July 8, 2022
xx min read

Unleashing the Value of Underwriting Data with Knowledge Graphs

At CONVR, we believe achieving Underwriting and Operational excellence demand innovation and thought leadership from platform to data.

At Convr, we believe achieving underwriting and operational excellence demand innovation and thought leadership from platform to data.

Background

Commercial Insurance Underwriters collect and analyze a broad array of sources to support their underwriting decisions. These sources of information can be broadly classified into:

  1. First party documentation shared by agents and insureds (submissions)
  2. Digital footprint (public/open data, third party)
  3. In-house data (historical claims, underwriting guidelines, etc.)

Challenges facing underwriting teams

It is no secret that aggregating all of these sources and making sense of it all is a very manual and cumbersome process. Some of our observations about the current state also include:

  1. Manual effort to organize this information means that underwriting teams sometimes have to make trade-offs on level of data capture e.g. large vs. smaller accounts
  2. What is information collected and how it is organized (structure and quality) can vary across underwriting teams (even within business units)
  3. Most of this valuable data is transient and sometimes, entirely lost, based on the final disposition of the insurance application e.g. quote not taken, declinations etc.
  4. Compiling this information is a point-in-time exercise with limited access and insights into changes in the underlying data e.g. new services from a business that could materially impact pricing decisions

The opportunity

Companies can address these challenges in part by increasing the efficiency of capturing the required data with underwriting automation, including document extraction methodologies, RPA etc. While this is a step in the right direction, it doesn't address the most valuable opportunity. Developing a consistent approach to organize, maintain, and analyze the wealth of information aggregated in the underwriting process is essential to achieving excellence in other areas, including claims processing, fraud analysis, premium audit, pricing and analytics.

Our best practice approach

The key to success is to invest in capabilities that support near-term improvements in speed and efficiency gains but in parallel, drive to unleash the value of underwriting data across the organization. Adopting an AI underwriting data platform such as Convr enables insurance companies to do exactly that.\nOur products are built on the concept of knowledge graphing. According to IBM, information – “ie. Objects, events, situations, or concepts . . .” are collected in a way that “illustrates the relationship between them. This information is usually stored in a graph database and visualized as a graph structure.”\nWhat this means for insurance organizations is that all information captured during the underwriting process (documents, extractions, public data, etc.) is organized into a graph database. Graphs capture both the "point-in-time" information, and they're also, continually updated to capture changes. The graph data is made available to users and readily accessible through traditional Extract Transform Load (ETL) pipelines and cloud warehouses such as Snowflake.\nWhile knowledge graphs may not be exactly top-of-mind for underwriting teams, as a product "for underwriters by underwriters," we have supercharged the underlying bones of our product suite to deliver the greatest value to the entire insurance value chain.\n

blogs

Keep Reading

More articles on AI, underwriting and the future of commercial P&C.

XX MIN READ

Glean Insights on Hard-to-Find Small Businesses with Convr’s Biz Intel Feature

A huge portion of commercial property and casualty (P&C) insurance applicants barely exist online. Many small and mid-size commercial insureds (the bread and butter of commercial insurance underwriting) are nearly invisible online.

Think about it . . . landscapers, contractors, florists and more. The  food truck owners, small town auto mechanics and mom and pop shops . . . many don’t have:

  • a website
  • a strong social media presence
  • consistent business filings
  • complete insurance applications

Underwriting team members call this a low digital footprint risk and it’s a problem for them. When the submission comes in, they need to know if the business is real, if the owners do what they claim to do, and if the exposure is what the agent says it is.

But if the business has no digital presence, the underwriter is lost without their normal verification tools including website and online reviews, access to pertinent safety records and satellite exposure checks as well as prior filings.

That’s where Convr’s AI Underwriting Workbench shines. With our Biz Intel web search feature for low digital footprint companies, that hard to find information easily turns up for the underwriter within our underwriting platform.

The Convr Underwriting Workbench’s Biz Intel can uncover:

1) Business Classification

2) Appetite relevant exposures

3) Number of employees

4) Revenue

It turns an unknown into a knowable risk, giving the underwriter the opportunity to decide whether or not to write the risk rather than to spend time investigating it further. It’s a shortcut for underwriting team members of all levels as they spend less time searching for the details that move the decision.

All in one place:

In the Convr AI Underwriting Workbench, every new submission with the web option enabled, runs Biz Intel and returns the results inline. The hard-to-find details land next to the submission you're working on, not three tabs away from it.

Why it matters:

Low-digital-footprint submissions take time that underwriters often can't justify spending. Enrichment surfaces the missing data automatically, so accounts that would have been deprioritized or declined for lack of information become writable.

