세계의 보험용 생성형 AI 시장 평가 : 도입별, 기술별, 용도별, 지역별, 기회, 예측(2017-2031년)

Global generative AI in insurance market is projected to witness a CAGR of 25.10% during the forecast period 2024-2031F, growing from USD 408.32 million in 2023 to USD 2449.40 million in 2031F. Factors such as management of large data, fraud prevention, faster claim management process, and reduction in operational inefficiencies are driving the market growth.

Generative AI uses deep learning to generate text, audio, image, and video by analyzing the patterns in the already existing data. Unlike traditional AI, which is based on supervised learning and a set of predefined rules, generative AI uses unsupervised learning to find underlying patterns in data.

In June 2023, the United States-based founder and CEO of InsuredMine announced the launch of its new AI features for customer relationship management (CRM) users. It features an AI text service that allows agencies and agents to easily create engaging text content for any text message, email, or campaign.

A Faster Claim Management Process to Drive the Growth of Generative AI

Generative AI is driving the growth of its adoption in the insurance industry, speeding up claims processing. Insurers are leveraging the power of generative AI models to automate and smoothen the claim management process, leading to gainful efficiencies and cost savings. It can extract information from all the documents submitted during an insurance claim process. The information, ranging from claim forms and medical records to receipts, can be done with little manual data entry, which leads to minimal errors and speeds up the claim processing period.

Moreover, generative adversarial networks and virtual assistants can make immediate customer support possible through guided claims processing and answering doubts in real-time. Moreover, with the availability of real-time claim monitoring, generative AI empowers systems to create alerts on suspicious patterns or anomalies, which in turn enhances fraud detection capabilities. As such, the accuracy of the processed claims is increased, and insurers are aided with risk management. Further research and development will bring a revolutionary transformation in application of generative AI in the insurance processes.

In April 2024, Swiss Re launched an augmented version of its market-leading underwriting manual, Life Guide. The Swiss Re Life Guide Scout is empowered with new AI-powered, generative underwriting assistants, aimed to support the efficiency and quality of underwriting services.

Management of Large Data to Fuel the Global Generative AI in Insurance Market Growth

The insurance sector faces an unprecedented surge in volume and complexity concerning data handling, which is not possible with traditional methods. However, the landscape has evolved with the emergence of generative AI that can process and analyze large datasets for valuable insights in business. With innovative AI capabilities, insurance companies are better positioned to navigate the complexity of their data and find patterns, trends, and anomalies that might have been overlooked in the past. One of the big factors driving the increasing adoption of Generative AI in insurance is its ability to harness and extract meaningful insights from large datasets as it improves decision-making and operational efficiency, helping the companies to seek an edge over their competitors.

Machine Learning to Dominate the Global Generative AI in Insurance Market Share

Machine learning has dominated the market based on technology, fueling the fast pace of innovation in generative AI for the insurance industry, allowing enriched analytics, automation, and personalization. Core competence in modeling probabilities and outcome predictions, along with its inherently self-improving capabilities from experience, make it indispensable for the tasks of underwriting risk assessment and pricing policies, and virtually necessary for fraud detection. Machine learning algorithms drive predictive analytics, enabling insurers to proactively detect high-risk situations before actual losses, which empowers the development of solutions that meet the changing customer needs and market dynamics. Through the machine learning approach, insurers can automate complex processes and gain insights from large amounts of data to drive operational efficiency and resource optimization offering more tailored products. While machine learning has the top position in terms of adoption, other technologies, such as natural language processing and computer vision, are gaining impressive ground. For advanced consumer experiences, chatbots and automated claims processing apply natural language processing, while computer vision is applied in image and video analyses in claims assessment and underwriting.

In December 2020, Progressive launched the Snapshot program which utilizes machine learning to analyze driving behavior and offer personalized insurance rates.

Fraud Detection and Credit Analysis to dominate the market

The insurance fraud detection market is growing at a tremendous rate amid rising fraudulent activities across the industry. It is expected that fraud analytics will occupy the largest market share since advanced techniques, such as Artificial Intelligence and machine learning, are used to minimize fraudulent activities. Generative AI algorithms can significantly improve fraud detection in the insurance sector through the generation of synthetic data from actual transactions to help prevent fraud. Generative AI algorithms go through many volumes of data to recognize suspicious patterns that represent fraudulent activities insurers may take as appropriate action in advance. In addition, predictive analytics solutions like SAS are deployed by insurance companies to aid in the detection of fraudulent claims and other similar unauthorized activities, especially in health insurance. By analyzing historical data, such solutions can recognize suspicious patterns and help insurers proactively reduce their financial losses from frauds. Due to a rise in cybercrimes and financial frauds, one of the major drivers for the adoption of generative AI and advanced analytics in the insurance fraud detection market is the growing demand for practical fraud detection tools.

