July 11, 2023
CASE STUDY
MMMM D, YYYY
xx min read

Build vs Buy Insurance Software – A Platform View

The decision for an insurance provider to buy vs build a submission ingestion platform should be based on a thorough evaluation of various critical viewpoints.

When property and casualty insuran­­­ce carriers consider whether to buy or build a comprehensive automated submission ingestion platform, several factors should be taken into account. Here are some considerations and the general cost and time aspects associated with building such a platform.

  1. Definition and Scope: It’s critical to gain organizational agreement on the definition and scope of the project. Without this first step, large programs such as this can be doomed to unsatisfactory results. Many insurance organizations identify the critical components of the submission intake or ingestion process to include the following:
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  1. Document splitting and classification
  2. Stages to separate clearance, rating and extraction
  3. Micro services to separate loss runs, SOV’s, ACORD forms, etc.
  4. Enrichment services
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  5. Expertise and Resources: Assess the availability of in-house expertise and resources to develop and maintain the platform. Building a submission ingestion platform requires specialized knowledge in areas such as data ingestion, document processing, data storage, data extraction, optical character recognition (OCR) and integration with existing systems. If the required expertise and resources are readily available within the organization, building internally may be a viable option.Another useful area of expertise is data science as the platform will be most powerful as a “lifelong learner.” When insurance organizations embed machine learning models into their platforms, the system will increasingly learn from captured data. It would also be helpful to have a plan for building connections with in-house data repositories with first and third-party information so that submissions can be enriched with pertinent information prior to transmission to underwriting teams.
  6. Time to Market: Evaluate the time constraints and urgency to implement the platform. Building a platform from scratch may take a significant amount of time, likely a year or more, depending on the complexity and scale of the project. If there’s a pressing need for a solution, purchasing an existing platform may offer a faster time to market. Also, consider that most often platform development plans exceed their expected timelines.
  7. Cost Analysis: Consider the financial implications of building versus buying. Building a comprehensive platform internally involves costs associated with hiring or allocating resources, development, testing, maintenance and ongoing support. Additionally, there may be hidden costs related to unforeseen challenges during development. When purchasing a platform, costs can be well-understood in advance. That may not be so with building internally. You could compare this with building a house, where it’s common for overrides and changes to result in cost overrides of 20% or more. Compare these costs with the upfront investment and ongoing licensing or subscription fees associated with purchasing a platform.
  8. Vendor Solutions: Evaluate the available vendor solutions in the market. Look for platforms that align closely with the organization's requirements and have a successful track record in the insurance industry. This cannot be overemphasized.There are many relatively young entrants in this arena and not all of them are likely to survive the test of time and capital requirements. Additionally, many vendors have broad focus beyond insurance making them potentially less able to deliver with quality results due to the specific terminology and documents utilized by insurers. One last note of caution is the distinction between vendors who utilize offshore labor versus those who use automation to perform the laborious processes associated with the insurance submission process. Automation will likely prove more reliable over time.Lastly, companies must consider actual system performance when selecting a vendor. We recommend insisting on an onsite demo with features to be displayed ad hoc. This approach will confirm actual system capabilities versus those that are manually assisted in the backend or on a roadmap for future development. Of course, you should also consider factors such as scalability, flexibility, integration capabilities, security measures and overall performance. And always ask for references and case studies.
  9. Customization Needs: Assess the level of customization required for the submission ingestion platform. Purchased platforms may offer a range of customization options to meet specific needs, but there could be limitations. Building internally allows for more extensive customization, tailored specifically to the organization's requirements.
  10. Support and Maintenance: Consider the long-term support and maintenance aspects of your decision. Building internally means taking responsibility for ongoing support, updates, bug fixes and enhancements. It also puts pressure on your teams for excellent documentation and development practices to ensure the possibility of future extensibility and integrations. Purchasing a platform typically comes with vendor support and regular updates, ensuring ongoing functionality and performance improvements.
  11. Performance: The performance of internally built submission ingestion platforms can vary based on the expertise of the development team, the underlying technology stack and adherence to industry best practices. Insurers need to focus on factors such as scalability, reliability, speed and accuracy of data ingestion and processing. Performance issues may arise if the platform is not properly optimized or fails to meet the specific requirements of the organization. Rigorous testing and continuous monitoring are essential to ensure optimal performance. Outside providers can be entirely focused on the successful performance of their platform since that’s their primary mission, whereas insurers are in the business of insurance underwriting and pricing.
  12. Industry Benchmarks: Research the success record of insurers who have built their own platforms. This information can provide insights into the performance, cost and time aspects of internal builds in the insurance industry. While specific data may be difficult to obtain without conducting individual case studies, industry reports and discussions with peers can help inform decision-making. Some research makes it clear that time and cost overruns are common.

