Transforming Claims with “Service-as-Software”
Introduction
The insurance claims landscape is currently facing significant challenges. A combination of economic and operational factors is creating a profitability squeeze that is testing the industry's traditional operating models. Cost inflation and increasing claim volumes are driving up losses. For instance, in North America, bodily injury severity increased by 9.2% year-over-year in 2024. Additionally, the Insurance Research Council analysis indicates that personal auto losses rose at a 14% annualized rate between 2020 and 2024. In the UK, total claims paid by motor insurers rose to a record £11.7 billion, which is 17% in 2024.1
At the same time, claims processing is slowing. A 2024 review by the UK's Financial Conduct Authority (FCA) found that resolving term life insurance claims can take between 53 and 122 days.2 These delays and rising costs inevitably lead to higher premiums. The Association of British Insurers (ABI) reported that the annual average cost of motor insurance in the UK rose by 15% in 2024 compared to the previous year.1 This strategy of passing costs to consumers is reaching its limit; record premium hikes are fueling record policy shopping, with over 45% of U.S. auto policies shopped at least once in 2024, leading to a 22% increase in policy churn since 2021.3
Higher losses, slower cycle times, customer resistance to price hikes, and tighter regulatory oversight create tremendous pressure. The confluence of all these pressures makes it clear that traditional claims IT systems and manual processes are no longer sustainable. Customers are demanding fast, transparent service, regulators are demanding fairness and oversight, and insurers are having to control costs through a new lever: radical operational efficiency.
The Need for a New Model
Insurers must now rethink claims delivery. Piecemeal automation and legacy “digitalization” have not delivered breakthrough improvements. Instead, the industry is moving toward service-as-software – treating every element of claims servicing as an automated, software-defined service. Under this model, advanced AI systems and bots autonomously deliver entire claims services that humans previously did.
A recent industry example is Snapsheet’s claims platform, which automates the end-to-end process. Its system enables consumers to file electronic First Notice of Loss (FNOL) forms, assigns tasks, dispatches work, and sends payments directly to customers’ bank accounts. For clients like the insurtech Clearcover, this has enabled the settlement of some auto damage claims in under 30 minutes, from First Notice of Loss (FNOL) to payment.4 In effect, claims handling becomes a software-delivered service: always-on, scalable, and built on AI rather than human labor.
What Is “Service-as-Software”?
In an AI-driven world, Service-as-Software (sometimes abbreviated as SaS) extends beyond the traditional Software-as-a-Service (SaaS) model. Where SaaS provides users with access to a tool they must operate themselves, SaS delivers a complete, automated outcome. It is a model where intelligent agents and agentic workflows make autonomous decisions, drive dynamic processes, and render services just as humans would. The cognitive load is now mastered by AI, making it possible for software to deliver services that humans traditionally did.
In claims, this means AI agents can handle intake, documentation, review, fraud detection, and customer communication with minimal human intervention, effectively “delivering” the claims service as a complete, automated package. 5
Table 1 Illustrates the fundamental shift from a manual, linear claims process to a dynamic, automated service delivery model powered by agentic AI.
