Handling complex submissions with AI

Every underwriter knows the pain: a 50MB email lands with a mess of spreadsheets, PDFs, and scanned slips. Critical risk information is buried somewhere inside. Before pricing can begin, you're hunting, validating, and re-keying data manually.

This tedious reality defines submission handling in commercial and specialty insurance. But it's 2025. Technology is finally catching up.

AI, intelligent preprocessing, and automation are now transforming submission handling from underwriting's biggest bottleneck into a streamlined process. These advances don't just save time, they're fundamentally changing how insurers evaluate risk by ensuring quality data flows into every decision.

The most painful part of underwriting is becoming its most efficient without sacrificing the judgment that matters most.

The anatomy of a complex submission

Commercial insurance submissions represent a data management nightmare, arriving as chaotic email packages with multiple file formats and inconsistent structures. Grant Thornton reveals how "a year's worth of data is disaggregated across 12 to 15 different Excel files," creating significant processing challenges for underwriters:

• Oversized SOV spreadsheets - Statements of Values often arrive as massive Excel files with thousands of rows, multiple worksheets, multiple tables on a sheet, and proprietary formatting that defies standardization.

• Multi-format documentation - A single submission might include PDFs, scanned documents, Excel files, images, and even handwritten notes that must be reconciled into a coherent risk profile.

• Multi-language content - International submissions frequently contain information in multiple languages, requiring translation alongside technical interpretation.

• Inconsistent naming conventions - The same risk elements might be labeled differently across documents or submissions, making automated processing nearly impossible.

• Fragmented critical information - Key details are often scattered across different files, tabs, or buried in footnotes, requiring manual compilation to create a complete risk picture. They also might then require some level of judgment. For example: a Cyber underwriter may need to assess how “strong” the MFA setup is. This requires looking for indicators across submissions and making an assessment. Those indicators may not be easily searchable.

• Data validation requirements - Each field requires verification against multiple sources, policy terms, and historical data to ensure accuracy before pricing.

This highly manual reconciliation process consumes more than 3 hours a day of underwriters' time. Insurance Business Magazine confirms this challenge, with 92% of organizations now actively investing in data processing automation to reclaim this lost productivity.

Data chaos is a real business risk

Underwriting teams consistently underestimate how inconsistent formatting and poor-quality submission data undermines business performance, creating far-reaching consequences. As explored in our analysis, these data challenges extend well beyond the initial processing stage. Capgemini's 2024 report confirms that poor data quality "inevitably flows downstream," affecting multiple operational areas:

• Fragmented information sources - Key risk data often spreads across dozens of files in different formats, requiring extensive manual compilation before underwriters can even begin analysis.

• Inconsistent nomenclature - The same risk elements appear with different labels across submissions, making automated processing nearly impossible and introducing error potential.

• Validation complexity - Each data point requires verification against multiple sources, creating significant overhead that diverts underwriters from actual risk assessment.

• Cross-reference limitations - Without structured data, underwriters cannot easily connect new submissions to historical performance, limiting their ability to identify patterns.

• Downstream contamination - Data quality issues cascade into claims handling, actuarial calculations, and analytics, degrading decision quality throughout the organization.

These issues directly impact competitive advantage in today's market. McKinsey's 2025 report shows that operational execution drives 60% of commercial insurance performance, with submission processing capabilities representing a primary differentiator. Underwriters who can quickly transform messy submissions into structured data consistently build stronger broker relationships and capture more profitable business.

Faster, better decision-making in an increasingly competitive environment

The forces shaping the industry are increasingly volatile and powerful. McKinsey's 2025 report reveals that operational execution drives 60% of commercial insurance performance, making submission processing capabilities a primary competitive differentiator. New exposures, climate volatility, geopolitical tensions, and complex emerging liabilities are reshaping underwriting criteria, expanding the surface area of risk and making it more complex to understand and price.

Yet despite the industry's $22.9 billion underwriting gain reported by IRMI, most underwriters remain trapped in workflows dominated by data entry and cleansing. EY's 2025 report reinforces this urgency, urging insurers to align data roadmaps with strategic business objectives and standards.

