Insurance is evolving. Earlier rooted in manual processes and intuition, today the industry is being reshaped by data, technology, and automation. Underwriting is no exception. Underwriters are facing a new reality defined by growing complexity, tighter timelines, and a flood of data. As risks evolve, underwriters now have to assess individual policies, understand entire portfolios, anticipate patterns, and act with speed. Hence, there is an operational shift.
At Send ‘s INFUSE webinar, industry leaders took center stage to discuss this shift on how portfolio-level strategies and AI are redefining risk assessment. Bijal Patel, Co-founder and CTO at Aurora mentioned that manual processes are evolving not because underwriters aren’t essential, but because the volume, speed, and complexity of today’s data simply can’t be managed by humans alone. Hence, Tom Nasso, CUO, Falvey Insurance, positioned portfolio underwriting as the natural next step for an industry under pressure to work smarter, not just harder. Building on that idea, Dan Walsh, CUO, Ardonagh Group, explained that portfolio underwriting is also influencing how brokers think about efficiency and capacity. It’s a win for clients, brokers, and carriers.
But with the shift comes new challenges. From legacy systems and data silos to cultural resistance. How can insurers balance innovation with intuition? And what does the rise of portfolio underwriting really mean for the future of the profession? Let’s find out.
Why portfolio underwriting now?
Risks aren’t the same anymore. They’ve become interconnected in nature making assessment extremely challenging. That’s where portfolio underwriting steps in. Instead of evaluating risks one policy at a time, this approach takes a broader, more analytical view of using data to assess performance, profitability, and exposure across entire books of business. It allows underwriters to move beyond gut instinct, spotting correlations and emerging trends that would otherwise remain hidden in spreadsheets and silos. As Tom Nasso put it, portfolio underwriting is the “natural next step” for an industry under pressure to work smarter, not harder.
Algorithmic intelligence will now do the heavy lifting
The goal of algorithmic underwriting is to automate the manual steps of evaluating risk, pricing, and applying underwriting rules, while still keeping humans in the loop for strategic decisions.
Bijal Patel, Co-founder and Chief Technical Officer at Aurora, breaks down the process.
- Submission Received
A broker sends a request. The system automatically extracts all relevant data from emails and attachments. - Data Enrichment
The extracted information is combined with external data sources: geolocation models, historical claims, market trends, and other relevant intelligence to create a detailed, granular risk profile. - Automated Underwriting Rules
Algorithms run the risk through a series of checks: Is the risk in appetite? Do underwriting rules apply? What are the appropriate limits, deductibles, and terms? - Pricing & Optimization
Using predictive models, the system calculates a recommended price and adjusts it for market conditions, broker relationships, or risk-specific factors. - Real-Time Decision Output
Within seconds, the system produces a complete quote the same outcome a human underwriter would generate, but much faster and more consistently. - Human Oversight & Portfolio Management
Underwriters use their expertise to monitor portfolios, manage emerging trends, and make strategic adjustments. For example, if certain policies begin trending negatively, underwriters can act immediately to adjust pricing or appetite.
The Result:
Faster, more consistent underwriting with human judgment focused on strategy, relationships, and portfolio performance.
Legacy Systems: A major barrier to adopting AI underwriting
While algorithmic and portfolio underwriting offer enormous potential, legacy systems and fragmented data remain significant hurdles. As Tom Nasso pointed out, “Legacy systems are what’s preventing algorithmic underwriting from really taking off. You need clean, mapped data to make algorithmic decision-making possible.” Yet technology alone isn’t the full picture. Dan Walsh highlighted that success also depends on culture. “This isn’t purely a tech issue. It’s a cultural one. Brokers and carriers need to trust each other and work in sync. The systems need to be intuitive, but there also needs to be belief in the process.” Shifting from intuition-driven underwriting to a data-powered approach takes time, collaboration, and a willingness to rethink long-established workflows, but the payoff is a smarter, faster, and more agile underwriting process.
Algorithmic underwriting reduces expenses by 90%
Return on investment is an important question that pops up when adopting new technology in the insurance industry. Bijal Patel had a straightforward answer: “We’ve seen carriers reduce expenses by up to 90% while also improving their loss ratios. You don’t need 600 underwriters to manage a massive portfolio anymore. You can have 60 who focus on relationships and high-value decisions, supported by technology doing the heavy lifting.”
Patel stressed that efficiency is only part of the equation. “It’s not about cost-cutting for its own sake. It’s about growth that’s profitable and sustainable. When algorithms continuously learn from portfolio data, they help underwriters make smarter calls every day.”
As the webinar closed, the panelists shared their final thoughts on Portfolio Underwriting.
–Dan Walsh reiterated that automation and data don’t replace underwriters. They enhance their ability to compete, build relationships, and strategically manage portfolios.
–Bijal Patel confirmed that algorithms can be applied to even complex, specialty lead underwriting, but success requires combining automation with portfolio management to optimize loss ratios.
–Tom Nasso stated that underwriting will increasingly leverage science and AI, but the human art of judgment remains essential, especially in specialty lines.
The discussion made one thing clear: the future of underwriting is here, and it’s a blend of data, technology, and human expertise. Portfolio-level strategies, supported by AI and algorithmic tools, are not about replacing underwriters; they’re about empowering them to make faster, smarter, and more profitable decisions. As insurers and brokers embrace this shift, those who combine the art of judgment with the science of data will lead the next era of insurance.
Keen to learn more? You can watch a recording of the webinar here.