Table 1
The Evolution from Traditional Service to Agent-Driven Service-as-Software
Dimension | Traditional Claims Service | Agent-Driven Service-as-Software (SaS) |
Process Flow | Linear, sequential, and characterized by manual handoffs between siloed tasks (e.g., intake, review, payment). | Dynamic, parallel processing orchestrated by a central intelligence. Tasks are executed concurrently, and the workflow adapts in real-time. |
Human Role | Focused on process execution: manual data entry, repetitive checks, document review, and direct communication for status updates. | Focused on strategic oversight: managing exceptions flagged by AI, handling complex, high-empathy cases, and continuously improving the system's logic and performance. |
Technology | Reliant on legacy core systems, basic digital forms, and email/phone for coordination. | Built on modern, API-driven architecture featuring agentic AI, multi-agent systems, and integrated data sources. |
Customer Experience | Reactive, often slow, and opaque. Customers must initiate contact for updates, which can result in long waiting periods. | Proactive, real-time, and transparent. Customers receive automated updates, can self-serve 24/7, and experience dramatically accelerated settlement times. |
Business Value | High operational costs, long cycle times, risk of human error, and potential for customer dissatisfaction. | Reduced Loss Adjustment Expenses (LAE), significantly shorter cycle times, improved accuracy and consistency, and enhanced customer satisfaction and retention. |
As illustrated above, this shift involves redistributing work, with routine tasks and decision-making steps being transferred from people to intelligent agents. For example, an AI agent can review an accident report instead of a claims adjuster reviewing it manually. The agent can extract data (via LLM/computer vision/NLP), check policy coverage, and even generate an explanation for the decision, all automatically. The result is reduced human cognitive load, faster processing, and more consistent service. This “agentic AI” approach yields human benefits, including reduced effort, increased productivity, and lower operational costs.
Why Now?
Several trends make this the right time for claims Service-as-Software. First, AI technology – especially Large Language Models (LLMs) and vision AI – has advanced enough to handle complex, unstructured data (documents, photos, voice) in claims. Second, customer expectations have shifted: they demand immediate updates and 24/7 service, which manual teams struggle to provide.5 Third, the cost pressures and labor constraints (rising claim volumes, but limited skilled adjusters) force the use of automation. In short, insurers can no longer improve efficiency by scaling humans alone; they need systems that behave more like “digital adjusters.”
Benefits of Service-as-Software
When executed correctly, this approach can significantly enhance claims outcomes. It enables the touchless processing of eligible claims, achieves higher straight-through processing (STP) rates, and results in a significant reduction of cycle time. Gartner predicts that by 2029, agentic AI will resolve up to 80% of customer service issues, reducing up to 30% of operational costs.6 Moreover, by continuously learning from data, these systems can drive continuous improvement (e.g., detecting new fraud patterns and optimizing reserves).
Conclusion and Next Steps
Claims Service-as-Software is more than just a buzzword; it represents a fundamental shift in the service model of claims. In the remainder of this series, we will explore the underlying Multi-Agent Systems (MAS) technology that enables this, outline a practical implementation blueprint, discuss how Encora can assist in its execution, and identify associated risks and compliance strategies. Insurers need an integrated, agent-driven claims architecture to stay competitive and meet rising demands, and Encora’s experts understand this vision and stand ready to guide carriers through this transformation. References
Motor claims hit record £11.7 billion in 2024 | ABI. (n.d.). The ABI. https://www.abi.org.uk/news/news-articles/2025/2/motor-claims-hit-record-11.7-billion-in-2024/#:~:text=Motor%20insurers%20paid%20out%20a,the%20year%20was%20%C2%A3621.
FCA calls for firms to improve bereavement handling times and shares best practice. (2024, November 22). FCA. https://www.fca.org.uk/news/press-releases/fca-calls-firms-improve-bereavement-handling-times-shares-best-practice.
Auto Insurance Trends Report. (2025, June 18). LexisNexis Risk Solutions. https://risk.lexisnexis.com/insights-resources/white-paper/auto-insurance-trends-report.
Clearcover | Claims Management Software | Snapsheet. (2024, September 12). Snapsheet. https://www.snapsheetclaims.com/case-study/clearcover/
Navigating the Claims Crossroads: An Actionable AI Strategy & Roadmap for Insurance Transformation. (n.d.-b). https://www.encora.com/insights/navigating-the-claims-crossroads-an-actionable-ai-strategy-roadmap-for-insurance-transformation.
Gartner Predicts Agentic AI Will Autonomously Resolve 80% of Common Customer Service Issues Without Human Intervention by 2029 | (2025, March 5). Gartner. https://www.gartner.com/en/newsroom/press-releases/2025-03-05-gartner-predicts-agentic-ai-will-autonomously-resolve-80-percent-of-common-customer-service-issues-without-human-intervention-by-20290.