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Insurance 2030 – The impact of AI on the future of insurance

Article Synopsis :

This visionary piece from McKinsey starts with a ‘day in the life’ of Scott, an insurance customer in the year 2030. Self-driving cars, pay as you go, auto-adjudicated claims, if at first the scenario feels too digital to be real, the authors remind us that all of the technologies referenced actually exist today.

 The Digital Insurer reviews McKinsey’s Report on Insurance 2030 – The impact of AI on the future of insurance

AI is not coming to insurance, it’s already here and will dominate underwriting and distribution within five years 

With a new wave of deep learning techniques, artificial intelligence (AI) has the potential to evolve insurance 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 likely 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.

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.

  1. Explosion of data from connected 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.

  1. Increased prevalence of physical robotics

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.

  1. 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.

  1. Advances in cognitive technologies

Cognitive technologies, 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.

AI will ultimately impact every key link in the insurance value chain.  For example:

Distribution: The experience of purchasing insurance will be faster, with less active involvement on the part of the insurer and the customer. Enough information will be 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.

Underwriting and Pricing: In 2030, manual underwriting will have ceased to exist for most personal and small-business products across life and property and casualty insurance. The process of underwriting will be reduced to a few seconds as the majority of underwriting will be automated and supported by a combination of machine and deep learning models built within the technology stack. These models will be powered by internal data as well as a broad set of external data accessed through application programming interfaces and outside data and analytics providers.

Claims: Claims processing in 2030 will likely remain a primary function of carriers, but head count associated with claims will shrink by 70 to 90% compared with 2018 levels. Advanced algorithms will handle initial claims routing, increasing efficiency and accuracy. Claims for personal lines and small-business insurance will be largely automated, enabling carriers to achieve straight-through-processing rates of more than 90% and dramatically reduce claims processing times from days to hours or minutes.

The reports suggests four broad steps to prepare for the AI-driven future:

  1. Get smart on AI-related technologies and trends

Although the tectonic shifts in the industry will be tech-focused, addressing them is not the domain of the IT team. Instead, board members and customer-experience teams should invest the time and resources to build a deep understanding of AI-related technologies. Part of this effort will require exploring hypothesis-driven scenarios in order to understand and highlight where and when disruption might occur—and what it means for certain business lines.

  1. Develop and begin implementation of a coherent strategic plan

Building on the insights from AI explorations, carriers must decide how to use technology to support business strategy. The senior leadership team’s long-term strategic plan will require a multiyear transformation that touches operations, talent, and technology. Insurers should develop a perspective on areas they want to invest in to meet or beat the market and what strategic approach—for example, forming a new entity or building in-house strategic capabilities—is best suited for their organization.

  1. Create and execute a comprehensive data strategy

How carriers identify, quantify, place, and manage risk is all predicated on the volume and quality of data they acquire during a policy’s life cycle. AI technologies perform best when they have a high volume of data from a variety of sources. As such, carriers must develop a well-structured and actionable strategy with regards to both internal and external data acquisition.

  1. Create the right talent and technology infrastructure

The insurance organization of the future will require talent with the right mind-sets and skills. The next generation of successful frontline insurance workers will be in increasingly high demand and must possess a unique mix of technological savvy, creativity, and willingness to work on a dynamic mix of semi-automated and machine-supported tasks that continually evolve. Generating value from the AI use cases of the future will require carriers to integrate skills, technologies, and insights from around the organization to deliver unique, holistic customer experiences. Doing so will require a conscious culture shift for most carriers that will rely on buy-in and leadership from the executive suite.

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Digital Insurer's Comments

2030 is just twelve short years away and we tend to agree with the AI-driven vision of the not-so-distant future spelled out in this report. Implied but not specifically mentioned in the report is the role the Cloud plays in all of this.

Cloud majors such as AWS, Microsoft, Google and Alibaba already offer AI-as-a-Service tools enabling developers to build AI features into enterprise software today. In our view, it’s a major mistake to ignore these advances. New technology tools that your IT department either overlooks or even actively tries to keep out of your organization are actually key to your business future.

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