Technology Deficit in Specialty and Commercial Insurance Sectors: An Empirical Study by Coleman Parkes and Hyperexponential

However, despite this wealth of information, many insurers are struggling to extract value from their data and make informed pricing decisions. The outdated pricing models and technology that still prevail in the industry hinder their ability to fully harness the potential of their data. In this article, we will explore the challenges faced by insurers in utilizing their data effectively for better pricing decisions and highlight the need for modern pricing technology and processes.

Data challenges vary by country

Insurers in different countries face varying data challenges. In the United States, the primary issue identified by participants revolves around the lack of real-time visibility into their portfolios. This limitation hampers insurers’ ability to promptly respond to market changes and adjust their pricing strategies accordingly. On the other hand, participants from the United Kingdom point to challenging processes and internal compliance as the main hurdles in harnessing data for pricing decisions. These localized challenges highlight the need for tailored solutions to address specific country requirements.

Perception of Technology by Underwriters and Actuaries

A significant majority of underwriters and actuaries, comprising 83% of respondents, believe that their current technology infrastructure requires improvements. This realization indicates an industry-wide recognition of the shortcomings in existing systems and a desire for better tools to make data-driven decisions. Astonishingly, only 19% of respondents feel empowered by their current technology, underscoring the urgent need for technological advancements in the insurance pricing landscape.

Underdelivering pricing platforms

According to the survey, a staggering 56% of respondents expressed dissatisfaction with their pricing platforms, as these systems were failing to live up to expectations. Furthermore, 45% of participants noted that they have not seen any value derived from their newly purchased pricing technology. This lack of effectiveness and value from the investments made in pricing technology is a cause for concern within the industry.

Time wasted on data entry

Outdated pricing models and technology place a significant burden on underwriters and actuaries. On average, underwriters spend approximately three hours per day on data entry tasks, which could otherwise be utilized for value-added activities such as analysis and pricing strategy development. The inefficiencies caused by these outdated systems result in a tremendous waste of resources and limit the potential for improved decision-making.

Sluggish release of pricing models

Inefficiencies in pricing model development further compound the challenges faced by insurers. US actuaries take an average of 192 days to release new pricing models, while their UK counterparts take an average of 150 days. The lengthy timeframes involved in developing and implementing new pricing models hinder insurers’ ability to adapt quickly to changing market dynamics, leaving them at a competitive disadvantage.

Barriers to underwriting

The rapidly evolving risk landscape poses significant barriers to underwriting. Coupled with the time-consuming administrative tasks that underwriters and actuaries grapple with daily, this presents a formidable challenge. The need for accurate and up-to-date data to inform pricing decisions is paramount, and insurers must find efficient ways to overcome these barriers to stay competitive.

Importance of pricing decisions

Pricing decisions are the most critical lever insurers can pull to drive their profit and loss. Yet, many insurers have struggled to achieve meaningful transformation in their pricing strategies. Outdated models and technology limit their ability to capitalize on data insights and make informed pricing decisions that align with market conditions and profitability goals.

Utilizing pricing insights

The potential value of data lies in its ability to provide actionable insights. When combined with the right data and technology, pricing insights can empower insurers to make better business decisions. By harnessing data-driven analytics and deploying advanced algorithms, insurers can extract valuable information from their datasets, enabling them to optimize pricing strategies, manage risks more effectively, and ultimately improve profitability.

Embracing modern pricing technology

To overcome the challenges plaguing the insurance industry, insurers must embrace modern pricing technology and processes. Those who successfully navigate the shift to data-driven pricing systems will gain a competitive advantage in the Specialty and Commercial insurance sectors. By investing in innovative pricing platforms that leverage artificial intelligence, machine learning, and real-time analytics, insurers can revolutionize their pricing capabilities. These technological advancements will streamline processes, automate tedious tasks, and enable agile decision-making.

In an era of growing digitalization and data availability, insurers must adapt to remain competitive. Overcoming the challenges associated with outdated pricing models and technology is imperative for unlocking the true value of data in insurance pricing. By embracing modern pricing technology and processes, insurers can make better use of their data, improve decision-making, and gain an edge in the market. The path forward lies in harnessing the power of data, empowering underwriters and actuaries, and deploying cutting-edge technology to drive agile and informed pricing strategies.

Explore more

Microsoft Is Forcing Windows 11 25H2 Updates on More PCs

Keeping a computer secure often feels like a race against an invisible clock that never stops ticking toward a deadline of obsolescence. For many users, this reality is becoming apparent as Microsoft accelerates the deployment of Windows 11 25H2 to ensure systems remain protected. The shift reflects a broader strategy to minimize the risks associated with running outdated software that

Why Do Digital Transformations Fail During Execution?

Dominic Jainy is a distinguished IT professional whose career spans the complex intersections of artificial intelligence, machine learning, and blockchain technology. With a deep focus on how these emerging tools reshape industrial landscapes, he has become a leading voice on the structural challenges of modernization. His insights move beyond the technical “how-to,” focusing instead on the organizational architecture required to

Is the Loyalty Penalty Killing the Traditional Career?

The golden watch once awarded for decades of dedicated service has effectively become a museum artifact as professional mobility defines the current labor market. In a climate where long-term tenure is no longer the standard, individuals are forced to reevaluate what it means to be loyal to an organization versus their own career progression. This transition marks a fundamental shift

Microsoft Project Nighthawk Automates Azure Engineering Research

The relentless acceleration of cloud-native development means that technical documentation often becomes obsolete before the virtual ink is even dry on a digital page. In the high-stakes world of cloud infrastructure, senior engineers previously spent countless hours performing manual “deep dives” into codebases to find a single source of truth. The complexity of modern systems like Azure Kubernetes Service (AKS)

Is Adversarial Testing the Key to Secure AI Agents?

The rigid boundary between human instruction and machine execution has dissolved into a fluid landscape where software no longer just follows orders but actively interprets intent. This shift marks the definitive end of predictability in quality engineering, as the industry moves away from the comfortable “Input A equals Output B” framework that anchored software development for decades. In this new