Convr’s Biz Intel users get:

1) First-quote advantage: Brokers place business with the first to quote. If your underwriting team is out searching Google, the Secretary of State, checking maps and emailing questions – you could be missing out on deals. With Convr AI data enrichment, the data comes to the underwriter instead of the other way around – and the first quote is more often yours.

2) Reduced referral dependency: When reliable information on low digital footprint companies is available in the file, more submissions can be decided where they land. Junior underwriters escalate only the accounts that genuinely need a second set of eyes. Senior underwriters spend their time on the complex risks and judgment calls that actually require their experience – not on questions a richer file would have answered on its own. Across the team, consistency improves and cycle times tighten.

3) Greater portfolio profitability: This is the real return on investment. Commercial carriers rarely lose money on catastrophic risks. Instead, they lose money on thousands of slightly mispriced/misunderstood small and mid-size policies – and low-visibility insureds are exactly where this is most common.

Convr's AI Underwriting Workbench isn't a productivity system. It's a loss ratio control system. If thin-file submissions are costing your team time or premium, we should talk – visit us at convr.com today.

XX MIN READ

Convr Accelerates MGA Growth

From Intake automation efficiency to data modeling for hidden insights, Convr is helping Managing General Agents (MGAs) turn fragmented submission documents into structured, enriched data – accelerating clearance, rating, and quote times to unleash profitable growth.

Everyone knows the best models win at taming documents!\nOur Intake module ingests and enriches data from both structured and unstructured documents including PDFs, Excel and emails across commercial property and casualty (P&C) insurance asset types, including ACORDs, Inspection Forms, SOVs, Loss Runs, Schedules, and more.

Powered by Convr AI and the Risk Context Engine – a purpose-built commercial insurance ontology, knowledge graph, and semantic layer that powers a multi-line schema – transforming fragmented submissions into structured, decision-ready intelligence. By grounding every document, application and data source into a consistent schema, Convr Intake ensures contextually complete, consistent, and reliable data from the start. The result is faster processing, fewer manual touchpoints, and improved risk clarity for accelerated MGA Growth.

Through Risk 360 – a commercial insurance data lake comprised of the digital footprints of millions of businesses – Convr standardizes addresses, performs geo-coding, enriches submissions with CAT modeling codes, and adds property intelligence data such as distance to coast and other hazard indicators. The enrichment delivers a holistic decision-ready view of risk prepared for underwriting, rating, and carrier reporting.

By eliminating re-keying and reducing back-and-forth data gathering, submissions are ready to quote in less than 10 minutes! This is how our MGA customers underwrite smarter and faster to unlock substantial written-premium growth without adding to headcount.

If you’re exploring ways to scale faster with AI, better data and meaningful operational efficiency, Convr welcomes the opportunity to share how leading MGAs are using Convr today.\nJust reach out to Convr today to see how we can help!

XX MIN READ

Convr® Evolves Data Catalog for Faster, More Transparent Underwriting

Convr®, took a leap toward delivering the next big advancement in artificial intelligence (AI) underwriting through the enhanced performance and usability improvements of its Data Catalog within its commercial insurance underwriting workbench in 2026. Convr’s Data Catalog makes it easier for underwriting team members to discover the thousands of data sources that are compiled in Convr’s Risk 360 data lake.\nThe leading artificial intelligence (AI) company serving commercial insurance organizations with its underwriting workbench implemented a new view for the company’s Data Catalog which aligns with its commitment to transform the commercial insurance underwriting industry and enables frictionless underwriting.\nWithin the model, users can easily glean insights from its extensive list of nearly 3,000 external data sources. Underwriters can also search across all Convr data sources, filter through the list by location, and view detailed information about each source with greater clarity. This new format allows users to quickly understand what data is available and how frequently it is refreshed.\nWhat it shows:The Data Catalog displays detailed information about each data source, including:

  • Source name
  • Data type
  • Source update frequency
  • Convr update frequency
  • State
  • Last updated date

The new table format makes it much faster and more intuitive for users to locate the data they need. The clickable links are up-to-date avenues that serve as a streamlined source to greater information and transparency into submission data. Our customers have much to gain from this new functionality.\nTogether, these advancements within the platform's user interface mark a pivotal moment, advancing the industry toward a more intelligent and trustworthy underwriting process built on accessible, high-quality data.

Realize End-to-End Underwriting Excellence with Convr AI

Experience how commercial P&C insurance organizations benefit from submission through quote with a frictionless process enriched by AI decisioning, empowering them to make better decisions, faster.