Underwriting has always been the heart of insurance. But that heart is now beating faster. For decades, underwriters have assessed risk one policy at a time. Today, they're under mounting pressure to process increasing volumes, respond to brokers faster, and still maintain profitability.
At Send's INFUSE webinar, my fellow panelists Tom Nasso, CUO, from Falvey Insurance Group, and Dan Walsh, CUO, from Equinox, shared compelling perspectives on the drivers behind this transition. Their insights crystallized that the future of underwriting lies not in individual policies but in portfolio-level intelligence powered by data and technology, for the majority of risks.
Why Shift from Policy to Portfolio Underwriting?
Tom articulated this evolution precisely: "Portfolio underwriting and the use of data to drive underwriting is the result of the market's need to address speed, efficiency, and decision-making."
This observation captures the fundamental challenge facing underwriters today. The modern underwriting environment demands both speed and precision - traditionally competing priorities. Portfolio underwriting provides the framework to achieve both. Rather than navigating submissions in isolation, underwriters can identify trends across their entire book, monitor performance metrics in real time, and detect emerging risks before they materialize into losses.
At Aurora, we've advanced this concept by embedding algorithmic intelligence directly into the underwriting workflow. Modern technology can automate the manual steps of case underwriting - risk assessment, rules application, pricing calculations, and quote generation - enabling underwriters to focus on strategic portfolio management, broker relationships, and value-creating decisions rather than repetitive administrative tasks.
How Algorithmic Underwriting Works
During the webinar, I talked through this process in action. When a broker submission is sent in, systems can automatically extract critical details and enrich them with supplementary data points: location-specific information, exposure analysis, and peril modeling. This enriched dataset flows through rules and pricing engines, which generate consistent, auditable assessments and quotations within seconds.
This represents algorithmic underwriting - leveraging automation to handle the computational heavy lifting for complex underwriting, while empowering underwriters to excel at what truly differentiates them: cultivating relationships, optimizing portfolios, and executing informed strategic decisions that drive sustainable growth.
Insurers Are Already Seeing Significant Cost Reductions
The question of ROI naturally arises with any transformative technology. The empirical results provide a compelling answer. Carriers implementing algorithmic underwriting solutions are realizing significant expense reductions in trading operations.
That level of efficiency doesn't just cut costs - it fundamentally unlocks organizational capacity. You no longer need hundreds of underwriters to manage growth; you need skilled professionals focused on high-value decisions, supported by technology that enables scalable growth.
But efficiency is only part of the story. The real value lies in improving performance. When underwriters maintain real-time, granular visibility into portfolio performance, they can identify emerging patterns and intervene before trends deteriorate into losses. This operational agility transforms automation from a back-office efficiency tool into a genuine, profitable growth catalyst.
Legacy Systems: Still the Barrier to 'Smart Underwriting'
Transformation and change, however, is rarely frictionless. Both Tom and Dan highlighted persistent challenges: entrenched legacy systems, inconsistent data, and the cultural resistance that accompanies new technology.
At Aurora, we encounter these barriers regularly. Many carriers want to move forward but hesitate, concerned that their data isn't ready. My counsel is simple: start anyway. Begin laying the foundation. Use technology and AI to clean, structure, and organize your existing data assets. Simultaneously, establish robust processes to capture new data from inception - ensuring it's clean, structured, vast, and granular. Even if it isn't perfect, the progress you make today will determine how effectively you can use automation tomorrow.
And then there's culture. As Dan said during the session, this isn't just about tools - it's fundamentally about trust and organizational alignment. Underwriters and brokers need to experience automation as an enabler rather than threat. Success requires cultivating confidence that technology augments human judgment rather than replacing it.
Looking Ahead
Underwriting has always existed at the intersection of art and science. What's changing now is the scale and speed at which the science amplifies the art.
Automation, data, and algorithmic systems are enabling underwriters to make better decisions, faster, while freeing them to focus on the human aspects that have always mattered most: relationships, intuitive judgement, and experience.
The next chapter of underwriting isn't characterized by machines taking over. It's defined by human-technology collaboration that makes underwriting demonstrably smarter, faster, and more efficient - for underwriters, brokers, and clients alike.
