Abstract / Introduction
From January to May 2025, I completed my second work term at Sovereign Insurance in downtown Toronto, returning in a new capacity as an underwriting intern with the Equipment Breakdown (EB) team. My main contribution this term was the development of a Probable Maximum Loss (PML) rater—an Excel- and VBA-based tool designed to support underwriters by automating loss estimation based on IBC codes and loss scenarios. This role allowed me to dive deeper into the thought process behind EB underwriting, which involves analyzing the potential impact of equipment failure on business operations, assessing exposure, and considering industry-specific risks. My work aimed to assist underwriters by embedding that complex risk logic into a streamlined, automated tool that improves consistency and speed during decision-making.
Goals
Expand my understanding of risk modelling, particularly in the context of equipment breakdown insurance.
Enhance my technical skills in Excel VBA by developing a fully functional PML rater.
Improve my ability to communicate technical tools and results to non-technical stakeholders.
Develop a user-friendly interface to ensure adoption and usability by underwriters.
Technologies and Skills I Targeted:
I focused on Excel and Visual Basic for Applications (VBA), technologies widely used in insurance for quick yet powerful automation. I aimed to write complex macros capable of processing large datasets, improve my UI/UX instincts within Excel, and reinforce data validation and error handling in VBA.
Reflection:
I successfully met my goals. I gained hands-on experience building a production-ready tool used by the EB team, refined my programming skills in VBA, and deepened my understanding of how insurers assess potential losses. I also improved in translating technical processes into intuitive user experiences. However, similar to my first work term, I recognize the need to continue building deeper expertise in policy frameworks and regulatory considerations.
Summary
My primary responsibility was the development of a Probable Maximum Loss (PML) rater using Excel and VBA. This tool allows underwriters to quickly assess maximum loss estimates based on variables like company size, industry classification (IBC codes), and scenario-based risk data. The underwriting of equipment breakdown policies requires a detailed understanding of how various types of machinery and systems operate, what failure could look like in different environments, and the resulting financial impact. Underwriters must also weigh historical loss data, the criticality of equipment to business continuity, and preventive maintenance efforts when evaluating risk.
By collaborating closely with underwriters, I incorporated their domain expertise directly into the tool, ensuring it reflected real-world assessment logic. I designed the system to analyze large datasets, perform backend calculations, and output actionable estimates—all wrapped in a clean, user-friendly UI. The project demanded strong logic structuring, macro optimization, and performance-aware programming. While some of the foundational programming skills came from university courses (e.g., Object-Oriented Programming), much of the Excel-specific logic, UI creation, and nuanced understanding of insurance risk modelling were developed on the job through direct feedback and mentorship.
Conclusion
This term at Sovereign Insurance allowed me to bridge advanced technical skills with practical underwriting needs in a real-world business setting. My contributions to the EB team through the PML rater not only streamlined workflows but also reinforced the value of well-designed technical solutions in traditional industries. I leave this term with stronger coding abilities, better cross-functional communication skills, and a sharper understanding of insurance data workflows. Moving forward, I feel more equipped to drive impactful, tech-enabled innovations in the business world.