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While most organizations likely didn't invest heavily in AI during the pandemic, the increased emphasis on digital technologies and a greater willingness to embrace change will put them in a better position to incorporate AI into their operations. The COVID-19 crisis will cause structural shifts that will have significant implications for the insurance industry. Some innovative insurers are partnering with external players to offer customers a full suite of services through external application programming interfaces (APIs) and warm handoffs between companies. Please try again later. For example, applied AI is forcing insurers to view customers as distinct individuals with specific customer journeys and demands for products. Adoption of technology will inevitably make some companies significantly more competitive than others, resulting in a redrawing of the competitive landscape. Switching to agile waysof working helped these insurers bring their products to market two to four times more quickly, improved customer satisfaction scores by 10 to 25 percent, and raised productivity by 10 to 30 percent. UBI becomes the norm as physical assets are shared across multiple parties, with a pay-by-mile or pay-by-ride model for car sharing and pay-by-stay insurance for home-sharing services, such as Airbnb. The work is not only about technology; it will also require significant investments in reskilling (and upskilling) employees and reimagining the way they work. This consistency will be empathetic and low-stress for customers. In jurisdictions where change is embraced, the pace of pricing innovation is rapid. More-granular pricing (based on better data capture) is a key way to finance these investments. Most AI technologies will perform best when they have a high volume of data from a variety of sources. The winners in AI-based insurance will be carriers that use new technologies to create innovative products, harness cognitive learning insights from new data sources, streamline processes and lower costs, and exceed customer expectations for individualization and dynamic adaptation. Subscribed to {PRACTICE_NAME} email alerts. Additive manufacturing, also known as 3-D printing, will radically reshape manufacturing and the commercial insurance products of the future. Insurance clients tend to look for clear answers during times of uncertainty.

Some of these shifts will be irreversible. March 8, 2022The insurance industry has advanced into the next stages of digital transformation. This approach helps maintain focus and maximize payoff when working with partners and within ecosystems. 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. In property and casualty, auto insurers have launched mobile apps that allow customers to get an instant quote by submitting a photo of their drivers license. We'll email you when new articles are published on this topic. Now could be a good time to innovate and scale up work on new products and ecosystems that reflect new customer needsfor instance, in health and prevention. Some insurers use AI to transfer information between channels and create a seamless omnichannel experience, letting chatbots and virtual agents provide quick service and transferring customers to traditional agents as needed. Such investments can be the difference between slowly declining and flourishing. Carriers should be prepared to have a multifaceted procurement strategy that could include the direct acquisition of data assets and providers, licensing of data sources, use of data APIs, and partnerships with data brokers. We strive to provide individuals with disabilities equal access to our website. An extended period of volatility, uncertainty, and depressed economic activity will accelerate ongoing changes in consumer behavior, needs, and expectations. 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). New products emerge to cover the shifting nature of living arrangements and travel. 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. Virtually overnight, organizations had to adjust to accommodate remote workforces, expand their digital capabilities to support distribution, and upgrade their online channels. Auto accidents will be reduced through use of vehicles with self-driving capabilities, in-home flooding will be prevented by IoT devices, buildings will be reprinted after a natural disaster, and lives will be saved and extended by improved healthcare. Second, drastic shifts in risk profile, from human-caused risks to technology malfunctions and cyberattacks, will require a new calculus on risk and premium. His personal assistant instructs him to take three pictures of the front right bumper area and two of the surroundings. Finally, leading insurers use talent-to-value diagnostics to ensure that they match the right talent to high-value processes, all while building the most important capabilities when reskilling the workforce. When power goes out, insurers can prefile claims by using data aggregators, which consolidate data from satellites, networked drones, weather services, and policyholder data in real time. McKinsey: How should insurance players prepare for these digital changes? Retaining and growing revenue from an existing customer is usually a better bet than acquiring new clients. Most important, carriers that adopt a mindset focused on creating opportunities from disruptive technologiesinstead of viewing them as a threat to their current businesswill thrive in the insurance industry in 2030. The future of US healthcare: Whats next for the industry post-COVID-19, Getting personal: How banks can win with consumers. Upon hopping into the arriving car, Scott decides he wants to drive today and moves the car into active mode. 3 IoT sensors and an array of data-capture technologies, such as drones, largely replace traditional, manual methods of first notice of loss. Companies with access to customer behavior data will uniquely benefit from this iterative process by being able to produce better-fitting products and to bring concepts to market more quickly. Also, the maturing of cloud and distributed infrastructure is forcing incumbents to migrate out of legacy on-premise servers and into a cloud environment in order to benefit from the scalability and speed of development. The experience of purchasing insurance is faster, with less active involvement on the part of the insurer and the customer. By the time Scott gets back to the drivers 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. Public policy considerations limit access to certain sensitive and predictive data (such as health and genetic information) that would decrease underwriting and pricing flexibility and increase antiselection risk in some segments. For example, insurers are unlikely to gain much insights from limited-scale IoT pilot projects in discrete parts of the business.