In December 2023, Shift Technology released a new case management feature a new add-on module to the Shift Claim Fraud Detection solution designed for claims fraud detection. This new feature will help Insurance companies bring more efficiency and effectiveness to the identification of suspicious claims and behaviors throughout the lifecycle of policies and claims.

North America Dominated the Generative AI in the Insurance Market

North America dominated the generative AI in insurance market, owing to the predominantly mature life insurance market that is technologically advanced, with the highest number of insurance companies, brokers, and reinsurers. These well-established insurance players have grown to be forerunners in the adoption of new technologies, such as generative AI for improving operations, risk profiling, and offering personalized customer experience products. The early adoption of risk assessment measures suggested by generative AI in North America helped the region gain a competitive market advantage. Besides, North America has a well-developed digital infrastructure with good connectivity, which lays the ground for implementing generative AI in the life insurance market. High-speed and reliable internet connectivity, real-time analytics, and smooth integration of generative AI solutions aid in effective data processing.

In June 2024, Sixfold, a New York-based Insurtech company that specializes in generative AI solutions for insurance underwriting raised USD 15 million in a series A funding round led by Salesforce Ventures with participation from Scale Venture Partners, Bessemer Venture Partners, and Crystal Venture Partners.

Future Market Scenario (2024 -2031F)

The future of generative AI within the insurance market is positive with the potential to make a difference in many aspects of the insurance industry, starting from distribution and underwriting to processing of claims and customer servicing. One such area where generative AI will most likely contribute significantly is in the area of hyper-personalization.

Advanced data analytics and machine learning capabilities can be utilized to set up extremely customized insurance products attuned to individual risk profiles and real-time situations, while more accurate risk assessment, dynamic pricing, and personalized customer experiences come into play.

In May 2023, Sapiens International Corporation, a leading global provider of software solutions for the insurance industry, announced an agreement to integrate Microsoft Azure Open AI service. It will help leverage the most advanced, innovative generative AI models and tools in the insurance space.

Key Players Landscape and Outlook

Generative AI in insurance market is very competitive, with major players targeting to grab the majority of market share. Key drivers of competition include efficient operations, increasing personalized insurance experiences in demand, and the ability to leverage AI technologies in such solutions. It will further lead to faster claims processing, more effective customer interactions based on AI-powered assistants, and improved risk assessment and premium calculation enabled by generative AI models.

In February 2024, FWD Group Holdings Limited, a pan-Asia life insurance business, announced a partnership with Microsoft in a four-year agreement that will enable the life insurer to gain access to the latest generative artificial intelligence innovations while continuing to support FWD's cloud-first technology strategy for its business.

Table of Contents

1. Project Scope and Definitions

2. Research Methodology

3. Executive Summary

4. Voice of Customer

• 4.1. Product and Market Intelligence
• 4.2. Mode of Brand Awareness
• 4.3. Factors Considered in Purchase Decisions
  • 4.3.1. Customization and Flexibility
  • 4.3.2. Data Security and Privacy
  • 4.3.3. Reputation
  • 4.3.4. Scalability
  • 4.3.5. Integration Capabilities
• 4.4. Consideration of Privacy and Regulations

5. Global Generative AI in Insurance Market Outlook, 2017-2031F

• 5.1. Market Size Analysis & Forecast
  • 5.1.1. By Value
• 5.2. Market Share Analysis & Forecast
  • 5.2.1. By Deployment
    • 5.2.1.1. Cloud-based
    • 5.2.1.2. On-premises
  • 5.2.2. By Technology
    • 5.2.2.1. Machine Learning
    • 5.2.2.2. Natural Language Processing
  • 5.2.3. By Application
    • 5.2.3.1. Fraud Detection and Credit Analysis
    • 5.2.3.2. Customer Profiling and Segmentation
    • 5.2.3.3. Product and Policy design
    • 5.2.3.4. Underwriting and Claims Assessment
    • 5.2.3.5. Chatbots
  • 5.2.4. By Region
    • 5.2.4.1. North America
    • 5.2.4.2. Europe
    • 5.2.4.3. Asia-Pacific
    • 5.2.4.4. South America
    • 5.2.4.5. Middle East and Africa
  • 5.2.5. By Company Market Share Analysis (Top 5 Companies and Others - By Value, 2023)
• 5.3. Market Map Analysis, 2023
  • 5.3.1. By Deployment
  • 5.3.2. By Technology
  • 5.3.3. By Application
  • 5.3.4. By Region

