BẢO HIỂM 2030 - TÁC ĐỘNG CỦA AI ĐỐI VỚI TƯƠNG LAI CỦA BẢO HIỂM
Ngành công nghiệp đang trên bờ vực của sự thay đổi - Công Nghệ. Tập trung vào bốn lĩnh vực có thể định vị các nhà dịch vụ để nắm lấy sự thay đổi này.
Với làn sóng mới của các kỹ thuật học tập chuyên sâu, chẳng hạn như trí thông minh nhân tạo (AI) có tiềm năng sống theo lời hứa bắt chước nhận thức, lý luận, học tập và giải quyết vấn đề của tâm trí con người. Trong quá trình tiến hóa này, bảo hiểm sẽ chuyển từ trạng thái hiện tại của nó "phát hiện và sửa chữa" để "dự đoán và ngăn chặn", chuyển đổi mọi khía cạnh của ngành trong tiến trình. Tốc độ thay đổi cũng sẽ tăng nhanh như môi giới, người tiêu dùng, trung gian tài chính, công ty bảo hiểm và nhà cung cấp trở nên chuyên nghiệp hơn khi sử dụng các công nghệ tiên tiến để nâng cao việc ra quyết định và năng suất, chi phí thấp hơn và tối ưu hóa trải nghiệm của khách hàng.
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Welcome to the future of insurance, as seen through the eyes of Scott, a customer in the year 2030. His digital personal assistant orders him an autonomous vehicle for a meeting across town. Upon hopping into the arriving car, Scott decides he wants to drive today and moves the car into “active” mode. Scott’s personal assistant maps out a potential route and shares it with his mobility insurer, which immediately responds with an alternate route that has a much lower likelihood of accidents and auto damage as well as the calculated adjustment to his monthly premium. 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 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.
While this scenario may seem beyond the horizon, such integrated user stories will emerge across all lines of insurance with increasing frequency over the next decade. In fact, all the technologies required above already exist, and many are available to consumers. With the new wave of deep learning techniques, such as convolutional neural networks, artificial intelligence (AI) has the potential to live up to its promise of mimicking the perception, reasoning, learning, and problem-solving of the human mind (Exhibit 1). In this evolution, insurance will shift from its current state of “detect and repair” to “predict and prevent,” transforming every aspect of the industry in the process. The pace of change will also accelerate as brokers, consumers, financial intermediaries, insurers, and suppliers become more adept at using advanced technologies to enhance decision making and productivity, lower costs, and optimize the customer experience.
As AI becomes more deeply integrated
Four AI-related trends shaping insurance
AI’s underlying technologies are already being deployed in our businesses, homes, and vehicles, as well as on our person. Four core technology trends, tightly coupled with (and sometimes enabled by) AI, will reshape the insurance industry over the next decade.
Explosion of data from connected devices
In industrial settings, equipment with sensors have been omnipresent for some time, but the coming years will see a huge increase in the number of connected consumer devices. The penetration of existing devices (such as cars, fitness trackers, home assistants, smartphones, and smart watches) will continue to increase rapidly, joined by new, growing categories such as clothing, eyewear, home appliances, medical devices, and shoes. The resulting avalanche of new data created by these devices will allow carriers to understand their clients more deeply, resulting in new product categories, more personalized pricing, and increasingly real-time service delivery. For example, a wearable that is connected to an actuarial database could calculate a consumer’s personal risk score based on daily activities as well as the probability and severity of potential events.
Increased prevalence of physical robotics
The field of robotics has seen many exciting achievements recently, and this innovation will continue to change how humans interact with the world around them. Additive manufacturing, also known as 3-D printing, will radically reshape manufacturing and the commercial insurance products of the future. By 2025, 3-D-printed buildings will be common, and carriers will need to assess how this development changes risk assessments. In addition, programmable, autonomous drones; self-driving cars; autonomous farming equipment; and enhanced surgical robots will all be commercially viable in the next decade. By 2030, the proportion of autonomous vehicles on the road could exceed 25 percent, having grown from 10 percent just four years earlier.Carriers will need to understand how the increasing presence of robotics in everyday life and across industries will shift risk pools,
Open source and data ecosystems
As data becomes ubiquitous, open source protocols will emerge to ensure data can be shared and used across industries. Various public and private entities will come together to create ecosystems in order to share data for multiple use cases under a common regulatory and cybersecurity framework. For example, wearable data could be ported directly to insurance carriers, and connected-home and auto data could be made available through Amazon, Apple, Google, and a variety of consumer-device manufacturers.
Advances in cognitive technologies
Convolutional neural networks and other deep learning technologies currently used primarily for image, voice, and unstructured text processing will evolve to be applied in a wide variety of applications. These cognitive technologies, which are loosely based on the human brain’s ability to learn through decomposition and inference, will become the standard approach for processing the incredibly large and complex data streams that will be generated by “active” insurance products tied to an individual’s behavior and activities. With the increased commercialization of these types of technologies, carriers will have access to models that are constantly learning and adapting to the world around them—enabling new product categories and engagement techniques while responding to shifts in underlying risks or behaviors in real time.