| | 19 JAN - MARCH 2024Thanks to advancements in AI and machine learning, image recognition technologies can now achieve impressively accurate results. In fact, image recognition technologies used by major insurance players such as AIA have managed to achieve an output accuracy of above 90%. 3.Digitizing Customer InteractionsThe ability to submit claims digitally has also breathed new life into AI applications.Not long ago, all forms and documents were submitted as physical documents that required a person's intervention, as crucial data would need to be manually input into systems.Today, customers simply need to type in information and upload photos of the required documents online. With crucial information available in digital formats, it removes the need for in-person intervention and makes it easier to automate the remaining process via AI solutions.4.Change in the organization culture Organizational cultural changes have led to more successful AI solution implementationChanging the way organizations work is always challenging, especially for processes like claims approval, which have been practiced a certain way for decades. Claims assessors were initially cautious of leaving important decisions to a machine. It is not a surprise that in many organizations, attempts to use AI for claims approval often fail due to human resistance.More insurers are beginning to educate employees about the reliability of data analytics, which has contributed to the acceptance of AI solutions. Such programmes help employees better understand how AI solutions work, and how to manage the risks involved . This also assures employees that AI can improve their work performance instead of replacing them.ConclusionWith advancements in the people and technologies powering AI, the technology is now ready to make its mark on the insurance industry.For example, the implementation of AI solutions in AIA has contributed to time savings and customer experience improvements. AIA has managed to automate 90% of their claims approval processes while achieving an output accuracy of 99.7%. This has reduced the time required to process claims from 2 days to 2 minutes ­ which means that customers can expect a refund in their bank account in less than 20 minutes upon submitting a digital claim. Having seen the advancement of new AI models (i.e. Transformers) with big improvements in the fields of Computer Vision and in Natural Language Process (NLP), we are already exploring the usage of those methodologies, and can soon expect further improvements on the accuracy of AI solutions to automate the claims approval decisions.AI's potential to optimize the health insurance process is ready to be realised. and this presents the industry with a good opportunity to drive AI adoption. By delivering accurate, efficient and speedy processes at a fraction of the time and effort, AI is here to move the industry forward. The first step in the claims process is to manually input claims information for further assessment
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