Insurtech Highlights: Trends Shaping the Insurance Industry of Tomorrow

Summary

A team of sales and customer success leaders from Skan AI attended the Insurtech Insights conference in New York during the week of June 2, 2025. It was exciting and inspiring to see how various advanced technologies – robotics, IoT/connected devices and wearables, drones, AI-powered solutions, computer vision/recognition, etc. – are being utilized across the insurance sector, and the positive impact they are already making.

Take, for example, how traditional home insurance underwriting is being enhanced through the utilization of satellite and drone imagery. Unlike self-reported data or historical and outdated public records, satellite and drone imagery provide up-to-date, high-resolution visuals of the property and surrounding areas, facilitating better risk assessments and improving underwriting accuracy.

They can also help track changes over time, enabling insurers to make adjustments as needed to continue insuring the property appropriately and adequately, while reducing errors and their own exposure. It also helps address fraud – both, in underwriting and, subsequently, in claims.

Similarly, AI-enabled technologies are helping streamline workflows and operations. For example, advancements in process intelligence technologies have enabled significant improvements in the efficiency of insurance operations, particularly in claims management and underwriting. At Skan AI, we've observed productivity gains exceeding 30% and processing time reductions of up to 40% across various claim types and underwriting processes at several of our clients.

One of the astonishing results we’ve seen is in the utilization of claim adjustors and how it compares across different Insurers. While a few Insurers have been leveraging advanced process intelligence to drive utilization improvements for several quarters, others have recently started measuring claim adjustors’ performance. Insurers that adopted Skan AI and implemented necessary changes show 50%-60% (fifty to sixty percent!) higher process utilization vs. those who are still taking their first steps on the claims transformation journey.

Imagine what unlocking 50% additional capacity within your claims management and adjudication process might mean for your teams and organization! This higher utilization offers significant, quantifiable cost savings and productivity benefits to insurers, improving customer and employee experiences as claims are processed faster and adjudicated more quickly.

This is not an isolated use-case, or an indicator of poorly managed operations within certain Insurers. Rather, this is one example – among many others – of the challenges and opportunities that lie ahead for Insurers, as they look to transform themselves and prepare their operations to address the needs and expectations of tomorrow’s customers.

Challenges in Insurance Operations

As we spoke with numerous Insurers at the conference, a few common operations challenges emerged. We summarize them here.

1. Limited Understanding of Operator Utilization, Leading to Overstaffing and High Operational Costs

• Since the COVID-19 pandemic, remote work has become a standard part of how Insurance operations teams work, but it also seems to have resulted in reduced operator utilization. When productivity is measured by completed claims or tasks per day, low utilization often goes undetected. Efficient operators often complete tasks quickly, leaving them with significant downtime, especially in remote settings.
• Current methods of tracking utilization, such as self-reporting tools or BPM systems, fail to provide a full picture of operator activity. Many tasks are done outside of BPM workflows, making it difficult to measure accurately.
• Low utilization results in overstaffing and elevated costs, which could be mitigated with accurate measurement and monitoring tools.

2. Limited Understanding of End-to-End Processes, Leading to High Costs in Claims Processing and Policy Issuance

• Many insurers rely on a complex web of systems for claims and underwriting, including custom-built applications, mainframes, home-grown and acquired systems, and tools like Microsoft applications, emails, and messaging/chat platforms. Experienced, efficient operators can complete processes two to three times faster than less experienced ones, resulting in high variation in processing times.
• Internal and external operations improvement consultants often introduce various types of technologies including Gen AI, RPA, BPM, etc. that purport to simplify and streamline operations. However, there is limited visibility into the adoption of these technologies and limited understanding of the reasons for low adoption rates.
• Traditional process mining tools, like Celonis and UiPath, have limitations as they rely on log files that do not capture the full scope of activities, especially those done outside of core claims or policy systems. There are multiple attempts to supplement process mining with task mining. However, task mining tools only capture a fraction of operator activities, offering visibility into just 10–20% of tasks.
• This lack of process insight hinders standardization and automation, resulting in the inability to reduce processing times, turnaround times, and operations costs.

3. Lack of Visibility into Service Costs for Different Clients

• Insurance operations teams typically serve multiple clients, and some clients are far more expensive to serve than others – due to factors like demographics, location, business type, etc.
• Without a detailed understanding of unit costs for each client or claim type, insurers struggle to develop appropriate products and adjust fees. Early adopters of technologies that offer granular insight into cost-to-serve stand to gain a significant competitive edge.

Breakthroughs in Process Intelligence and Workforce Management

In our conversations with Insurers, tech vendors and service providers, we repeatedly heard that two key technical challenges hinder the ability to provide end-to-end process intelligence: 

1. The ability to capture all operator activities across different applications. The first challenge lies in observing activities across diverse systems – mainframes, custom applications, web platforms, Microsoft tools, Citrix screens, and more – and combining them into an end-to-end process view using unique identifiers (such as claim numbers). Furthermore, the unique identifier may not propagate or be available across all applications and tools used, necessitating a probabilistic approach to be able to stitch the process together. For example, operators may consult resources outside of the core work system or use Excel for calculations, where the unique identifier may not be present, complicating process tracking using a single unique identifier.

Traditional process mining tools cannot achieve the same level of fidelity as newer tools like Skan AI. Capturing the most complete picture in high fidelity is one of the foundational attributes that sets Skan AI apart.  

2. The ability to do so cost-effectively, at scale. The second challenge involves the cost of processing large volumes of data using computer vision and AI models. This tends to limit scalability. Most tools are only applied for short-term process discovery. However, Skan AI is the only platform that has solved this scalability issue, demonstrating its ability to scale to thousands of workstations.

Skan AI provides insurers with a unique opportunity to address the key challenges above.

Below, we present a benchmark comparison between Insurance leaders who have utilized process intelligence for several quarters and the followers who have just started using it.

Benchmark Comparison Among Group Insurers with Similar Business Lines

The chart below illustrates a significant difference in the utilization of claim adjustors among five group insurers with very similar product lines. The 2 group leaders on the left have been using Skan AI for 4+ quarters. On the right are 3 followers who have recently deployed Skan AI and just started measuring claim adjustors’ utilization. While on the left, the difference in process utilization between top quartile and bottom quartile of claim adjustors is very low (~20%) within the leaders, we see that utilization variability between top and bottom quartile of claim adjustors is considerable for the 3 follower companies on the right. For these 3 group insurers, the bottom quartile utilization is at 40%-50% of the top quartile.

Utilization improvement requires a focused effort. While Skan AI can help measure and monitor utilization, the Insurer needs to ensure their teams and leaders are acting on the data and information provided. The chart below shows an example of one of the leaders who improved people utilization by more than 50% over 5 quarters: from 4 hours per day to 6+ hours per day. The specific steps taken to achieve this improvement are listed to the right of the chart.

Ultimately, by measuring, acting on and monitoring utilization performance, the leaders have been able to achieve a competitive cost advantage in running claims operations significantly more efficiently.

The Future is Bright

Insurtech Insights 2025 was a great source of validation for us. We met with Insurers, brokers, service providers, tech companies and suppliers – all the key players in the Insurance ecosystem.

From our conversations, it is clear to us that Insurers who embrace a data-based approach to driving operational improvements stand to gain significant competitive advantages in terms of productivity, efficiency, cost savings, and customer, member and employee experience.

AI-powered technology solutions such as Skan AI are here to power your business transformation and enable the next level of operational performance.

Let's talk today and we'll show you how Skan AI can guide your business into the AI-powered future of tomorrow.