Underwriting at leading P&C carriers is under constant pressure to quote faster, drive efficiency, and improve accuracy—all while lacking the tools to make sense of complex, unstructured submission data.
Many carriers attempt to implement generalized AI solutions that are meant to quickly get their underwriters data; however, they fall short. They take months or years to implement, and these generic solutions often lead to maintaining manual operational processes or creating workarounds that were meant to be eliminated by adopting this new technology. Underwriters are left in the same place they started: spending hours parsing, verifying and structuring the data to make risk assessments based on incomplete or inaccurate information.
These inefficiencies don’t just slow things down; they impact profitability and increase loss ratios. Carriers need purpose-built underwriting technology that automates ingestion, standardizes data, and delivers data to underwriters that they can use to uncover actionable insights and make better risk decisions.
The Problem with One-Size-Fits-All Underwriting Models
Underwriting often attempts to improve efficiency by implementing generalized AI solutions, but these models struggle to handle the complexity of commercial insurance data. Submission formats, risk categories, and policy structures vary widely, and a one-size-fits-all model can’t account for these differences. Additionally, gaps in data enrichment mean key details like subcoverage specifics, claim classifications, and financial data are often missing or incomplete, giving underwriters an insufficient picture of risk.
For example, loss run reports often present financial data differently depending on the carrier, making it difficult for a generic model to extract and standardize information. Policy terms and coverage details may also be formatted inconsistently, requiring additional manual review to ensure accuracy. Without a predefined model tailored to each line of business, these discrepancies create more work for underwriters rather than reducing it.
Generalized models also fail to deliver fully enriched business intelligence. While they may extract a limited set of basic data fields, they often overlook critical underwriting insights, such as:
- Subcoverage classifications to ensure accurate policy pricing
- Net total incurred and other financial data to assess claims risk
- Policy year and term structures to provide a complete underwriting picture
Without this depth of insight, underwriters are forced to make decisions based on incomplete or inaccurate data, creating unnecessary risk within their portfolio
Groundspeed by Insurance Quantified takes a different approach. Rather than applying generalized AI models that don’t account for industry-specific needs, Insurance Quantified has developed a purpose-built AI platform designed for the complexities of commercial underwriting.
How Groundspeed Delivers Accurate, Actionable Intelligence
Groundspeed eliminates inefficiencies by applying our proprietary AI models for each line of business. From ingestion to enrichment, every stage of the process ensures consistency and accuracy, allowing underwriters access to the data they need to make informed decisions.
Here’s how it works:
- Automated data ingestion
- Submissions are received via API, SFTP, or email.
- Groundspeed’s AI processes PDFs, Excel spreadsheets, images, and emails.
- Optical character recognition (OCR) and intelligent document processing (IDP) extract key underwriting information.
- Line-of-business-specific standardization
- Normalized and object-oriented data models specific to each exposure under a line of business.
- Standardization eliminates format inconsistencies between brokers and carriers.
- Underwriters receive a unified, structured risk picture in a fraction of the time.
- Quality assurance for 98%+ data accuracy
- Automation validation detects anomalies before data is delivered.
- In-line quality assurance checks verify accuracy at multiple points.
- Human-supervised labeling supplements automation when a document is not known.
Groundspeed’s purpose-built AI and rigorous quality controls standardize raw, unstructured data into high-confidence underwriting intelligence, with automated data submission extractions typically completed in a few minutes.
The Business Impact of Purpose-Built Underwriting Intelligence
The shift from generalized models to purpose-built AI has a direct impact on underwriting performance, driving efficiency and profitability.
Faster quote-to-bind ratios
The first carrier to respond often wins the business, but complex submissions can take days to process manually. Groundspeed structures and delivers risk data in hours, not days, allowing underwriters to quote faster and win more deals.
Lower operating expenses
Manual data extraction and processing costs can range from $85 to $100 per submission, and that’s just for access to partial data. Groundspeed eliminates these costs by automating ingestion, reducing manual processes, and improving accuracy.
More accurate risk selection and lower loss ratios
Having complete and accurate underwriting data leads to appropriately priced policies and lower claims costs. Groundspeed’s AI-driven approach maintains a 98% data accuracy score, ensuring underwriters work with complete, enriched data. This improves risk selection and lowers loss ratios.
Greater innovation and new product growth
With high-quality data, carriers can develop new insurance offerings based on real-time underwriting insights. Groundspeed provides a clearer view of risk profiles, allowing for more targeted and profitable product development.
Empowers underwriters and attracts new talent
By automating tedious data entry and standardizing inconsistent submission formats, Groundspeed frees underwriters to do what they do best: evaluate complex risks and craft smarter coverage strategies. This shift not only improves job satisfaction for current teams but also positions carriers to appeal to a new generation of underwriters who expect modern, tech-enabled workflows.
Transforming Underwriting with Groundspeed’s AI
As commercial insurance continues to evolve, underwriters can’t afford to rely on inaccurate and incomplete data. To compete, carriers need standardized, structured risk data that supports fast, confident decision-making.
Groundspeed delivers on this need by:
- Eliminating manual inefficiencies and inconsistencies
- Applying tailored AI models for different lines of business
- Ensuring 98%+ data accuracy through automation and human review
- Delivering structured, enriched risk data within hours
Groundspeed is a proven solution for carriers seeking to accelerate their underwriting process and enhance their competitive advantage.
Request a demo to learn how Groundspeed delivers seamless underwriting automation in just 90 days.
