세계의 보험 분석 시장 : 구성요소별, 전개 방식별, 용도별, 최종사용자별, 지역별, 기회 및 예측(2018-2032년)

Global insurance analytics market is projected to witness a CAGR of 11.12% during the forecast period 2025-2032, growing from USD 14.02 billion in 2024 to USD 32.59 billion in 2032. The global insurance analytics market is driven by the increasing adoption of big data and AI technologies to enhance risk assessment, fraud detection, and customer personalization. The growing demand for data-driven decision-making, regulatory compliance requirements, and the need for operational efficiency further propel market growth. Additionally, the rise of insurtech startups, the integration of IoT devices, and the expansion of cloud-based analytics solutions contribute to market expansion. Emerging markets and the shift toward predictive analytics also play a significant role in shaping the industry's future.

In an increasingly competitive insurance landscape, the demand for advanced analytical solutions is intensifying as organizations seek to differentiate themselves and secure a stronger position in the global marketplace. Companies are embracing scalable, efficient analytics platforms to address mounting risk exposures, enhance disaster response capabilities, and ensure compliance with evolving regulatory standards. Moreover, heightened competition is fueled by consumers' access to instantaneous online quotations and tailored insurance offerings from multiple providers around the clock. These dynamics are collectively accelerating the adoption of insurance analytics among leading industry participants and represent key drivers of market expansion.

For instance, in May 2025, IBM Cloud announced a series of new partnerships and new offerings with the purpose of advancing AI transformation in response to the changing regulatory context. These solutions provide insurers with advanced capabilities in predictive analytics and risk, while still using secure and compliant infrastructure, demonstrating the importance of cloud providers in supporting data-driven innovation across insurance.

Increased Implementation of AI and ML Drives Global Insurance Analytics Market Demand

The rise in application of Artificial Intelligence (AI) and Machine Learning (ML), further unlocked demand for insurance analytics in the global market. Insurers are using AI and ML technology for better data processing capabilities, creating better risk assessments, detecting fraud, and assessing claims. AI and ML models can sort through vast amounts of structured and unstructured data and continuously assess risk in a timeframe that allows insurance companies to make faster and increasingly immediate decisions based on data. This not only enhances operational processes but also allows them to design personalized insurance products and create a system of dynamic pricing. As competition heats up and customer expectations rise, it's no longer a choice for insurance analytics to deploy AI and ML technology; it is simply how to innovate and enhance profitability and will either be a departure from business together in the insurance industry, or long-term sustainable innovation.

For example, in May 2025, Axa S.A. and Allianz SE adopted AI at scale in the insurance sector to evaluate across four pillars-Talent, Innovation, Leadership, and Transparency-both insurers scored within the top five, demonstrating sustained, and strategic investment in AI over multiple years.

Rising Demand for Data-Driven Risk Assessment and Fraud Detection

As insurance claims continue to grow in complexity and fraud is constantly evolving, insurers are looking to data-based analytics as a new pillar for risk management. Using data-based tools to better identify outliers, understanding the risk profiles of their policyholders better, performing predictive modeling to lower opportunities for fraud before it happens, are just a few examples of the advantages afforded through data-based tools that insurers can leverage. The advanced reasoning that data-based tools enable will help insurers not only reduce manual errors in processing, increase efficiency and speed in claims investigations, and create better capacity in underwriting. In the end, using data-based analytics is more than a way to mitigate loss; it is an opportunity to enhance efficiency, improve the decision-making process across the insurance value chain.

For example, in September 2024, Sapiens International Corporation entered a partnership with Addresscloud to enhance geographic risk assessment capabilities for insurers. This collaboration integrates Addresscloud's precise geocoding and property data services with Sapiens' software solutions, aiming to improve the accuracy of underwriting decisions and streamline claims management processes. The partnership is designed to equip insurers with more reliable risk insights, ultimately providing them with a competitive edge in the market.

Risk Management Analytics Holds the Largest Global Insurance Analytics Market Share

Risk management analytics in the insurance industry has emerged as a key enabler of change in the way organizations evaluate, manage, and respond to risk. In an extremely complicated and data-driven environment, the insurance market can be getting more discerning in terms of the opportunities and risks it accepts. The industry has traditionally relied on actuarial models and historical data to stack rank threats, but now the insurance sector has started to capitalize on technology, particularly Artificial Intelligence (AI), Machine Learning (ML), and predictive analytics, in their risk evaluations. This allows an organization to spot risks it may not have known about, as well as provide an opportunity to create proactive action plans, and to also ultimately make quicker decisions that are more informed. The increase in risk management analytics also gives the insurer an edge in the global market that is evolving at light speed. There is a great level of enthusiasm with organizations taking on digital transformation, including a large insurer in Canada developing their digital products and services business unit, of which risk management analytics is going to play a role. The increase of risk management analytics represents a major shift in how the insurance industry can become smarter and more data-driven around the globe.