6. North America Generative AI in Insurance Market Outlook, 2017-2031F*

• 6.1. Market Size Analysis & Forecast
  • 6.1.1. By Value
• 6.2. Market Share Analysis & Forecast
  • 6.2.1. By Deployment
    • 6.2.1.1. Cloud-based
    • 6.2.1.2. On-premises
  • 6.2.2. By Technology
    • 6.2.2.1. Machine Learning
    • 6.2.2.2. Natural Language Processing
  • 6.2.3. By Application
    • 6.2.3.1. Fraud Detection and Credit Analysis
    • 6.2.3.2. Customer Profiling and Segmentation
    • 6.2.3.3. Product and Policy Design
    • 6.2.3.4. Underwriting and Claims Assessment
    • 6.2.3.5. Chatbots
  • 6.2.4. By Country Share
    • 6.2.4.1. United States
    • 6.2.4.2. Canada
    • 6.2.4.3. Mexico
• 6.3. Country Market Assessment
  • 6.3.1. United States Generative AI in Insurance Market Outlook, 2017-2031F*
    • 6.3.1.1. Market Size Analysis & Forecast
      • 6.3.1.1.1. By Value
    • 6.3.1.2. Market Share Analysis & Forecast
      • 6.3.1.2.1. By Deployment
        • 6.3.1.2.1.1. Cloud-based
        • 6.3.1.2.1.2. On-premises
      • 6.3.1.2.2. By Technology
        • 6.3.1.2.2.1. Machine Learning
        • 6.3.1.2.2.2. Natural Language Processing
      • 6.3.1.2.3. By Application
        • 6.3.1.2.3.1. Fraud Detection and Credit Analysis
        • 6.3.1.2.3.2. Customer Profiling and Segmentation
        • 6.3.1.2.3.3. Product and Policy Design
        • 6.3.1.2.3.4. Underwriting and Claims Assessment
        • 6.3.1.2.3.5. Chatbots
  • 6.3.2. Canada
  • 6.3.3. Mexico

All segments will be provided for all regions and countries covered

7. Europe Generative AI in Insurance Market Outlook, 2017-2031F

• 7.1.1. Germany
• 7.1.2. France
• 7.1.3. Italy
• 7.1.4. United Kingdom
• 7.1.5. Russia
• 7.1.6. Netherlands
• 7.1.7. Spain
• 7.1.8. Turkey
• 7.1.9. Poland

8. Asia-Pacific Generative AI in Insurance Market Outlook, 2017-2031F

• 8.1.1. India
• 8.1.2. China
• 8.1.3. Japan
• 8.1.4. Australia
• 8.1.5. Vietnam
• 8.1.6. South Korea
• 8.1.7. Indonesia
• 8.1.8. Philippines

9. South America Generative AI in Insurance Market Outlook, 2017-2031F

• 9.1.1. Brazil
• 9.1.2. Argentina

10. Middle East and Africa Generative AI in Insurance Market Outlook, 2017-2031F

• 10.1.1. Saudi Arabia
• 10.1.2. UAE
• 10.1.3. South Africa

11. Demand Supply Analysis

12. Value Chain Analysis

13. Porter's Five Forces Analysis

14. PESTLE Analysis

15. Transaction fee Analysis

16. Market Dynamics

• 16.1. Market Drivers
• 16.2. Market Challenges

17. Market Trends and Developments

18. Case Studies

19. Competitive Landscape

• 19.1. Competition Matrix of Top 5 Market Leaders
• 19.2. SWOT Analysis for Top 5 Players
• 19.3. Key Players Landscape for Top 10 Market Players
  • 19.3.1. Microsoft Corporation, Inc.
    • 19.3.1.1. Company Details
    • 19.3.1.2. Key Management Personnel
    • 19.3.1.3. Products and Services
    • 19.3.1.4. Financials (As Reported)
    • 19.3.1.5. Key Market Focus and Geographical Presence
    • 19.3.1.6. Recent Developments/Collaborations/Partnerships/Mergers and Acquisition
  • 19.3.2. International Business Machines Corporation
  • 19.3.3. Amazon Web Services Inc.
  • 19.3.4. Avaamo Inc.
  • 19.3.5. Zuriy Marketplace Private Limited
  • 19.3.6. Prudential Financial
  • 19.3.7. Wipro Limited
  • 19.3.8. Leewayhertz Technologies Private Limited
  • 19.3.9. Markovate Inc.
  • 19.3.10. InData Group Pvt Ltd.

Companies mentioned above DO NOT hold any order as per market share and can be changed as per information available during research work.

20. Strategic Recommendations

21. About Us and Disclaimer