February 13, 2024
CASE STUDY
MMMM D, YYYY
xx min read

Accelerating the Pace of Change

In insurance, the acceleration of tech advancement gives us increased hope that we can better understand and manage risk and thereby provide a better CX.

Since Moore’s Law was introduced by Gordon Moore, co-founder of Intel, we’ve accepted that the rate of technological advancement continues to accelerate, just as the number of transistors on a microchip has roughly doubled every two years.  

\n

In the property and casualty (P&C) insurance industry that acceleration of technological advancement gives us increased hope that we can better understand and manage risk and thereby provide a better customer experience. 

\n

Sources of Innovation Acceleration 

\n

At Convr, we work to support the accelerating pace of technological change by understanding issues behind it. Our take is that there are four primary drivers of today’s innovation acceleration: 

\n

1. Need — The increasing universe of perils as well as unprecedented severity and frequency growth are helping drive the accelerating rate of technological advancement in insurance. Climate change, natural disasters, social unrest, and mass immigration are just a few of the exposures demanding new assessment and risk mitigation tools. With new perils ever looming, P&C insurers are focusing their technology investments on these emerging realities as well as other more enduring issues such as efficiency and accuracy. 

\n

2. Appetite — Broad and rapid adoption of the internet, digital tools, mobile devices, cloud storage, apps and more are also supporting innovation acceleration. This convergence of new technologies and the appetite for adoption is spurred by new innovation in many fields with both consumers’ and business users’ escalating expectations for ease and quality experiences. Technology utilization among the youngest in our educational institutions is also fueling this demand for new and innovative technologies. The net result is that broad adoption is forcing organizations of all sorts to embrace technological advancements just to stay relevant. 

\n

3. Advanced Capabilities — Faster computers and greater data storage capacity are helping to drive technology forward. Among the resulting benefits of this are faster computations, even as we develop more complex algorithms and data sets. And with that, we are deriving new insights to support better decision-making and experiences. Furthering this gratuitous cycle, are advances in artificial intelligence, simplified approaches to coding and better data analytics tools – fueling accelerated innovation and information mastery. 

\n

4. Knowledge Sharing — Increased collaboration and data aggregation is also fostering technological acceleration. At Convr, we facilitate this by designing pathways for disparate platforms or networks to be accessed simultaneously for rapid consideration and then disseminated as insights at the moment of decisioning. This “collaboration” between technologies and users facilitates the aggregation of data, better and faster decision-making, and also advances the pace of continuous learning. 

\n

Exploiting Acceleration 

\n

At Convr, we believe within the realm of technology acceleration, hyper-connectivity – deploying big data and artificial intelligence applications to advance business efficiency and decisioning – provides an enormous opportunity for profitable growth.

\n

In the insurance space, we prioritize the following disciplines for exploiting acceleration: 

\n

Data Analytics and AI: Invest in advanced data analytics and artificial intelligence (AI) capabilities to analyze vast amounts of data and identify patterns, correlations, and insights related to current and emerging risks. Machine learning algorithms can help insurers collect and process vast data sets, detect early warning signs, predict trends, and develop proactive risk mitigation strategies. 

\n

Geospatial Analysis: Leverage geospatial analysis tools to assess risks related to climate change, natural disasters, social unrest, terrorism targets, or population movements. Mapping technologies can help insurers understand and visualize the potential impact of these emerging issues for specific regions and properties, enabling better risk assessment and pricing. 

\n

Predictive Modeling and Scenario Analysis: Develop sophisticated predictive models and scenario analysis techniques to assess the potential impact of emerging trends on insurance portfolios. This can help insurers evaluate their exposures, stress test their underwriting appetite and producer strategies, and develop mitigation or remediation plans accordingly. 

\n

Methodical Collaboration: Foster collaborations and partnerships with technology providers, and other innovation accelerators to jointly identify and build solutions that can address improved risk management and mitigation. Thinking creatively about partnerships as opposed to competitors can facilitate knowledge sharing and the development of innovative solutions for the betterment of both the insurance industry and customers. 

\n

Customer Engagement and Education: Harness customer input and then utilize technology to enhance customer engagement and decision-making. With supportive training, we can then deliver new tools that deliver documented financial and operational performance improvement.  

\n

The accelerating pace of change will continue to demand nimble technology adoption for competitive advantage and perhaps survival in many industries, but especially within insurance. Where once there was a claims system there is now an end-to-end policy management system. Where there was a team trained in business intelligence tools like Tableau, there is now a team of data scientists using multiple business intelligence tools and AI.  

\n

With explosive computing power at the core of innovation and active machine learning and AI-driven modeling, early investment will deliver sustained competitive advantage so if you are looking to align technology investments with these innovations, the sooner, the better. 

\n

At Convr, we are committed to helping commercial P&C organizations increase efficiency and profitability with improved understanding, management, and mitigation of known and emerging risks. To do this, we help them adopt the best for-purpose, supportive technology that has the flexibility to evolve with the industry and integrate seamlessly with emerging tools and requirements. In the P&C insurance industry the accelerating pace of change gives us hope that we will continue to better understand and manage risk for a safer world and improved customer experience.  

blogs

Keep Reading

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.

‍

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.

‍

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.


‍

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.