Players that embraced cloud environments early are benefiting from faster turnaround with new product launches. Hiring the digital talent needed to drive the necessary digital and analytics transformation can be expensive and time consuming. When Scott pulls into his destinations parking lot, his car bumps into one of several parking signs. Building on the insights from AI explorations, carriers must decide how to use technology to support their business strategy.

Insurers with a good understanding of why customers are calling can optimize calls and route them to the most appropriate service professionals. In addition to being able to understand and implement AI technologies, carriers also need to develop strategic responses to coming macrolevel changes. These cognitive technologies, which are loosely based on the human brains 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 individuals behavior and activities. If you would like information about this content we will be happy to work with you. Violet Chung: Insurers can take four actions: Violet Chung is a partner in McKinseys Hong Kong office. Are you searching the right talent pools? Welcome to the future of insurance, as seen through the eyes of Scott, a customer in the year 2030. In response, leading insurers are investing in long-term reskilling and upskilling to harness the capabilities of their existing workforce through personalized digital learning. Future of insurance: Unleashing growth through new business building. What insurance companies know about customer journeys will significantly change, affecting business models and competitive landscapes. To retain knowledge while also ensuring the business has the new skills and capabilities necessary to compete, many organizations will design and implement reskilling programs. Customers will be embedded into human in the loop optimization processes empowered by AI. Some carriers are already beginning to take innovative approaches such as starting their own venture-capital arms, acquiring promising insurtech companies, and forging partnerships with leading academic institutions.

Customers will also be more acutely aware of their personal and health risks and will demand solutions to help them better manage these risks.

These roles will include data engineers, data scientists, technologists, cloud computing specialists, and experience designers. An in-depth examination at what insurance may look like in 2030 highlights dramatic changes across the insurance value chain. And finally, insurers will more or less automatically underwrite a much wider range of risks using real-world, real-time data from a variety of sources. In 2030, underwriting as we know it today ceases to exist for most personal and small-business products across life and property and casualty insurance. If you would like information about this content we will be happy to work with you. Human claims management focuses on a few areas: complex and unusual claims, contested claims where human interaction and negotiation are empowered by analytics and data-driven insights, claims linked to systemic issues and risks created by new technology (for example, hackers infiltrate critical IoT systems), and random manual reviews of claims to ensure sufficient oversight of algorithmic decision making. Part of this effort will require exploring hypothesis-driven scenarios in order to understand and highlight where and when disruption might occurand what it means for certain business lines.

IoT and new data sources are used to monitor risk and trigger interventions when factors exceed AI-defined thresholds. Demand for digital interactions will spike and stay elevated. At the same time, players that manage to build a strong moat in specialized fields will expand to other niche spaces and redistribute the entire industrys value pool. A North American auto insurer produced a 3 to 5 percent improvement in payout accuracy Please email us at: The Great Attrition is making hiring harder. Regulators review AI-enabled, machine learningbased models, a task that requires a transparent method for determining traceability of a score (similar to the rating factor derivations used today with regression-based coefficients). While no one can predict exactly what insurance might look like in 2030, carriers can take several steps now to prepare for change. Likewise, vehicles will still break down, natural disasters will continue to devastate coastal regions, and individuals will require effective medical care and support when a loved one passes. To remain at the forefront of the industry, insurers will need to have numerous employees with the right technical skills and the commitment to continuously upgrade these skills. Many life carriers are experimenting with simplified issue products, but most are restricted to only the healthiest applicants and are priced higher than a comparable fully underwritten product. The turnaround time for resolution of many claims is measured in minutes rather than days or weeks. 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. AIs underlying technologies are already being deployed in our businesses, homes, and vehicles, as well as on our person. Something went wrong. By 2030, a much larger proportion of standard vehicles will have autonomous features, such as self-driving capabilities. As data becomes ubiquitous, open-source protocols will emerge to ensure data can be shared and used across industries. Meanwhile, contract processing and payment verification are eliminated or streamlined, reducing customer acquisition costs for insurers. World Economic Forum, 2015. In fact, all the technologies required above already exist, and many are available to consumers. Automated customer service apps handle most policyholder interactions through voice and text, directly following self-learning scripts that interface with the claims, fraud, medical service, policy, and repair systems. As soon as the car stops moving, its internal diagnostics determine the extent of the damage. Scotts 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. Furthermore, products are disaggregated substantially into microcoverage elements (for example, phone battery insurance, flight delay insurance, different coverage for a washer and dryer within the home) that consumers can customize to their particular needs, with the ability to instantaneously compare prices from various carriers for their individualized baskets of insurance products. As the external data ecosystem continues to expand, it will likely remain highly fragmented, making it quite difficult to identify high-quality data at a reasonable cost.

