AI in Insurance Market, Outlook by Types, Applications, Opportunity, Technology, and End-User Analysis Development Status, Forecast by 2027
Market Scenario:
Market Research Future (MRFR) report on the global AI in Insurance Market (2019-2025) addresses the COVID-19 analysis of a critical factor affecting the market growth. The research examines competition in the regional and global markets, providing a holistic evaluation of factors that could have a significant impact on the industry’s outlook over the forecast period.
Artificial Intelligence is affecting every step of the insurance value chain. AI technologies like machine vision, machine learning and deep learning, natural language processing (NLP), and robotic automation can re-imagine the entire insurance lifecycle from customer acquisition to claims processing. Adopting AI allows insurance companies to stay competitive on the market, drive operational excellence, and boost growth.
Machine learning and deep learning algorithms help drive smart, automated applications like healthcare diagnosis, predictive maintenance, customer service, self-driving cars, automated data centers, and smart homes. The rising need to offer personalized insurance services and automate the operational process are factors propelling the growth of Artificial Intelligence in Insurance industry around the globe. AI technologies are capable of managing vast quantities of customer and enterprise data and different tasks more efficiently and reliably compared to humans, enabling insurance professionals to concentrate more on challenging and high-value activities. AI is becoming an expert at recognizing faces or images and spoken language with the aid of technologies like NLP and computer vision that give intuitive experience. In addition, the increasing acceptance of IoT technology is also expected to fuel market growth. Growing volume and speed of data generation with the adoption of IoT is anticipated to push the need to automate the process of generating actionable insights using advanced machine learning and deep learning algorithms.
Nevertheless, the lack of technical expertise related to complex AI algorithms is hindering market development. The industry is looking for opportunities for advances in machine learning and deep learning algorithms. Whereas the risks associated with data leakage and cybersecurity breaches are significant challenges facing the industry.
Interactive insurance chatbots, insurance analytics, customized claims settlements, behavioral premium pricing, fraud, and risk management are various AI cases in the insurance industry. Adoption of UAVs and smart devices for extreme surveillance are the prevailing trends in the market. The insurance industry is expected to be mainly impacted by technologies such as blockchains and big data analytics.
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Competitive Outlook:
The prominent participants active in the global market of AI in insurance are
Insurify (US), Planck Re (US), Insurmi (US), PolicyPal (
Segmentation:
The global market for AI in the insurance has been segmented into components, technology, deployment, application, and sector.
By component, the global AI in the insurance market has been segmented into hardware, software, and services.
By technology, the global AI in the insurance market has been segmented into machine learning and deep learning, machine vision, robotic automation, and natural language processing (NLP).
By deployment, the global AI in the insurance market has been segmented into on-cloud and on-premise.
By application, the global AI in the insurance market has been segmented into claims processing, chatbots, risk management and compliance, personalized recommendation, and others.
By sector, the global AI in the insurance market has been categorized into life insurance, health insurance, title insurance, auto insurance, and others.
Regional Analysis:
By region, the global AI in the insurance market has been segmented into
The
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Table of Contents:
1 Executive Summary
2 Scope of the Report
2.1 Market Definition
2.2 Scope of the Study
2.2.1 Research objectives
2.2.2 Assumptions & Limitations
2.3 Markets Structure
Continued....
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