Why underwriting inefficiency is holding back performance and profitability

Underwriters enter the profession to assess risks, price them strategically, and build strong broker relationships. But instead of focusing on high-value decision-making, they are often stuck in a cycle of manual processes, fragmented systems, and inefficient workflows.

The numbers from our State of Pricing Report tell the story:

• Underwriters spend an average of 3 hours per day on manual data entry, time that should be spent on risk assessment and strategic decision-making.

• Peer review processes stretch into days or weeks, delaying critical decisions that affect competitiveness.

• Submission-to-quote and quote-to-bind cycles remain measured in days, not hours, putting insurers at a disadvantage against faster competitors.

Despite years of discussion about modernization, the majority of underwriters say they haven't seen meaningful improvements in their workflows. This challenge is further highlighted by ACORD research showing that only 25% of insurance carriers have fully digitalized their value chains, indicating that 75% still rely on manual processes or legacy systems for portions of their operations.

Why are underwriting workflows broken?

Too many insurers still rely on disconnected systems and legacy processes that slow down underwriting instead of enabling it. While fewer insurers today rely entirely on spreadsheets, legacy Excel-based pricing tools remain a core part of many underwriting teams' daily workflows. McKinsey research confirms that "nearly 50 percent of manual activities could potentially disappear thanks to gen AI alone," confirming that manual activities represent approximately half of underwriting workflows.

1. Siloed systems drain efficiency

• Submission data arrives in varied formats across multiple platforms, requiring underwriters to manually clean, reformat, and reconcile information before they can even begin pricing.

• Disjointed data management leads to version control challenges. An underwriter pricing a risk may rely on outdated exposure data, while an actuary conducting simulations or trend analysis works with a completely different dataset. These version control issues create inefficiencies, increase the risk of errors, and make it difficult for insurers to maintain a single source of truth.

• Poor integration between pricing models, underwriting workbenches, and policy admin systems slow down workflows and increase the risk of errors.

• Underwriters often need to manually search third-party data sources, such as public datasets (e.g. Companies House) or news articles, to supplement pricing models. This extra step adds complexity and further delays decision-making.

• *Convr research shows nearly half of underwriters need better data access (46%) and improved technology tools (45%)**. This underscores the operational challenges facing commercial insurance teams.

2. Slow pricing model adjustments damage competitiveness

• Rigid legacy systems make it difficult for underwriters to efficiently price complex risks. This can lead them to relying on judgment-based pricing, instead of benefiting from structured models.

• For more complex policies, underwriters may need to work across multiple pricing models (sometimes four or five) before consolidating the results into a final, weighted quote. While this can be done in Excel, many underwriters avoid it as they find that Excel's limitations make it impractical for complex rating scenarios.

• Slow and cumbersome model updates mean pricing tools become less useful over time, leaving underwriters stuck with outdated assumptions or workarounds that undermine pricing accuracy.

Nearly half of underwriters (47%) find their pricing models unfit for purpose, while Convr data shows 74% of commercial insurers implemented new underwriting tools in 2024. This is clear evidence that the industry recognizes its underwriting capabilities need modernization.

3. Lack of actionable insights limit continuous improvement

• Insurers struggle to capture data from lost deals, leaving them guessing about what's driving success or failure.

• Without a clear feedback loop between underwriting decisions and portfolio outcomes, insurers are missing key opportunities to refine pricing and optimize risk selection.

• Underwriters lack real-time visibility into the impact of pricing decisions, which makes it difficult to track profitability across their book of business.

Industry data shows growing investment in analytics capabilities to address these gaps. Deloitte research reveals 76% of US insurers have already implemented generative AI to enhance decision-making capabilities and generate real-time insights from their underwriting data.

How the hx platform transforms underwriting workflows

The hx platform moves underwriting from manual and siloed to connected and scalable. It empowers underwriters to make better decisions at the point of pricing, reduce time spent on admin, and improve margins through better risk selection. Accenture research confirms that 81% of underwriting executives believe AI/gen AI will deliver significant efficiency gains in operations, risk assessment, and decision-making.

1. Streamlines data ingestion and eliminates re-keying

The hx platform streamlines the ingestion of submission data, reducing manual data cleaning and reformatting burdens. By integrating external data sources directly into underwriting workflows, it eliminates hours spent on low-value data entry tasks, allowing underwriters to focus on risk assessment instead of administrative work.

2. Connects pricing, underwriting, and portfolio management

The platform creates a feedback loop between underwriters, actuaries, and decision-makers, ensuring pricing, risk selection, and portfolio strategy remain aligned. Automated peer review integrated into internal communication platforms like Microsoft Teams reduces bottlenecks, while underwriters benefit from working with consistent, governed data that eliminates discrepancies between systems.

3. Enables instant pricing adjustments to keep pace with market changes

Underwriters can adjust key pricing variables in real time, whether attachment points, coverage tiers, or layer structures, without waiting for IT support. Changes instantly reflect in the underwriting workflow, enabling faster broker responses and the ability to adapt quickly to evolving market conditions.

4. Captures data for continuous optimization

The hx platform retains all underwriting decisions, including declined and lost quotes, creating a growing data asset for better pricing strategies. Underwriters gain real-time portfolio impact visibility, enabling data-driven decision-making. This continuous feedback loop allows underwriters and actuaries to refine models based on actual performance results.

Turn underwriting into a competitive advantage

Modern underwriting technology delivers efficiency gains, but the real impact comes from enabling underwriters to focus on strategic decision-making rather than administrative work. With underwriters spending up to 3 hours per day on manual data entry alone and facing significant delays in pricing decisions, the right technology can dramatically reduce this waste.

The industry recognizes the urgency. Convr research shows the vast majority of commercial insurers are actively investing in new underwriting tools and upskilling teams in data analytics and automation.

With only 25% of carriers having fully digitalized their value chains, insurers who modernize their workflows now will be better positioned to compete effectively as industry standards evolve. To learn more about how the hx platform can improve your underwriting capabilities, get in touch with our team.