Published on
17 June 2024
Once perceived as intricate, time-consuming, and even, on occasion, frustrating, insurance claims processing has undergone a substantial transformation with the integration of new technological solutions. From artificial intelligence (AI) to big data and automation, we, as the insurance industry, are witnessing a rapid evolution towards faster, more efficient, and transparent claims handling.
What is the future role of the claims handler?
With the advent of technology, the role of a claims handler has rapidly evolved. To keep up, claims handlers need to embrace digital tools to provide the best experience for their customers.
For the last few years, the industry has been intensely focused on developing two key areas. Firstly, streamlining the value chain through technological integration, encompassing setup and tech finance, and secondly, using data and analytics to measure the speed of claims processing, as well as obtaining real-time insights to enhance overall business operations. These processes, established correctly, will ensure that claims processing sees an overall increase in end-to-end efficiency.
These transitions cannot take place in isolation – the ease of transition is intertwined with the insurance sector’s collaboration with the financial industry. As the technology continues to evolve, staying ahead of the adoption curve will be paramount for insurers looking to provide a superior claims experience to their clients.
Advanced analytics and use of data
Data and analytics are integral components in measuring the speed of claims processing. The ability to access and analyse data in real-time means that insurers can manage funds more effectively, ensuring that there are sufficient resources on the balance sheet to meet claims obligations promptly. Technology also aids in loss fund management, allowing claims to be paid promptly after an event occurs.
Use of AI in claims processing
The integration of AI into claims processing has brought about significant advancements in the industry. AI systems can analyse the vast amounts of data embedded in the claims process, streamline processes through automating basic functions and complete repetitive tasks in seconds, leading to faster response times and less reliance on and constraint by human capacity. Advanced AI analytics sift through vast datasets, extracting valuable patterns and trends that facilitate more informed decision-making.
Managing data allows us to identify and monitor market trends and detect instances of fraud. Additionally, AI models can ultimately enable claims handlers to make faster decisions and reduce the time it takes to assess and settle claims.
Technology in practice
For successful real-time analysis and awareness of emerging risks and trends, a consistent and high-quality foundational data set is required. To that end, we have been carrying out cross-regional and cross-functional reviews of the 25 Loss Code Groups available to handlers to enrich the stories we deliver to our internal clients. By collectively reviewing Cause of Loss Codes (COLs), both the handlers capturing the data at the point of claim, and the actuaries, underwriters and portfolio managers using this data later downstream, have been able to baseline our understanding of the types of claims we have had with more granularity.
Fire claims, for example, can now retrospectively be filtered and categorised into either accidental or arson. This is done by registering the root cause of an accident, for example, as a “short circuit”, “unattended heat works” or “discarded cigarette”. To expedite these historic clean-ups we have been leveraging a Large Language Model solution. This refers to the amount of text a bot has access to or can draw on to make decisions. The more words the model has access to, the better it becomes. This means we are able to review the documentation of up to twenty years’ worth of closed claims to retell the COL story, so it aligns to the new, granular version.
Need for collaboration
The insurance industry's embrace of technology is transforming the way claims are handled, with a clear focus on speed, efficiency, and customer experience. The future claims handler is no longer confined to traditional practices but is at the forefront of integrating AI, digital tools, and advanced analytics.
