4 AI-related trends shaping insurance
This blog entry has been excerpted from a longer paper by McKinsey. Other authors include Ari Libarikian, senior partner; and Doug McElhaney, associate partner. Contributors include Gijs Biermans, Bayard Gennert, Nick Milinkovich and Erik Summers.
AI and its related technologies will have a seismic impact on all aspects of the insurance industry, from distribution to underwriting and pricing to claims. Advanced technologies and data are already affecting distribution and underwriting, with policies being priced, purchased, and bound in near real time. An in-depth examination at what insurance may look like in 2030 highlights dramatic changes across the insurance value chain.
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.2Carriers will need to understand how the increasing presence of robotics in everyday life and across industries will shift risk pools, change customer expectations, and enable new products and channels.
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.