With artificial intelligence bringing the insurance industry new capabilities across operations – from product development to underwriting to claims — now is the time to formulate and execute an AI strategy.
As AI plays an increasing role in the insurance industry with aggressive adoption by some major companies, most insurers are moving more slowly, unsure where and how to best deploy these technologies. In our 2018 AI survey, only 51% of insurance executives said that AI technologies were extremely or very important to their company’s success today, which was lower than for any other industry.
Insurers need to pick up the pace of investment. To remain relevant, insurers will need to move quickly to infuse AI throughout their strategy and operations. Those that don’t may discover that it is too late to catch up with their more forward-looking competitors.
The AI edge
AI technologies — including machine learning (ML), neural networks, natural language processing (NLP) and computer vision — can handle an ever-expanding range of tasks more quickly and accurately than humans, while freeing employees to focus on more complex and higher-value activities. AI is enhancing every step in the insurance value chain, including:
Chatbots that deliver customized product recommendations and manage customer service inquiries.
Underwriting that occurs in minutes by analyzing a broad array of external data sources.
Automated claims processing that analyzes images of damage provided by the policy holder or through drones.
New, innovative products created by insurtechs, such as instantly customizable life insurance and on-demand property coverage.
Many daily operational tasks at insurance companies are repetitive, manual tasks that use structured data — ideal targets for productivity-improving, cost-slashing automation. AI applications will enhance the customer experience by providing personalized product recommendations, rapid underwriting and quick resolution of claims. For example:
Amelia, IPsoft’s virtual agent, is used at insurers such as MetLife and Credit Suisse to combine ML with NLP to make decisions based on real-time conversations. Call-center representatives can even receive coaching tips from AI tools that assess the sentiment and mood of a caller while a call is in progress.
Zurich Insurance Group has partnered with the Swedish insurtech Greater Than to allow it to analyze a potential customer’s individual driving data compared to a set of reference profiles created from more than a decade’s-worth of collected data, allowing the company to customize the premium based on the individual customer’s driving behavior.
Haven Life is using ML applied to third-party data such as prescription and driving records to offer real-time underwriting, which allows customers to buy life insurance online in just minutes without a medical exam.
AI will allow the processing of most personal and small business claims to be automated, substantially reducing operating costs. For example, U.S. insurers Allstate and Farmers use image recognition software, or computer vision, to settle auto claims without the need for an adjustor visit.
How to develop an AI strategy
Many insurance companies are unsure what AI investments to make in an environment where technology evolves rapidly and business benefits are unclear. In our view, creating an effective AI strategy should start with the company’s business needs and opportunities rather than with the technology’s capabilities. Although each company’s situation is unique, the following are helpful guidelines for developing an AI plan.
Cast a wide net. Insurers should conduct a comprehensive examination of their business processes to identify where AI technologies can be applied, the potential benefits, the investment and time required to achieve them, and the technical and human capabilities required. Each business challenge needs different AI technologies, techniques and approaches. To ensure the underlying algorithms in AI technologies “understand” the business context in which they operate, cross-functional teams should be established to identify potential AI-enabled improvements to processes and products.
Look for opportunities to leverage data. As insurers assess how to apply AI, they need to identify what data is required for each business process to operate optimally. Generating value from AI depends on access to accurate data, which is a challenge for many insurers. Stronger data governance will be required to address fragmented data architectures that are plagued by multiple legacy administrative systems and databases, often the result of growth via acquisitions. Insurers will also need to gain experience in leveraging external data generated by the explosion of IoT-connected devices.
Acquire AI expertise. Access to experience and skills with rapidly developing AI technologies is essential. In addition to hiring talent, more insurers are partnering with or acquiring insurtech start-ups. For example, Allianz has invested in the digital insurer Lemonade, MassMutual has launched the insurtech start-up Haven Life, and Aviva Canada has created its InsurTech Growth Program to work with innovative start-ups.
Encourage experimentation — and discipline. There are no ready-made, turnkey AI solutions, and each insurer will need to chart its own path forward. For this reason, managed experimentation will be key. Insurers will need an increased tolerance for risk-taking and innovation, and must balance that with rigorous testing and measurement of ROI and tangible business value. It will be important to quickly identify and terminate failures, while moving successful pilot projects into full production.
Prepare business processes for digitization. Applying AI technologies to a poorly designed, fragmented business process will lead to disappointing results. Insurers should consider first optimizing processes through such approaches as system changes, standardization and consolidation. In some cases, insurers will need to integrate fragmented systems that have resulted through a series of mergers and acquisitions — for example, by using a business-process-as-a-service (BPaaS) solution.
Design responsible AI
Applications that make inappropriate or biased decisions can inflict significant reputational damage and loss of shareholder value. Just as they have ethics officers, insurers will need to establish AI ethics policies and procedures to ensure their applications are designed ethically and continue to operate appropriately as they learn and adapt over time.
Unless insurers move quickly, some might soon find they are no longer competitive in the AI-powered insurance environment now emerging.
Three key trends
In conjunction with AI, three trends are changing the face of the insurance industry: an explosion of data, the entrance of nontraditional competitors and the rise of ecosystems.
Insurers now have the opportunity to gain actionable insights from a proliferating variety of new data sources, such as fitness trackers, drones, smart home appliances and telematics in automobiles. These data sources are improving underwriting and claims processing, as well as enabling products where customers agree to share their data with providers in exchange for improved service or lower premiums.
Nontraditional competitors at the gates
Insurtechs, which leverage advanced technologies to introduce innovative products, are proliferating. McKinsey estimates there are now 1,500 insurtechs globally, 38% headquartered in the U.S. Many wield AI technologies to slash costs, speed response times and improve customer service. Life insurer Ladder, for example, offers flexible policies that allow customers to change the size of their policy instantly online, rather than having to cancel and reapply for a new policy. And technology giants like Amazon and Alphabet are also eyeing insurance markets.
Rise of ecosystems
Ecosystems consist of a platform with core components provided by the owner that are extended by applications devised by independent companies to offer new products or services to end users. Ecosystems are arising in a variety of areas relevant to insurance such as housing, healthcare, financial planning and personal mobility. Learning how to compete on these ecosystems will be a new experience for insurance companies.