As technology continues to develop, the re/insurance sector continues to adapt and apply various methods into their systems to change the way how certain tasks are completed, ultimately allowing for automation and saving valuable time that can be used for future tasks.
Artificial intelligence (AI) remains a heavy topic in the industry, with many different organizations experimenting and testing the technology across their systems.
However, a recent method that has been conducted by data specialists at AM Specialty, showcases a way to leverage advanced semantic understanding and natural language processing (NLPs) models to process claims bordereaux automatically, which can save time and many costs.
Nishad Lad, Head of Data at AM Specialty, recently spoke to Reinsurance News about a number of different topics associated with the method, and how it can impact the re/insurance industry.
Firstly, Lad named some of the key advantages that introducing NLPs for managing bordereaux brings.
“One of the main advantages is efficiency. When a human reads through a bordereau, it’s time-consuming as they must thoroughly verify each detail to ensure accuracy. However, an automated system with NLP fundamentally changes this. While the automation accelerates the task; NLP enables the system to understand the necessary checks and extractions, thereby allowing it to process a bordereau within seconds.”
“The other key advantage is accuracy. Humans might sometimes miss details, but an automated system with NLP ensures thorough and consistent task execution. Crucially, NLP helps the system in understanding and aligning different terminologies used in various bordereaux. It interprets these varying terms, ensuring they correctly correspond to the intended data points. This capability is essential for accurate and consistent data processing across different sources.”
Staying on the topic of bordereaux, Lad also explains how modernizing bordereaux processing with cutting-edge technological solutions can lead to major cost efficiencies.
“When we were conducting the method, we gave one of our analysts a bordereaux and got them to go through it and put in all the claims in our system and complete all the necessary checks like you normally would. Then when we did the same with the NLP-based automated system, it completed it so quickly that it practically felt effortless. A human can spend a good half hour/one hour completing a bordereaux, while an automated system can do it within seconds, which ultimately can save a lot of money.
“Also, having this technology in general gives organizations a competitive edge, because the technology is going to open the door to so many more opportunities. More people are trusting this technology within the insurance sector because they can see it is making their overall processes very robust too.”
With AI and NLPs creating quicker and more efficient ways of completing such tasks, a major concern across the industry is whether this form of automation could wind up leading to job losses across the sector.
However, Lad believes that this technology will create more job opportunities.
“In our company, we do not want to replace anyone by all the automated systems that we build. The systems that we create are always aimed at making the operational tasks more efficient. What our system does, is that it simply takes away the data entry and genuinely mundane tasks, and it allows for people to concentrate on the many other areas that their job role includes. The systems we design are designed to provide help, but not take away an entire person’s job.”
Lastly, Lad also addressed how incorporating AI-driven anomaly detection helps to enhance data security, and whether he feels that more companies should be incorporating it into their platforms.
“Humans can make errors, it does happen. But, if you are using a system that is coded to complete a particular task, you know it is going to be 100% correct and accurate. This helps to ensure that there are not going to be any mistakes that go into that data, which saves you from the additional time that you spend correcting that data.”
To learn more about transforming insurance operations with AI, you can read AM Specialty Insurance Company’s free whitepaper, Elevating Insurance Workflows: Strategic Analytics through Automated Bordereau Processing, written by Nishad Lad (Head of Data), available for download here.