October 7, 2025
xx min read

Convr Adds Tasks to Expand Workflow Features

Convr supports Tasks in the Convr Underwriting Workbench. Customers can use this feature to begin to associate Convr submissions with tasks for underwriting.

Convr now supports Tasks in the Convr Underwriting Workbench. All Convr customers who use Convr as an underwriting workbench can take up this feature and begin to associate Convr submissions with work tasks for their underwriting team members. This feature allows a team-based, role-based approach to underwriting submissions in which multiple users can assign, perform, and complete various tasks needed to underwrite a risk—creating a space for greater input and collaboration from underwriting team members. \nWith Task Manager, users have a view of pending tasks originated by them and assigned to them. They can click on a task and review any comments or activity that has been added to the submission. Documents can be uploaded to tasks as well — further advancing the cascade of information and collaborative team environment.\nWhere to find Tasks:In the table view in Convr, you can click on a submission and then see the “Tasks” button. From there you can see open and completed tasks, comments exchanged between team members and all activity attributed to a particular task. Additionally, you can attach supporting documents for an audit trail. \nThe activity box displays all updates to the task, any assignment of the task and if a user wanted to attach a document to the task, that information would also be displayed in the activity box. Updates appear in real-time. Additionally, when creating a task the user can require that a task be completed before advancing to the next stage.\nThere are also automated tasks – tasks that will be automatically added to the submissions – such as sanctions screening for example – there will be a task automatically assigned to the legal department to clear the submission.\nWhy this Feature Matters: \nThis functionality enables customers to create a task – assign a name for the task and description as well as the reason the task needs to be completed. The improvement enables users to better communicate and advance submissions amongst underwriting team members.\nConvr AI is invested in improving the user interface for customers and believes this new feature will be supportive of better collaboration and submission visibility. It supports both automated or manually created tasks with a single view of all task statuses viewed under Workflow History. \nTo learn more about Tasks workbench capabilities reach out to Convr at convr.com.

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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
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  • consistent business filings
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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.

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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!

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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.

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