA INDUSTRIAL SYSTEMS INC.

Aurelia Industrial Systems Inc. is a vertically integrated manufacturer specializing in engineered industrial components and automated material handling systems. The company operates advanced manufacturing facilities, regional assembly centers, and strategically-positioned distribution hubs designed to support global supply chains for construction, energy, infrastructure, and heavy equipment.

INDUSTRY	HEADQUARTERS	GLOBAL PRESENCE	EMPLOYEES	REVENUE	OPERATIONS
Industrial manufacturing and engineered infrastructure systems	Toronto, Ontario, Canada	Operations across 18 countries in North America, Europe, and Southeast Asia	~8,400 worldwide	USD $3.2 billion	26 owned manufacturing and assembly facilities, 14 leased regional distribution hubs, and assets across North America, Europe, and Southeast Asia

CASE STUDY SUMMARY

Aurelia Industrial Systems Inc., a multinational manufacturer operating across 18 countries, recognized a growing disconnect between how it assessed risk and how emerging risks were evolving. While historical loss performance remained stable and traditional catastrophe models suggested manageable exposures, leadership questioned whether historical data alone was sufficient to understand future climate-related threats.

To address this concern, the organization implemented a forward-looking risk intelligence strategy designed to evaluate future exposures rather than relying solely on past events. By combining climate-adjusted catastrophe modeling, scenario analysis, geospatial analytics, and financial stress testing, the company assessed how changing climate conditions could affect its operations, financial performance, and long-term resilience.

The assessment identified several emerging vulnerabilities, including heightened flood exposure, increased typhoon risk, wildfire-related business interruption concerns, and portfolio concentration risks that were not fully reflected in traditional models. These findings provided leadership with a clearer understanding of future threats and enabled the organization to take proactive measures before losses occurred.

As a result, the company strengthened resilience, improved risk visibility, optimized its insurance strategy, and enhanced its ability to make informed operational and financial decisions. More importantly, it shifted from a reactive approach focused on historical performance to a proactive model centered on continuous risk intelligence.

This case study demonstrates how forward-looking risk assessment can help organizations identify emerging exposures, improve preparedness, and support more confident decision-making in an increasingly uncertain environment. The key lesson is clear: organizations cannot assess tomorrow's risks using yesterday's assumptions.

Aurelia Industrial Systems' Strategic Objectives

The Case Study details how leadership identified four key priorities that would strengthen coverage consistency, improve governance, simplify program administration, and support the organization's long-term strategic objectives.

For decades, the company relied on historical loss data and traditional catastrophe models to assess property risk. As climate patterns evolved and insurers increasingly incorporated forward-looking assumptions into underwriting decisions, leadership recognized the need for a more comprehensive understanding of future exposures.

Rather than relying solely on historical performance, the organization sought to evaluate how climate-related hazards could affect its operations, financial performance, and long-term insurability. The goal was to identify emerging risks, strengthen resilience, and support more informed strategic decision-making.

To support this initiative, Aurelia identified several key priorities that would guide the assessment.

Aurelia Industrial Systems' Key Priorities

Aurelia Industrial Systems' Assessment Results

The Blind Spots Delaying Progress

The analysis revealed several unexpected insights that challenged conventional risk assumptions:

The full case study explores the entire assessment, the complete implementation process, the coordinated approach taken, and the measurable benefits and outcomes achieved following the transition to a unified global insurance program.

Aurelia Industrial Systems' Climate-Driven Risk Assessment: A Forward-Looking Approach to Climate Risk

To address these challenges, Aurelia Industrial Systems Inc. conducted a climate-adjusted, forward-looking catastrophe modeling assessment designed to evaluate future rather than historical risk.

The objective was not simply to analyze past loss experience, but to identify emerging exposures, quantify potential financial impacts, and determine how evolving climate conditions could affect the company's operations, resilience, and insurance strategy.

highly-structured, multi-phase approach risk assessment

Using a highly-structured, multi-phase approach, the assessment combined climate projections, geospatial analytics, exposure mapping, and financial stress testing to provide a comprehensive view of future risk across the global portfolio.

Understanding future climate risk requires more than reviewing historical loss data. It demands a systematic process that evaluates changing hazard patterns, operational dependencies, financial exposures, and long-term resilience.

The following phases illustrate the key steps used to assess future climate-related risk and support strategic decision-making.

The Implementation: Turning Insights into Action

Armed with a clearer understanding of its future risk landscape, Aurelia Industrial Systems Inc. implemented a forward-looking, climate-adjusted risk intelligence strategy designed to strengthen resilience, optimize insurance programs, and support long-term business continuity.

Rather than relying solely on historical loss experience, the organization adopted a structured approach that evaluated how evolving climate conditions could influence future operational, financial, and insurance-related exposures. This provided leadership with a more comprehensive view of risk across its global portfolio.

The strategy integrated climate modeling, exposure mapping, and financial stress testing to identify vulnerabilities that may not have been visible through traditional assessment methods. By examining both current and projected risks, the company gained deeper insight into potential impacts on facilities, supply chains, business interruption exposures, and capital planning.

The approach connected future hazard projections with the organization's assets, operations, and financial risk tolerance, enabling decision-makers to prioritize mitigation efforts, evaluate insurance adequacy, and support long-term strategic planning.

This framework transformed risk management from a largely retrospective exercise into a forward-looking decision-making tool, helping leadership make informed decisions today to reduce vulnerability tomorrow.

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The Takeaway: A Summary

The Aurelia Industrial Systems' Case Study demonstrates why organizations can no longer rely solely on historical loss data to understand future risk. As climate conditions, supply chains, regulations, and operational exposures continue to change, risks can emerge even where historical performance appears stable.

By combining historical data with predictive modelling, scenario analysis, and continuous monitoring, organizations can identify emerging exposures earlier and take proactive steps to protect operations, strengthen resilience, and inform capital and insurance decisions.

In an environment where tomorrow’s risks may look very different from today’s, forward-looking risk intelligence is becoming a business necessity.

→ Download the complete case study to explore the full implementation process, key lessons learned, and practical insights that can help strengthen your own global insurance program.

If you'd like to discuss your organization's multinational insurance needs, contact MWB Global Risks to speak with one of our specialists.

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Please note: This article is a summary of the case study. To download the full case study, click below

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