Artificial Intelligence (AI) in Insurance – Thematic Research

The insurance sector faces a myriad of challenges. Insurtechs are disrupting the industry, drawing on AI, cloud services, and IoT to offer lower-cost and personalized insurance coverage, via seamless digital platforms. COVID-19 has hastened the shift towards digital insurance, and providers with superior online offerings are attracting new customers. Falling profitability is another issue, with greater competition driving down prices, and insurers facing an influx of claims due to COVID-19. Technology, and specifically AI, will play a role in improving the efficiency of existing operations while helping insurers to expand product lines and customer service.

GlobalData’s Emerging Technology Trends Survey 2020 found that 80% of insurance executives expect AI to play a role in helping their companies weather the pandemic.

Bigger insurance companies have led the way, but AI adoption is becoming more widespread, with use cases extending further than the basic conversational platforms that were initially deployed. As cloud-based operating systems become more popular, even legacy insurers will begin to implement compatible AI tools. The growing emergence of several specialist tech vendors will further facilitate AI adoption in the sector, presenting a cost-effective approach to using AI versus developing and curating in-house expertise.

Machine learning (ML), computer vision, and conversational platforms hold the most potential across the insurance value chain. These technologies can help with customer service, claims processing, and underwriting. More advanced applications of AI technology include the use of data science and context-aware computing to enhance risk profiling.

Innovation is greater in general insurance lines as products are less complex and easier to underwrite.

While insurtechs continue to disrupt the insurance sector, incumbents hold an advantage as they have access to swathes of historic customer data on which to train AI models, resulting in superior decision-making outputs. Nonetheless, explainable AI practices and algorithmic transparency will need to be integrated into the early stages of AI deployment to safeguard consumer trust.

Scope

Growth forecast (2019-2024) of the AI platform market in the insurance sector, including a regional breakdown of sector spending on AI technologies.

Recommendations on which of the seven key AI technologies should be deployed across the insurance value chain (product development, marketing and distribution, underwriting and risk profiling, claims management, and customer service), and where they will offer the most value.

Several examples of sector-specific AI use cases, in addition to qualitative analysis of the benefits these AI solutions can offer insurance companies.

Identification of the leading insurance companies adopting AI segmented by business line (motor, property, and life insurance), alongside in-depth coverage of the various specialist tech vendors with insurance-specific AI platforms.

GlobalData’s Insurance thematic scorecard which ranks companies in the sector based on investment in ten key themes disrupting the industry, including AI. This is informed by GlobalData’s comprehensive tracking of AI-related deals, job openings, patents ownership, company news, and financial and marketing statements.

Key Highlights

Insurance industry sentiments towards AI are largely positive. According to GlobalData’s Emerging Technology Trends Survey 2020, 56% of insurance executive respondents believed AI would significantly improve operational efficiency over the next three years, with 47% stating that investment in AI would accelerate over the next year.

Primary research reveals that firms in the industry view vendor partnerships as the most cost-effective approach to deploying AI solutions.

General insurance lines have seen greater AI innovation due to less complex products and underwriting processes, but pandemic-induced stay-at-home orders will likely push life insurers to adopt more advanced AI tools.

Using AI will help insurers mitigate against the effects of COVID-19 on business. By deploying tools such as virtual assistants to help with common queries and insurance purchases, and computer vision to remotely assess claims, insurers can meet customers’ changing demands while also improving operational efficiency.

AI can be used to model climate risk. As extreme weather events become an increasing consequence of climate change, insurers have had to improve their ability to model these weather events and their effects on properties. Aon works with Zesty.ai, a specialist tech vendor that uses computer vision and ML to calculate predictive wildfire risk scores for US-based properties.

Reasons to buy

Insurance companies:

Identify leading AI vendors in insurance and pinpoint potential partners based on our comprehensive analysis of where in the value chain, and in which insurance sectors, vendors can best support.

Benchmark your AI strategy against competitors in the sector through access to several examples of successful AI investment case studies and insurer-vendor partnerships. This includes Aon’s partnership with leading vendor Zesty.ai, and Zurich’s collaboration with Greater Than.

Improve existing investment in AI technology by learning where in the insurance value chain AI can be used, and the benefits of those use cases. Discussion of specific insurance business lines helps clarify which AI technologies will be most useful to different insurers, and where to prioritise resources.

Vendors:

Develop marketing messages and value propositions for your AI solutions targeted at potential insurance partners by learning about some of the key insurance sector sentiments towards AI technology and its business benefits.

Quantify the sales opportunity for AI platforms in your regional market by accessing GlobalData’s market growth forecast (2019-2024) segmented by geographic region.

Companies mentioned

Google, IBM, Amazon, Facebook, Baidu, Apple, Nvidia, Intel, AMD, Qualcomm, iRobot, ABB, Robotiq, Teradyne, Festo, Samsung, Sony, Axa, Allianz, Zurich, Ping An, Root Insurance, Lemonade, Tokio Marine, Swiss Re, China Life, Tencent, Alibaba, Munich Re, Metromile, Progressive, Travelers, Aon, Brit, Sentiance, Lapetus, Tractable, Cape Analytics, H20.ai, Cytora, Afiniti, WorkFusion, Sapiens, CCC Information Services, Direct Line, Nauto, Greater Than, Clara Analytics, Shift Technology, Spraoi, Sprout.ai, Zesty.ai, Synthesized.io, Chubb, Flyreel, Anorak, Trov, Bdeo, Euler Hermes, Bold Penguin, Next Insurance, Rakuten

Table of Contents

| Contents

Executive summary

AI value chain

Insurance challenges

The impact of AI on insurance

Case studies

Market size and growth forecasts

Mergers and acquisitions

AI timeline

Companies

Sector scorecard

Glossary

Further reading

| Our thematic research methodology

| About GlobalData

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