It's becoming universally accepted that artificial intelligence (AI) and automation are essential to insurance industry competitiveness. A solid ingestion platform with these attributes, built with a focus on efficiency and extensibility—especially as the pace of technological advancement continues to accelerate—is an important asset for insurance industry underwriters and customer-facing personnel. At the start of any digital transformation project, property and casualty insurance carriers must decide whether to buy vs build. When they consider an automated submission ingestion platform it is essential to perform a comprehensive analysis to determine the acceptable time and cost allocations, also taking into account the availability of experienced, internal human resources. The estimated delivery time for internal builds versus purchasing can vary significantly based on project complexity, resource availability and platform sophistication. With that said, it could take a number of months to onboard a purchased system. A realistic expectation for internal builds could range upward from one to two years, or longer, depending on various factors.

According to Brajesh Ugra in his article, Insurance Software Build vs. Buy: Could Speed to Market be the Decider?, Brajesh states, “The savvier companies have decided they are insurance companies and not software companies and are turning to external insurtech insurance specialists to provide core platform technology . . . internal IT teams continue to support core business need . . . in the build vs buy analysis, it comes down to the fact that digitization is bringing in changes at too fast a pace for insurance IT teams to keep up. While proprietary software might sound tempting, the risks are too high and the fear of software getting outdated after a long development cycle is real. Many insurers in recent years have poured in hundreds of thousands of dollars in custom IT solutions that did not measure up in the final analysis.”

According to Mark Breading, a partner in Strategy Meets Action, “The level of integration between possible new systems and existing systems is one of the primary considerations when evaluating buy vs build. In today’s world, most modern solutions have extensive APIs and, in many cases, are already preintegrated with other solutions in the marketplace . . . with a buy approach, you can receive upgrades from a collaborative group of users. The prebuilt solution gives you the benefit of upgrades and enhancements that come from a pool of users outside of your organization. In contrast, using the build approach requires you to continue to modify the solution based on your specific needs. This is important, as innovative software developers are always evolving. If you can’t keep up, important integrations might not work . . .”

Christine Aletti of In Thought Leadership points out that the question of build vs buy for software development should focus on, “. . . Is building software “core” to the company? This framework illuminates whether value is being created or destroyed by the decision to insource or outsource.” In other words, if you’re not in business to create software, don’t do it. Others such as Dave Tobias, Chief Operations Officer and Co-founder of Betterview articulate the issue in a very direct way. Carriers must ask themselves, “Are we an insurance company or a technology infrastructure company?” He goes on to point out that internal teams might be best focusing on thinking and developing at a more strategic level. Ultimately, the decision to buy vs build a submission ingestion platform should be based on a thorough evaluation of the factors and viewpoints mentioned above, combined with a clear understanding of the organization's goals, resources and long-term strategy. If you need an opportunity to discuss this more in depth, schedule a time to meet with our team.

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

XX MIN READ

The Hidden Cost of Manual Data Entry in Commercial Lines Underwriting

Ask a commercial lines insurance underwriting leader where their team's time goes, and the honest answer often isn't underwriting at all. It's data entry: keying in values from an SOV, cross-referencing a loss run against a submission, retyping limits and named insureds from a PDF into a rating system.

On paper, this looks like a minor operational cost, the price of doing business with documents that don't come in clean formats.  

The visible cost of manual data entry is time. A commercial property submission with a large SOV can take an underwriter or their support staff hours to process by hand, checking property values, occupancy types, and construction details against what's on the application. Multiply that across a full pipeline of submissions, and the hours add up fast.

While time is the cost that's easiest to see, it is often the least significant one. The hidden costs are the ones that don't show up until later.

‍The following are four hidden costs underwriting leaders need to consider:


Cost one: decision quality

Every hour an underwriter spends transcribing data is an hour not spent evaluating it. When manual entry eats into the day, the analysis that should happen around a submission -- spotting a concerning trend in loss history, questioning whether a stated property value is realistic, comparing an account against appetite -- gets compressed into whatever time is left.

Underwriting quality doesn't erode all at once. It erodes in small increments, submission by submission, as the ratio of time spent on data handling to time spent on judgment tips further out of balance. See why this is a hidden cost that cannot be overlooked?

Cost two: accuracy risk

Manual entry is also where errors creep in. A transposed limit, a missed COPE field, an incorrectly keyed TIV, these mistakes are easy to make and hard to catch, especially under volume pressure.

In commercial lines, where pricing and terms often hinge on the accuracy of property and exposure data, a small entry error can compound into a meaningfully mispriced risk. The cost of that error rarely surfaces immediately. It surfaces later, at claim time or renewal, when it's far more expensive to fix.

Cost three: inconsistent turnaround time

Manual processes don't scale evenly. When submission volume spikes, whether from a hard market, a new distribution partnership, or seasonal patterns, teams reliant on manual data entry hit a ceiling fast. Turnaround times stretch, brokers wait longer for quotes, and the accounts that move fastest aren't necessarily the best risks. In fact they're often the ones with the simplest paperwork. That's not a formula for disciplined underwriting; it's a formula for favoring ease over quality.  

Cost four: talent and turnover

There's also a cost that's harder to quantify but increasingly difficult to ignore: the toll manual entry takes on the people who are doing it.

Underwriters and underwriting assistants who spend a disproportionate share of their day on repetitive transcription rather than analysis tend to disengage from work that should be intellectually demanding. In a competitive labor market for underwriting talent, that's a retention risk hiding in plain sight.