Human interaction will remain pivotal in the future, but stakeholders will expect all interactions to have digital support. Scotts 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. As AI permeates life underwriting and carriers are able to identify risk in a much more granular and sophisticated way, we will see a new wave of mass-market instant issue products. Convolutional neural networks contain millions of simulated neurons structured in layers. In the case of an auto accident, for example, a policyholder takes streaming video of the damage, which is translated into loss descriptions and estimate amounts. The experience of purchasing insurance is faster, In 2030, underwriting as we know it today ceases to exist, Claims processing in 2030 remains a primary function of carriers, require talent with the right mindsets and skills. Claims are a promising area for mining additional value. As operations stabilizeeven as the macroeconomic environment does notthe next phase must be focused on embedding resilience and flexibility in organizations and reimagining insurance for the next normal. Rapid advances in technologies in the next decade will lead to disruptive changes in the insurance industry. The next-best conversation applies analytics to an organizations existing data and knowledge about its customers to suggest ways to engage them. 1. Instead, they must proceed with purpose and an understanding of how their organization might participate in the IoT ecosystem at scale. Because of these and other trendssuch as the prevalence of 5G networks, more sophisticated automation and virtualization, and trusted architecturethe foundation of insurance is changing.

Developing an aggressive strategy to attract, cultivate, and retain a variety of workers with critical skill sets will be essential to keep pace. Insurers should not postpone their digital and analytics agendas. Enough information is known about individual behavior, with AI algorithms creating risk profiles, so that cycle times for completing the purchase of an auto, commercial, or life policy will be reduced to minutes or even seconds. The underlying reason for this counterintuitive outcome depends on whether the individual interacting with AI embraces, trusts, and understands the supporting technology. Others will improve severity prediction and early intervention, including identification of claims likely to jump in severity, such as short-term disability claims that become long-term disability claims, auto bodily injury claims, and workers compensation claims. Convolutional neural networks contain millions of simulated neurons structured in layers. 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. As a last component of developing the new workforce, organizations will identify external resources and partners to augment in-house capabilities that will help carriers secure the needed support for business evolution and execution. 1 The authors would like to acknowledge the contributions of Gijs Biermans, Bayard Gennert, Nick Milinkovich, and Erik Summers. Third, value chain evolution. Sophisticated proprietary platforms connect customers and insurers and offer customers differentiated experiences, features, and value. Highly dynamic, usage-based insurance (UBI) products proliferate and are tailored to the behavior of individual consumers. The number of agents is reduced substantially as active agents retire and remaining agents rely heavily on technology to increase productivity. Ramnath Balasubramanian is a senior partner in McKinseys New York office; Krish Krishnakanthan is a senior partner in the Stamford office; Johannes-Tobias Lorenz is a senior partner in the Dsseldorf office; Sandra Sancier-Sultan is a senior partner in the Paris office; and Upasana Unni is an associate partner in the Boston office. Please try again later. Subscribed to {PRACTICE_NAME} email alerts. The plan should outline a road map of AI-based pilots and POCs and detail which parts of the organization will require investments in skill building or focused change management. Technology adoption will inevitably make some companies significantly more competitive than others, resulting in a redrawing of the competitive landscape. 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. As a result, we are seeing scaled personalization in distribution, underwriting, claims, and service to enable tailored experiences based on individual preferences. Claims organizations increase their focus on risk monitoring, prevention, and mitigation. Please try again later. McKinsey: What are some major digital and analytics trends you are seeing in the insurance world? Insurers should develop a perspective on areas they want to invest in to meet or beat the market and what strategic approachfor example, forming a new entity or building in-house strategic capabilitiesis best suited for their organization.

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