“Welcome to the future of insurance, as seen through the eyes of Scott, a customer in the year 2030 (...) Scott’s assistant notifies him that his mobility insurance premium will increase by 4 to 8 percent based on the route he selects and the volume and distribution of other cars on the road. It also alerts him that his life insurance policy, which is now priced on a “pay-as-you-live” basis, will increase by 2 percent for this quarter. The additional amounts are automatically debited from his bank account.

When Scott pulls into his destination’s parking lot, his car bumps into one of several parking signs. As soon as the car stops moving, its internal diagnostics determine the extent of the damage. His personal assistant instructs him to take three pictures of the front right bumper area and two of the surroundings. By the time Scott gets back to the driver’s seat, the screen on the dash informs him of the damage, confirms the claim has been approved, and reports that a mobile response drone has been dispatched to the lot for inspection. If the vehicle is drivable, it may be directed to the nearest in-network garage for repair after a replacement vehicle arrives”-McKinsey & Company., 2021 

Artificial Intelligence (AI) is not just a buzzword; it is a transformative force that is reshaping industries worldwide, and the insurance industry is no exception. This has led to a significant acceleration in the adoption of AI's underlying technologies, from underwriting and claims processing to customer service and risk management, creating a true revolution in every aspect. In this article, we will explore the most typical use cases where AI is driving major changes in the industry.

First and foremost, AI has already had a significant impact on the underwriting process. At Perifai, we have streamlined underwriting into an automated process that takes just seconds. By capturing just six images, we assess the external conditions of the vehicle and recommend the optimal policy option through a fusion of machine and deep learning models.

In addition, for various insurance policies (e.g., life, home, etc.), we are witnessing an explosion of data coming from connected devices. According to the World Economic Forum, there will be up to one trillion connected devices generating data by 2025. This surge in data should facilitate the creation of more personalized and customized insurance policies, tailored to the insights derived from the processed data.

In addition, this trend is driving the emergence of "open source and data ecosystems," where data collected from different industries is shared and leveraged across sectors. Consequently, this development paves the way for the adoption of usage-based insurance (UBI) as a prevalent trend within the industry. Models such as pay-by-mile or pay-by-ride for car-sharing services and pay-by-stay insurance for home-sharing platforms such as Airbnb are gaining traction, in line with this shift towards data-driven, personalized insurance solutions.

In addition to advances in underwriting and policy creation, the claims process has undergone significant change. McKinsey & Company predicts that by 2030, more than half of all claims processes will be automated. Currently, at Perifai, we have already automated more than 40% of our clients' claims within the insurance industry, revolutionizing the process.

Our automated system allows users to capture six images to initiate a seamless process. Using artificial intelligence algorithms, we can quickly assess external damage in less than 20 seconds. This efficiency not only speeds up the claims process, but also increases accuracy, ensuring prompt and fair settlements for policyholders.

Challenges and considerations

While the potential benefits of AI in insurance are enormous, it's important to recognize and address the challenges and considerations associated with its adoption. Data privacy and security remain paramount, as insurers deal with sensitive personal information that must be protected from unauthorized access and misuse. Ensuring compliance with regulations, such as GDPR and HIPAA, is critical to maintaining consumer trust and avoiding regulatory penalties.

In addition, as AI technologies become more sophisticated, there are growing concerns about algorithmic bias and fairness. Insurers must ensure that their AI models are trained on diverse and representative datasets to mitigate the risk of biased outcomes, particularly in areas such as underwriting and claims, where decisions can have a significant impact on individuals' lives and livelihoods.

Conclusion

In conclusion, the impact of artificial intelligence on the insurance industry is profound and far-reaching, revolutionizing underwriting, claims, customer service, and risk management. By leveraging AI technologies, insurers can automate processes, improve the customer experience, and make more informed decisions, ultimately increasing efficiency and profitability. However, as AI continues to evolve, insurers must address ethical, regulatory, and technical challenges to realize its full potential while ensuring fairness, transparency, and accountability. Embracing collaboration, innovation, and responsible governance will be key to harnessing the transformative power of AI and shaping a more resilient and inclusive insurance industry for the future.

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References:

• https://www.researchgate.net/profile/Naman-Kumar-3/publication/337305024_Artificial_Intelligence_in_Insurance_Sector/links/5dd00e33a6fdcc7e138761cc/Artificial-Intelligence-in-Insurance-Sector.pdf
• https://anuarioseguros.lat/admin/storage/files/impacto_de_la_ia_en_el_seguro_en_2030.pdf