Artificial Intelligence (AI) is rapidly transforming the insurance sector, reshaping how organisations operate and deliver services. In recent years, organisations have recognised AI’s potential to improve efficiency, provide deeper insights, and revolutionise operations.
Underwriting has traditionally been at the forefront of digital innovation. However, according to a report from Sprout.ai, in the last two years, the spotlight has shifted to claims.
The report titled The Business Case for AI in Claims highlighted that insurers are dedicating more resources to improving the claims function, understanding its critical role in customer experience and overall business strategy.
AI adoption in claims is being explored in several key areas. For many organisations, the integration of AI into existing systems has been the first step. Others have opted for more customised solutions tailored to their unique needs. The prevailing trend, however, is the move towards using AI as an assistant to enhance human decision-making rather than replacing human workers altogether.
This “Co-pilot” or “AI Assistant” approach focuses on automating routine tasks to support claims handlers. Rather than eliminating jobs, AI is becoming a tool to augment human expertise, allowing staff to focus on more complex decisions while AI handles repetitive tasks.
In addition, AI is being used to tackle large-scale challenges that humans alone could not manage, such as analysing vast volumes of claims documents to extract insights and identify patterns for loss prevention or policy optimisation.
Several AI use cases are gaining traction in claims departments. Automated decision support, for example, is enhancing accuracy and consistency in decision-making, allowing insurers to triage claims more effectively. AI has been found to also play a key role in First Notification of Loss (FNOL) processing, automating the initial intake of claims information and reducing the time it takes to extract relevant data.
AI’s predictive capabilities are also increasingly being leveraged. Insurers are using AI to forecast key variables, such as reserve values and the likelihood of claims leading to litigation. This predictive power helps claims managers identify high-risk cases early.
Furthermore, fraud detection is another area where AI is making significant strides. By identifying anomalies and patterns in claims data, AI systems can uncover fraudulent activities that would otherwise go undetected.
Despite the growing use of AI in claims, organisations are at varying stages of implementation. Some companies have sophisticated AI models and processes in place, while others are just beginning to explore the possibilities. One of the main challenges insurers face is determining where to start.
To overcome these challenges, experts have suggested strategies for successful AI adoption. One important consideration is whether to partner with an external AI provider or build in-house expertise. Companies are also advised to assemble the right team, with clear ownership of AI initiatives, and to address ethical and privacy concerns from the outset.
Additionally, running Proof of Concepts (PoCs) and pilots can help insurers test AI solutions in controlled environments before scaling them across the organisation.
Do you have something to say about this story? Share your comments below.
