Introduction
The claims industry is facing an unprecedented era of transformation, with new technologies reshaping traditional workflows and expectations. Claims departments, sitting at the heart of the insurance industry, play a pivotal role, directly influencing the largest expense item—claims costs. Recent insights from Rising Medical Solution’s benchmarking study (the Rising study) point toward growing challenges—including rising attrition rates and excessive caseloads burdening claims departments. This article examines the challenges faced by claims professionals and explores the transformative potential of artificial intelligence (AI) in enhancing departmental performance.
Overview: Claims problems and AI solutions
| Problem claims professionals face | How AI provides a solution |
|---|---|
| High turnover: Turnover has been on the rise for the past 10 years. It’s getting more difficult to find experienced, talented claims professionals. | AI helps improve consistency and reduce leakage in claims handling practices by consistently evaluating claims, resulting in better claims outcomes. |
| Excessive caseloads: Workloads for many claims professionals exceed recommended maximums, potentially compromising claims-handling best practices. | AI algorithms are designed to complement the expertise of claims professionals, not replace them. By processing much more information than a human ever could, AI flags high-risk information, thereby providing decision support. AI enhances claims professionals’ focus and efficiency by prioritizing critical cases. |
| Tech shortfall: Less than half of claims professionals have predictive analytics and even fewer leverage modern AI. | AI can be easily integrated with existing systems, reducing disruptions and resulting in a more efficient workflow. |
Trending challenges facing claims departments
High turnover
One of the foremost challenges currently faced by claims executives is turnover at the frontline level. Rising’s study shows that attrition among claims departments has been on the rise over the last 10 years, with a sharp increase recently;1 55% of organizations reported turnover in excess of 10% in 2022 and 20% of organizations reported turnover in excess of 20% in 2022. High attrition levels disrupt continuity and efficiency, ultimately having a negative impact on claims outcomes. Finding and retaining skilled claims professionals who can effectively handle increasing caseloads is becoming more difficult.
Figure 1: Claims examiner attrition rates*
*Normalized to exclude those who answered “Unknown.”
Excessive caseloads
As a result of increasing attrition rates, the industry also faces challenging workloads for claims professionals. Insight drawn from the Rising study paints a concerning picture: 32% of respondents indicate indemnity caseloads of 126 claims or more in 2022.2 According to Kern (2019), the recommended maximum caseload is 111 indemnity claims per lost time adjuster,3 although this would likely vary based on the type of claims (highly complex claims would indicated workloads closer to 50 to 75 claims per adjuster). Elevated caseloads signal a potential compromise in the quality of claims handling. Overloaded claims professionals risk potentially derailing established claims best practices, resulting in suboptimal outcomes.
Figure 2: Average caseload per lost time claims examiner*
*Normalized to exclude those who answered “Unknown.”
Technology shortfall
Claims professionals are often buried with tasks including collecting information, managing documentation, authorizing treatment, and more. This challenge is magnified by the fact that 10% of claims account for 90% of total costs, underscoring the importance of quickly identifying high-risk claims to allocate resources effectively. According to the Rising study, only 42% of organizations leverage predictive analytics in insurance claims, and only 55% report using workflow automation.4 Although there has been a slight increase in the adoption of these technologies over recent years, the industry still falls short of fully integrating advanced tools, especially the latest generations of Large Language Models (LLMs), which could revolutionize claims management by enhancing efficiency and precision. Highly performing organizations are roughly 50% more likely to leverage predictive analytics.5
Figure 3: Tech utilization in claims departments
AI in insurance claims: A strategic solution
AI offers a strategic solution to address the challenges faced by claims professionals in managing increasing workloads and maintaining consistency. Below are key reasons why claims professionals need to use AI.
Improved consistency and reduced leakage
With claims departments facing higher attrition rates, AI provides a solution by automating the process of gathering and organizing claims information consistently. For example, modern claims triage solutions use AI to uniformly evaluate claims. This automation not only improves operational efficiency but also ensures a standardized approach for evaluating claims, a necessity in the face of inconsistency due to staff turnover.
Moreover, AI plays a critical role in insurance claims by preventing leakage, mitigating potential errors and omissions. It employs a consistent approach to analyzing claims data, diminishing the risk of missing critical information. This added layer of oversight not only refines the claims evaluation process but also supports downstream activities such as predictive analytics and benchmarking, making it an indispensable tool for modern claims departments.
Greater savings
Given elevated caseloads in claims departments, AI maximizes the value of senior claims professionals. Leveraging the capabilities of LLMs, AI can sift through and make sense of the vast amounts of unstructured text in claims files. This enables the detection of potential high-cost claims at an early stage, leading to a more refined and effective claims triage system. AI can exceed the capacity and consistency of manual review, freeing up claims professionals to focus on cost containment. Further, AI-driven claims triage excels in navigating through extensive datasets, spotting patterns and warning signs of costly claims faster and with more precision than previously possible. This proactive approach not only streamlines workflow but also enhances the strategic allocation of resources, addressing the challenges posed by increasing attrition rates.
Seamless tech adoption
Contrary to the perception that integrating AI in insurance claims is a complex and lengthy process, the reality is far more straightforward. Modern AI-powered claims solutions are designed for ease of integration, enabling claims departments to quickly adopt and leverage these technologies without the need for extensive overhauls of their existing systems. This ease of implementation comes from AI's compatibility with a wide range of data formats and its ability to seamlessly integrate with existing IT infrastructure, making adoption of AI a far less daunting task.
Moreover, the scalability of AI technologies means that organizations can start small, focusing on specific use cases, and then gradually expand their use of insurance analytics and AI as they become more comfortable with its capabilities. This incremental approach significantly reduces the barriers to entry for AI adoption. Claims departments that embrace AI experience substantial improvements in efficiency and accuracy, demonstrating that modernizing claims management through AI is not only straightforward but also beneficial. In our experience, utilizing AI for claims triage has led to a reduction in claim severity of 3% to 10%.
Conclusion
In the face of rising attrition, elevated workloads, and the underutilization of technology within claims departments, AI offers a streamlined, efficient solution to these ongoing challenges. By embracing AI, particularly LLMs, claims departments can modernize processes, enhancing accuracy and freeing up professionals to focus on more complex aspects of claims management. Integrating AI into current systems is simple and practical, setting the stage for a smarter, quicker, and more efficient approach to claims handling. Leveraging AI isn’t just a quick fix; it’s a strategic investment in the future of claims processing.
1 Rising Medical Solutions. 2022 Workers’ Compensation Benchmarking Study, pg. 31.
3 Kern, G.W. (October 26, 2019). Adjuster Case Load Management: A New Approach. RiskSavers. Retrieved March 6, 2024, from http://risksavers.com/claims-handling/adjuster-case-load-management-a-new-approach/.
4 Rising Medical Solutions, op cit., pg. 19.
5 As defined by Rising as organizations with claim closure ratio of 101% or higher. From Appendix D, 70% of high performing organizations leverage workflow automation versus 50% of low performing organizations. 48% of high performing organizations leverage predictive modeling versus 32% of low performing organizations.