utomation in general and artificial intelligence specifically are in the process of dramatically transforming many jobs in the manufacturing and service sectors including insurance. However, not all jobs are equally at risk from the pending revolution in automation and artificial intelligence. The jobs that are least at risk are those that require creativity, human interaction and an understanding of how to learn about human beings or social intelligence.
This includes most jobs in the health care, education, and managerial fields. In contrast, the jobs that are most at risk are those that entail data collection, data processing, and predictable physical work. In their landmark study, “Where machines could replace humans—and where they can’t (yet),” McKinsey’s Michael Chui, James Manyika, and Mehdi Miremadi articulate a clear methodology for understanding the jobs that are most at risk from automation:
An old, traditional service industry where technology-led changes are afoot is insurance. What are those challenges for the insurance sector specifically? Some of the answers can begin to be found in a detailed study with many highly insightful tables from McKinsey Global. There are interesting insights to be derived from the data:
Surprisingly, despite the fact that the financial sector was an early adopter of digital technology, 37% of the time spent in the finance and insurance sectors can still be saved through automation. The savings will undoubtedly be dramatic. Those savings can be found in the following ways:
These figures can serve as a baseline of potential expected savings as automation continues. Indeed, venture capitalists have taken note and insurtech investment activity rose to $17.8 billion in 2021 before declining sharply with the economic crisis to $8.4 billion in 2022 while deals fell 17% from 697 to 579 during the same period. There is however a scale issue in the industry. According to Conning’s “2023 Focus Series: The Current State of AI in the Insurance Industry,” as insurers with under $100 million in annual direct premium written had a low likelihood of adoption (35%).
The most salient factor in the growing use of artificial intelligence is the growth of data in the insurance sector. According to IBM, insurance data is expected to grow 94% in 2018 alone which will provide the raw fuel that supercharges artificial intelligence applications.
Overall, artificial intelligence technologies will marry real-time data from sensors, mobile devices, and the increasingly ubiquitous Internet-of-Things with low-cost data storage in the cloud and geometrically increasing computational power to far more accurately interpret insurance data, develop new products, and incorporate new insights into traditional insurance products and functions such as underwriting, operations and claims processing. In general, AI can help in the following ways:
- Understand – images, language and other unstructured data in claims photos, underwriters’ notes and contact center recordings.
- Reason – by comprehending insurance concepts, forming hypotheses and inferring and extracting ideas.
- Learn – by developing and sharpening expertise with each new data point, interaction and outcome.
- Interact – with employees and policyholders in a natural way that allows cognitive solutions to dissolve barriers between humans and machines.
The insurance industry poses myriad challenges with regard to digital technology. To begin with, the incumbents within the sector have been slow to embrace the application of digital technologies towards customer experience innovation so existing customers interactions with insurance providers are often already dissatisfied.
Secondly, the claims filing process is both data and time-intensive but often uses outdated processes that are highly dependent on human beings with all of the bottlenecks and bureaucracy intrinsic to their foibles. Many different types of data—unstructured and semi-structured—must be gathered and leveraged at the many different stages of the claims management process which includes claims form input, incident documentation, medical reporting, etc. Fraud prevention and identity verification are of salient importance throughout the process as fraud costs the industry $40 billion per year.
The industry has been slow to embrace digital technology because demand for insurance is constant and people have tended to stay with the same provider so profits have only recently faced the same kinds of intense pressures faced in retail and other sectors that have been revolutionized by information technology. This stagnation and the emergence of a new breed of insurance competitors who were “born digital” is why the industry is now primed for radical change as artificial intelligence, machine learning and such have matured to the point that it now possible for new entrants to directly address longstanding customer concerns at scale.
Despite these challenges, at a macro level, AI is having a dramatic impact on the insurance industry due to several specific trends:
- Customer Experience—AI is the New User Interface:
Through tools like chatbots that leverage the ubiquity of smartphones, artificial intelligence can improve customer service while lowering costs (less need to hire large numbers of customer service representatives) as the technology becomes a personalized digital ambassador linking customers, agents, employees and business partners in a seamless interface.
Chatbots are critical because they do not need an app to engage with customers so they don’t burden the user. They can be used to answer many of the basic questions that many customers have, more efficiently gather the data required to assist in claim resolution, cross-sell products and provide personalized reminders concerning matters such as insurance payment.
AI-enhanced chatbots can also be used to improve the quality of human-provided customer service. For example, a $200 million revenue company called LivePerson provides AI-augmenting messaging that uses a “bot assistant to the agent” model. The company believes that this is less frustrating and more effective for consumers. The model works as follows:
Although not insurance-related, this is an important use case because it demonstrates how to manage the fact that, according to Microsoft’s 2016 State of Global Customer Service Report, 78% of young consumers expect service agents to already know their contact and product information when they contact them and 60% of consumers aged 18 to 34 regularly use live chat for customer service versus 45% across all age groups and just a third (32%) of consumers above age 55. The key is to use AI to streamline the interaction and reduce complexity so that the window created by enhanced convenience can be used to cross-sell other products or at least reflects well on the company and its brand.
- Develop the Ecosystem:
Competitiveness in the insurance sector increasingly revolves around insurers developing a digital ecosystem or platform that requires long term engagement with a set of partners and mastery of the ever-evolving technologies that underpin that platform. Indeed, 94% of insurance executives surveyed by Accenture indicated that adopting a platform-based business model will be critical to their business and 76% said that the strength of their partners and the ecosystems they chose will influence their competitive advantage. This means that a focus on collaboration must inform digital strategy particularly as it relates to the use of critical digital technologies such as artificial intelligence.