Why this is solvable now

None of this is a new problem. What's changed is the availability of tools built specifically to solve it. Convr’s structured data ingestion, purpose-built for the ACORD forms, SOVs, and loss runs that make up commercial submissions, can take on the transcription work directly, pulling and validating data with a level of consistency manual entry can't match.

That data then feeds the Risk Context Engine, Convr’s ontology for commercial P&C risk, so a submission doesn’t sit as an orphaned record, it’s tied to the broader risk picture connected to prior submissions, relationships, and appetite history rather than evaluated on its own. That doesn't remove underwriters from the process. It removes the bottleneck standing between a submission arriving and a qualified underwriter evaluating it.

Rethinking where the real cost sits

The instinct to treat manual data entry as an operational cost is understandable.

It doesn't show up as a line item the way software or headcount does. But its true cost is distributed across decision quality, accuracy, turnaround times, and talent retention, all of which matter far more to a commercial lines book than the hours spent on submission entry alone.

The teams that recognize this are the ones rethinking where their underwriters' time really belongs, and building workflows that let judgment, not transcription, define how a submission gets handled.

If you’re ready for a conversation about re-envisioning how your team can improve the underwriting experience while avoiding some of these time sucking hidden costs, visit convr.com and book a demo today.

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XX MIN READ

Convr Prioritizes Communication in Underwriting Workbench

Email

Convr is making it easier than ever to communicate about submissions within the Convr AI Underwriting Workbench. Now there is an email capability where Convr customers can create new messages for submissions. A user would first need to have a specific submission open within the platform to see the email functionality available to them.

Within the left-hand pane they would just need to click, “Email” then “Create New Message.”

From there the “From” section will automatically be generated with their user email and they would need to plug in a recipient email address. The subject line would also be prepopulated with the submission name.

Convr users can also upload submissions assets and additional attachments about the submission in addition to crafting a customized message about the submission.

Comments
Within the Summary screen you can now also add a “Comment” about a submission, and they can be posted anywhere into Forms, Assets, Emails, etc. to support collaboration. Additionally, you can build a thread of comments. You can also reply to your own comment or react to another user’s comment with a thumbs up, as well.

The idea is that you’re creating a record or recorded conversation allowing another user to enter the platform, to get up to speed on the submission chat and join the conversation with the addition of new comments, which will show up within the feed as well.

You can tag users too, so they receive an in-app notification and email. You can also see in-app alerts, click on them and be taken directly to where you as a user were mentioned within the submission. This global, in-app notification feature is useful if a user wants to bring a team member’s attention to a given item within a submission.


The intent is to open lines of communication between underwriting team members to ensure there is greater transparency and oversight of submissions.

Convr is invested in improving the Convr AI Underwriting Workbench user interface for customers and believes these two new communication features will enhance collaboration and visibility throughout the submission process.  
 

To learn more about Emails and Comments capabilities reach out to Convr at convr.com to book a demo.

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XX MIN READ

Agentic AI Doesn’t Just Assist, It Acts

For most of its early history, the Artificial Intelligence (AI) that was used in commercial P&C insurance was a co-pilot. It was an always-on analyst sitting beside the underwriting team surfacing data, flagging anomalies, organizing submissions and more. It was genuinely valuable, yet it still relied on a human to make the call.

Agentic AI changes that equation entirely. It doesn't wait for a prompt or pass-back to a human for every decision. It perceives, reasons, decides, and acts autonomously, within defined parameters, at an unmatched speed and scale. With Agentic AI and the organizational shift from AI experimentation to real‑world execution, new challenges are emerging. If Agentic AI systems are making decisions and taking actions, insurance underwriting teams need to be ready. That means new roles and levels of authority need to be defined. That way, Agentic AI agents will operate within clear boundaries, stay anchored to trusted enterprise data, and scale confidently across the organization, so innovation accelerates without sacrificing governance and control.

The reason Agentic AI requires new operational control is specific to its potential independence of reasoning, decisioning and action. It’s collecting information and getting back to the underwriting team member(s) with a result or response. You're no longer just asking it a question, but giving it the autonomy to perform an action — giving it more authority to operate on your behalf.

When engaged via the Convr AI Underwriting Workbench, your organization benefits from the power of  this reasoning capability within an underwriting workflow. For example, it can act on your behalf sending emails back to a broker for more information. But better still, you benefit from the controls required to customize the workflows to your specific business and governance requirements.

What separates Agentic AI from Assistive AI

Assistive AI is reactive. If you ask it a question, you’ll get an answer. If you feed it a commercial insurance underwriting submission, then you’ll get a summary. It’s powerful precisely because it reduces cognitive load — but the human remains in the loop at every decision point.

Agentic AI is proactive. It doesn't wait to be asked or given a prompt. Given a goal — clear a referral queue, flag a declination, prepare a financial analysis — an agentic system executes the full workflow: gathering relevant data, applying business logic, taking action, and reporting the outcome back to the underwriting team.

Here’s a helpful breakdown:



To learn more about Convr’s Agentic AI capabilities and what we’re doing for customers – get a demo now or read more about it on our newly revamped website at convr.com.


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