The first mistake in underwriting transformation is treating it as a technology program alone, an initiative defined by faster workflows and ever-expanding data sets. That assumption implies progress can be engineered primarily through tools and process upgrades, when the harder work lies in reshaping how decisions are made, tested, and owned across the organization.
“Early in my career I thought underwriting precision meant technical accuracy,” says insurance strategist Douglas Robare. “The turning point for me came when I started underwriting through moments of stress where there was no perfect data and no safe answers.” Robare has spent nearly three decades leading underwriting organizations through regulatory scrutiny and market stress across global insurance markets, experience that shaped how he thinks about decision-making when conditions are least forgiving.
For insurers navigating correlated risks, mobile capital, and sharper regulatory expectations, his perspective reframes what effective transformation actually demands: precision. “Precision in this space isn’t about certainty. It’s actually more about clarity under uncertainty,” he says.
“Early in my career, I watched a highly profitable product with a twenty-five-year track record unravel in a single year,” Robare says. “Nothing we did was technically wrong. But by chasing growth without the contextual judgment that had protected that portfolio for decades, we destroyed its intent. That experience permanently reshaped how I think about underwriting precision.”
Decision Quality Over Technical Correctness
Robare’s definition of underwriting precision resists the neatness of a spreadsheet. Technical accuracy still matters, and pricing, policy wording, and delegated authority remain foundational. But technically correct decisions can still destroy long-term value if they ignore context, governance, and the behavioral elements of risk. What separates good underwriting from brittle underwriting is whether the organization can keep its intent intact when conditions are messy. “True underwriting precision in practice is the disciplined alignment of judgment, risk appetite, and accountability,” Robare says.
Precision is a system property. It lives in how decisions get made, escalated, documented, and owned. It also depends on how close leaders stay to outcomes. “The insights only really come from being close to the consequences,” he says. The further underwriting becomes removed from claims reality, conduct risk, and customer impact, the easier it is to confuse activity with judgment.
Precision Has Become a Competitive Differentiator
Insurers used to be able to carry pockets of imprecision inside large, complex portfolios. That buffer is thinner. “Precision matters now because the margin for error has collapsed,” Robare says. “We’re dealing with things in real time and the margin is much smaller.” He points to a set of forces squeezing the industry at once. “Capital is also more mobile. Risks are also very correlated. Regulators as well as consumers are much sharper, and the customer is also less forgiving.” In that environment, weak decisions surface quickly, whether through loss ratios, conduct failures, or reputational damage that spreads fast.
Robare’s critique of many transformation programs is that they confuse speed with clarity. “Precision is not about doing the same thing faster. It’s about deciding better,” he says.
“Most underwriting transformation programs fail not because the models are wrong, but because leadership is unwilling to be explicit about where judgment is allowed to fail.”
That starts with a hard question. “What risks do we actually want?” Portfolios can drift into volume chasing, particularly when growth targets become the organizing principle. He pushes the conversation further. Precision also requires knowing “where are we willing to go wrong and where are we willing to correct,” and “who owns the consequences when judgment fails.” Without explicit answers, technology does not fix precision. It simply magnifies whatever the organization already is.
Start Transformation at the Point of Judgment
Asked what levers matter most for leaders embarking on underwriting transformation, Robare begins with governance. “Who owns decision rights and accountability? Precision collapses when authority and responsibility are misaligned,” he says. “You need absolute clarity on who decides what, why, and with what consequences.” Robare’s second lever is how data is used. “Data is context, not control,” he says. Many firms deploy analytics to constrain underwriters, turning dashboards into compliance theater. High-performing organizations do the opposite. They use information to inform judgment, often by looking at the portfolio rather than obsessing over isolated transactions.
That means surfacing signals that sharpen thinking at key moments. “Not overwhelming people with metrics and KPIs,” he says, “but sharpening their thinking when it matters most.” Done well, data does not replace underwriters. It improves the consistency of decisions and highlights where intent and outcomes diverge. The last lever is culture. “Leadership behavior, not messaging,” Robare says. Underwriters watch what leaders tolerate when targets and discipline collide. “If leaders override discipline for growth targets, precision evaporates instantaneously.”
AI, the Accountability Amplifier
Robare is optimistic about AI’s impact on underwriting, but he treats it as an accountability amplifier. “AI will absolutely transform insurance underwriting, but it will never replace judgment,” he says. “If it doesn’t replace judgment, it will absolutely expose it.” The underwriter of the future is less of a transaction reviewer and more of a designer of decision environments. Leaders will spend more time “curating the decision environments, deciding what gets automated, what stays human, and where escalation genuinely adds value.”
Success, then, depends less on technical mastery and more on orchestration. “Success will depend far less on technical mastery and far more on the orchestration, the alignment of data models, people, and the risk appetite in real time,” he says. Leaders need enough AI fluency to ask the right questions and govern outcomes, not necessarily to build models. Robare sees a longer-term opportunity in collaboration. With firms racing to develop their own tools, he expects a shift toward shared data approaches that make markets more efficient, even within regulatory constraints. “I could see a future where there’s a lot more collaboration going on around big data sets,” he says, arguing that the complexity of emerging risks will eventually force greater cooperation.
The Real Prize Is Trust at Scale
Robare’s through-line is that transformation must start with intent. Technology is powerful, but it is not a substitute for clarity. Precision, in his framing, is a form of organizational trust, among underwriters, between leaders and teams, and between insurers, regulators, and customers. It is disciplined alignment repeated over time. AI can accelerate that discipline, or expose its absence. As Robare puts it, “Technology amplifies discipline and judgment, but it doesn’t replace responsibility.”