The hx State of Pricing Report revealed the stark reality facing US insurers::

• 95% say their pricing technology needs improvement

• 47% report their platforms haven't delivered what was promised

• More than 1/3 are losing business due to slow or inconsistent pricing processes

These findings align with broader industry research showing that 92% of organizations are now actively investing in data processing automation to reclaim lost productivity.

As hyperexponential CEO Amrit Santhirasenan noted, "The industry is shifting from a defensive posture toward one that embraces technology offensively - for decision-making, not just operational efficiency."

Structured submission data isn't optional. It's the foundation for confident decisions that match modern risk complexity.

How AI is untangling complexity

The hx Ingestion Agent transforms chaotic submission data into structured, usable information for underwriters. Purpose-built for commercial insurance's real-world complexity, it leverages large language models (LLMs) and intelligent preprocessing to bring submission data directly into pricing workflows without manual intervention.

• Advanced document processing - Automatically ingests messy submissions across multiple formats (Excel, PDFs, scanned documents), eliminating hours of manual data extraction and manipulation.

• Intelligent data standardization - Understands insurance-specific schemas and semantics, transforming inconsistent naming conventions ("Timber" vs. "Lumber") into standardized model fields.

• Contextual interpretation - Handles both straightforward mappings (addresses, limits) and complex qualitative assessments (cyber security posture, risk quality factors) that typically require underwriter judgment.

• Data cleansing and transformation - Converts currencies, aggregates tables and rows to fit policy formatting, maps many-to-many and one-to-many fields automatically based on your data schema, and standardizes messy fields and drop-downs for consistent model inputs.

• Workflow optimization - Pre-screens and shrinks files to reduce processing time, with side-by-side input review that lets underwriters adjust, override, or accept data before ingesting into the model.

This targeted application of AI directly addresses the most painful bottleneck in the underwriting process. By transforming the chaos of submission data into structured information, underwriters can focus on risk evaluation instead of administrative processing, dramatically increasing quote capacity while improving decision quality.

Why hx AI delivers more than standalone ingestion tools

Unlike isolated document processing tools, hx integrates submission data directly into your pricing workflow with schema-aware intelligence that evolves with your models. This approach aligns with leading industry frameworks, including EY's recommendation to "prioritize AI use cases that create human-in-the-loop processes" that augment rather than replace underwriter judgment:

• Seamless model integration - The platform understands your pricing models' structure, automatically mapping incoming data to your schema without manual configuration, eliminating onboarding delays and accelerating quote turnaround.

• Adaptive intelligence - Schema-aware design means the system evolves with your pricing models, eliminating the constant tuning and rule adjustments required by standalone tools that frequently break during model updates.

• Workflow continuity - Underwriters and actuaries can continuously develop and refine models without disrupting downstream processes, preserving the critical flow of information from submission to quote.

• End-to-end data utilization - Structured submission data becomes immediately usable in pricing tools, creating a growing data asset that enables performance benchmarking and portfolio optimization beyond simple document processing.

• Industry-aligned approach - The design aligns with RGA's findings on structured underwriting data standardization, positioning carriers to capitalize on industry-wide data initiatives.

This comprehensive approach enables documented productivity gains and operational expense reductions of up to 40 percent through automation. By providing the foundation for advanced analytics and decision-making tools, structured submission data becomes the catalyst for meaningful transformation rather than just another document processing solution.

Unlock smarter underwriting decisions, not just faster processing

While many AI tools promise productivity gains, quality submission data delivers deeper value: consistency across teams, faster response times, pattern recognition, and improved downstream data quality. Leading insurers have documented processing time reductions of 30-50% while redirecting underwriters to strategic risk evaluation.

In a market defined by rising complexity and competitive pressure, the targeted approach works best. By addressing specific bottlenecks like submission ingestion, insurers achieve immediate efficiency while building the foundation for broader transformation, aligning with industry frameworks from McKinsey and EY.

Ready to transform submission handling from your biggest bottleneck into a competitive advantage? Book a demo of hx and our Ingestion Agent today.