“Brokers are constantly evaluating underwriters," insurance veteran Tony Tarquini said in a recent webinar that I participated in. As a digital transformation expert, I’ve increasingly witnessed the broker-underwriter partnership being tested.
In the market these days, underwriters are pressed for higher quote volumes while needing to stay focused on quality risk selection, and brokers are pushing for faster turnaround times. With the staggering amount of data available to analyze, is it fair to expect underwriters to produce fast and accurate quotes using legacy systems?
In a fiercely competitive market, both underwriting delays and inaccuracies are unacceptable. While data is essential to gain real insights to assess risk accurately, sifting through large volumes in multiple documents and screens results in a massive slowdown. Hence, there is a sincere need for insight-driven data orchestration and enhanced efficiencies through automation across the risk life cycle. But are underwriters ready for the big shift?
In the recent webinar, “The Underwriting Maturity Framework,” my colleague Lloyd Peters and I discussed the current maturity level of underwriters, exchanged ideas on how to inspire change in the community, and discussed the value of having a road map to go from process-centric to data-centric underwriting at their own pace.
Here’s how underwriters can embrace automation and eliminate "Gen-AI-nxiety":
The change is inevitable
Today, insurers are looking to stay ahead and are seeking advanced risk assessment solutions. The focus has shifted from cost and efficiency to risk selection, pricing, customer-centricity, and AI enablement. Hence, underwriters must embrace technology to keep pace with the growing demands of the industry. The great news is underwriters now have access to emerging technologies and AI to support this transition.
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The first step: Breathe
The good news is underwriters don’t need to attempt transformation overnight. To acknowledge the need for change, one must be convinced it’s the right thing to do. A great place to start is to use an underwriting maturity model to benchmark where you’re starting from. This model provides a powerful visual of an underwriter’s current capabilities, allows them to identify both independent and interdependent business priorities, and accordingly identifies their level of maturity so they know where they’re starting from.
The next step: Self-assessment
The underwriting maturity framework is a practical, easy-to-embrace mechanism to make the necessary shift from manual to smart underwriting. There are five stages to this model, and each stage signifies the current capabilities of the underwriter.
- Stage 0: Manual Underwriting - Traditional manual, off-system underwriting with information sorted within documents and isolated Excel files. Work is allocated through email between teams.
- Stage 1: Digital Underwriting - Enable existing underwriting flow with a structured workflow engine and document/data storage where teams can collaborate.
- Stage 2: Connected Underwriting - Optimize the underwriting flow by leveraging technology to accelerate and automate key steps, allow data transfers, and replace manual steps across the submission-to-bind journey.
- Stage 3: Augmented Underwriting - Harness the power of the business and operational data captured through digital underwriting to provide targeted insights to underwriters on portfolio position, market, and risk characteristics.
- Stage 4: Smart Underwriting - Enable the system to make automatic, algorithmic underwriting decisions in certain scenarios and provide recommendations to underwriters in others.
The maturity framework allows underwriters to identify capabilities that are key to executing their underwriting strategy, which will be specific to the line of business, geography, and complexity of risk that they write. What’s meaningful for one carrier may be less important for another, so having clarity in that strategy (growth, new products, efficiency, etc.) will help determine where you go first. This model highlights how connected all the components through the value chain are, and why it is important to get your underwriting data needs understood, work with operations, data, and IT to craft the right roadmap together.
The final step: Outline goals
Once you have clarity on your current state, plot your deliverables around each phase that will support identified goals. Start putting the building blocks around the desired underwriting capabilities across the next six, 12, or 18 months. The aim is to move the current operating state into a more data-driven state that advances the strategy and where the collective teams see immediate benefit—dramatically improved quote turnaround times, better clarity, and consistency on risk selection with more accurate pricing.
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Remember
It is important to keep in mind that technology is only a part of the solution. Engagement from operations, data teams, application and infrastructure architects, etc. must be fully aligned to see success in smart underwriting. The way the insurance industry works is changing. The underwriting evolution is here. The tools are available. The potential is significant. Now is the time. Embracing automation is one of the best decisions in an underwriter’s career.