One of the most important of these AI-enabled platforms are smart home devices such as Alexa, Amazon’s personal assistant that use a natural language interface to respond to questions. These assistants are becoming a larger and larger part of the e-commerce ecosystem which is why Amazon invested in them to begin with; and they won’t just be selling physical products, they will also be used to market financial services such as insurance.
Smart-home platforms are also important to insurers because they can be used as a tool to personalize risk. The data that they gather about individual behavior can be used to both reward and penalize good and bad behaviors respectively such as locking doors and turning off heating when residents are not around. But how do insurance companies manage the challenges of leveraging a platform that you do not fully control to reach the new customers that you need to continue to grow your business? These are the kinds of questions and digital risks that must be confronted as AI-enhanced platforms develop and evolve.
- Design for Humans/Enhanced Personalization:
One of the most important AI-enabled trends will be design for humans which is the next phase in the personalization macro-trend. Data will be derived from all of the myriad digital and physical interactions with both consumers and employees to facilitate the most natural, human and preferred mode of engagement with the customer anchored in an understanding and analysis of corporate capabilities and customers’ actual behaviors and preferences so as to provide optimized real-time services and solutions.
More than a third (35%) of respondents to an Accenture survey indicated that they plan to use data derived from extensive studies of human behavior to inform the development of new customer experience and relationships. Indeed, 80% of insurers agree that organizations that endeavor to understand what motivates human behavior and design their customer experience accordingly will be the next industry leaders.
The data that can be processed by AI tools and technologies will enable insurers to expand personalization beyond marketing and customer service to include product design and hyper-personalized services that are aligned to customers’ personal and workplace behaviors and goals and then adapt to those goals and behaviors as they change over time. To be sure this degree of personalization has privacy implications but research by Accenture has indicated that 57% of insurance customers would be willing to share more of their information with their insurer in exchange for added benefits such as lower premiums or higher quality advice. Thus AI can empower consumers to collaborate with insurers to meet mutually agreed upon insurance goals.
- AI-enhanced Fraud Detection:
Most insurance companies are aware of how automation technologies like Robotic Process Automation can dramatically reduce the time and costs intrinsic to the claims process and this is now an industry focus. But AI can also improve the claims process as it can more rapidly identify patterns in data and help identify fraudulent claims. Through the use of machine learning, AI can interactively learn and discover new cases in new scenarios across broad swathes of data, automatically evaluating damages and predicting the costs from historical data. In this way, instances of fraud can be more easily and reliably detected, especially since AI software can detect patterns that are usually invisible to human agents. Given the costs and risks imposed on the industry by fraud, faster and superior fraud evaluations will have a dramatic impact on the cost structure of the insurance sector while improving customer service.
AI Insurance Companies
There are approximately 130 AI insurance startups in the US. Here are a few:
- Healthcare.com: An online insurance comparison platform for health insurances. It enables users to search, comparison and recommendation tools for healthcare consumers. It uses artificial intelligence and machine learning technology for customized proprietary products. It was established in 2006 in Miami and has raised over $200 million in funding.
- Jerry: Jerry is an AI-driven comparison platform for car insurance. It offers car insurance including property damage liability coverage, auto repairs, medical payments coverage. Users can get quotes from multiple insurance service on the platform. It was founded in 2017 in Palo Alto and has raised $132 million.
- Corvus: Corvus is a provider of AI-based policy development software for the commercial insurance industry. Its products offer first-party and third-party coverage for technology services, technology products, and professional services. It uses proprietary risk models built on billions of data points from IoT sensors to inform underwriting, coverage, and rate while also helping to minimize or prevent cargo damage. Founded in 2017 in Boston, it has raised $162 million.
- Cowbell Cyber: Cowbell Cyber is a provider of AI-based data and monitoring solutions for the cyber insurance industry. It features SaaS-based solutions for risk identification, risk management, and insurance underwriting. It helps in mapping cyber threats for claim filing and claim processing. The company was founded in 2019 in Pleasanton and has raised $124 million.
- Snapsheet: Snapsheet provides cloud-based software for auto insurance claim management. It facilitates pre and post-claim processing along with the underwriting, tracking, validation, auditing and expense management. It provides AI-based automated products- appraisal, transactions, rental & asset management platform and software platform. It also offers a digital payment solution for claims disbursements. The company was founded in 2011 in Chicago and has raised $100 million.
- Lemonade: Founded in 2015, Lemonade is an AI-driven insurance startup that has raised $480 million in venture funding. It offers homeowner’s and renter’s insurance to consumers and does business entirely through its mobile app on which customer can file their claims. The processing of those claims and the provision of payouts is processed faster through the use of AI. Among the AI applications are a chatbot to describe property damage; a fraud detection algorithm to identify suspicious aspects of the claim; and the use of AI to determine the appropriate payout.
- WorkFusion: WorkFusion was established in 2010 and has raised $121 in venture capital. It uses an AI platform called the Intelligent Automation Cloud to help insurance carriers improve their claims and appeals processing such that manual processing can be reduced by up to 85%. Benefits also include faster and better organization of customer data; and more accurate document verification.
It should be noted that all of the AI-driven innovation in the insurance sector is not being conducted by startups. Due to the fact that AI relies upon mountains of data, companies with access to that data are also keen to enter the market. For example, wearables are a valuable source of health data so companies like Apple and Google who have access to a treasure trove of such data through the fitness products they own like Apple Watch and Wear OS are keen to enter this immense market. Apple will reportedly be entering the health insurance market in 2024.
According to McKinsey, all of these trends point to a future of insurance that looks like this scenario:
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 a vehicle with self-driving capabilities 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.
AI will facilitate the integration of the digital and physical worlds by integrating and analyzing data from both arenas. It will facilitate a further reduction of risk in an industry that is focused on risk management. In so doing, it will be at the forefront of introducing AI to the services industries, which will lead to yet another technology-driven revolution.
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