Piers Williams, Global Insurance Lead at AutoRek
In today’s rapidly evolving insurance industry, integrating cutting-edge technologies such as artificial intelligence (AI), machine learning (ML), and robotic process automation (RPA) offers unprecedented opportunities to improve accuracy and drive operational efficiency in firms. For instance, 84% of insurance executives believe that AI will revolutionise the industry in the next three years.
The potential to leverage technology to transform operations and augment automation is plentiful. We are living in an exciting period with exciting new technologies that allow insurers to gain real-time insights, process more data, and provide added value to businesses.
How can AI & machine learning improve your insurance operations?
ML, a branch of AI, involves computer learning, analysing and identifying patterns in data to make predictions and inform future models. In terms of insurance operations, these technologies can allow for quicker data processing, better resource planning and elevated decision making.
AI tools, such as ChatGPT and Copilot, enables users to analyse and access information at their fingertips. By automating routine data processing and cleansing tasks, AI allows insurance professionals to focus on more value-added activities. However, while AI lets you do more for less, it should be viewed as a supplementary tool. When applied to a financial control perspective, where precision is paramount, the risk of AI error can arise if relied upon too heavily for decision making.
However, when used as a supporting technology, businesses can use AI in improving insurance operations by:
- Supplementing automation and established technologies in the industry
- Acting as a virtual assistant
- Driving efficiency
- Improving accuracy
- Processing data quicker
In addition, it’s important to remember there are lots of interesting opportunities around machine learning, from pattern recognition to data insights.
How can RPA benefit the insurance industry?
RPA is another example of a cutting-edge technology that is transforming insurance operations. RPA uses intelligent automation technologies to perform the repetitive office tasks of human workers, such as extracting data, filling in forms and moving files. RPA can do the heavy lifting, particularly at the data preparation stage.
One of RPA’s key advantages is the ability to operate 24/7, making it particularly valuable in scenarios requiring real-time information processing or managing large volumes of data. RPA’s deployment in insurance is evolving. Traditionally used for system integration, RPA is now gaining new roles as legacy systems are replaced and connectivity improves through open application programming interface (API), offering firms new ways to leverage this technology.
How is cutting-edge technology transforming processes?
The integration of AI, ML, and RPA can profoundly transform insurance operations by enhancing the deployment of intelligence and improving accuracy through rigorous validation of processes. These latest technological advancements drive organisational efficiency by offering insightful recommendations and solutions that bolster precision. They also accelerate decision-making, enabling faster outcomes while strengthening data controls and mitigating manual risks. Overall, this synergy not only streamlines operations but also fortifies the reliability and effectiveness of insurance practices.
How are solution companies leveraging these technologies?
Solution companies are increasingly leveraging advanced technologies to intelligently gather processes and enhance data, driving innovation across various operational areas. They are particularly focused on intelligent data acquisitions and transformation, which allows for efficient data handling, data acquisition and transformation. Additionally, these companies are improving automated matching rates, thereby reducing manual intervention and increasing efficiency.
There is also significant interest in refining the accuracy of suggested matches and exploring ways to fine-tune outputs for improved accuracy and precision. Generative reporting is another exploration area; companies that spend time on manual report generation can streamline this process through automation. Finally, the development of AI configuration builders is enabling these companies to create new processes and improve existing solutions, leading to more adaptive and scalable solutions.
Key takeaways for businesses
Technologies such as AI, machine learning, and RPA hold significant potential to drive efficiency, improve accuracy, and transform insurance operations. AI in particular, serves as a supplementary and supportive technology, enabling various processes without completely replacing human input. However, RPA can be efficiently leveraged to reduce manual tasks and mitigate the associated risk, allowing for more strategic work. More and more companies are continuing to explore ways to gather and enhance data more intelligently, aiming to optimise operations and deliver greater value in the insurance sector.