For example, in October 2024, LexisNexis introduced Life Smart Path, a new analytics solution for U.S. life insurers. Purpose-built to support early-stage underwriting, Life Smart Path uses real-time data to provide insights into risk and accelerate decision-making. By covering risk more accurately at the point of policy issuance, LexisNexis demonstrates how advanced analytics can enhance risk management capabilities in the insurance industry.

North America Dominates the Global Insurance Analytics Market Size

North America has the largest market share of the global insurance analytics market due to its early adoption and significant use of advanced analytics, a wealth of advanced technologies, an established insurance ecosystem, and supportive regulations. North American insurers have invested heavily in AI/ML-driven underwriting, risk modeling, fraud detection, and claims optimization tools for their processors. Many of the analytics vendors are solidifying the participant's role as the analytical leader in the insurance industry. Also, North America uses the NAIC and state regulations surrounding privacy and compliance as a precondition to using analytics to optimize and better manage risk but will often use analytics as a foundation to raise the level of trust and cut through competition.

For example, in June 2025, SAS Institute Inc. announced the integration of Azure Confidential Computing (in collaboration with Microsoft and AMD) into its SAS Viya platform. This initiative empowers insurance companies to perform advanced risk modeling, underwriting analytics, and fraud detection on fully encrypted data, even while its being processed in cloud memory. The solution uses AMD's SEV-SNP technology to ensure sensitive customer and risk data remains protected during active computation.

Key Players Landscape and Outlook

The global insurance analytics market is characterized by the presence of several key players that are leveraging advanced technologies to transform how insurers manage risk, streamline operations, and enhance customer experience. Companies are actively innovating and providing comprehensive, analytics-driven platforms that use both traditional and advanced technology tools that mitigate the threat of becoming obsolete using unviable channels. Specifically, they are implementing tools and technology to identify risk blessings, battling fraud, underwriting specimens, automating investigations, developing other tools to help their partners assess risk, and preserving their membership channels fully via cloud channels to leverage their presence in the summer. With insurance positivity at an all-time high, even so, the platform market outlook is better than promised, as forever improved. The global statutory systems are remarkably inconsistent, indicating that the market is most definitely still moving towards adopting cloud insurance platforms. The regulatory obligation with insurance fuels demand, as is InsurTech's forward thinking and the consumer's demands for life and more personalized and time-sensitive benefits. The persistent gap between the Americas ' cross-section and far relative sector commentary forecasts and leads all digitization in momentum, the APAC region is displaying very high growth potential, and the global entities appear to be challenging for market share through innovation, finding valuable or high-return partners and regional planning.

For example, in September 2024, Guardian Life Insurance, a leading U.S.-based insurer, implemented Oracle Fusion Cloud ERP (Oracle Corporation) to streamline its financial and operational workflows. By leveraging Oracle's embedded AI capabilities, the company significantly enhanced productivity and gained actionable insights, demonstrating the growing trend of insurers using advanced analytics tools to drive digital transformation and improve performance.

Table of Contents

1. Project Scope and Definitions

2. Research Methodology

3. Executive Summary

4. Voice of Customers

• 4.1. Respondent Demographics
• 4.2. Awareness of Insurance Analytics Tools
• 4.3. Key Challenges in Insurance Data Analysis
• 4.4. Preferred Vendors and Selection Criteria
• 4.5. Data Security and Compliance Concerns

5. Global Insurance Analytics Market Outlook, 2018-2032F

• 5.1. Market Size Analysis & Forecast
  • 5.1.1. By Value
• 5.2. Market Share Analysis & Forecast
  • 5.2.1. By Component
    • 5.2.1.1. Software
    • 5.2.1.2. Services
  • 5.2.2. By Deployment Mode
    • 5.2.2.1. On-premises
    • 5.2.2.2. Cloud
  • 5.2.3. By Application
    • 5.2.3.1. Claims Management
    • 5.2.3.2. Risk Management
    • 5.2.3.3. Customer Management and Personalization
    • 5.2.3.4. Fraud Detection
    • 5.2.3.5. Others
  • 5.2.4. By End-user
    • 5.2.4.1. Insurance Companies
    • 5.2.4.2. Third-party Administrators
    • 5.2.4.3. Brokers and Agencies
    • 5.2.4.4. Others
  • 5.2.5. By Country share
    • 5.2.5.1. North America
    • 5.2.5.2. Europe
    • 5.2.5.3. Asia-Pacific
    • 5.2.5.4. South America
    • 5.2.5.5. Middle East and Africa
• 5.3. Market Map Analysis, 2024
  • 5.3.1. By Component
  • 5.3.2. By Deployment Mode
  • 5.3.3. By Application
  • 5.3.4. By End-user
  • 5.3.5. By Country share

6. North America Insurance Analytics Market Outlook, 2018-2032F

• 6.1. Market Size Analysis & Forecast
  • 6.1.1. By Value
• 6.2. Market Share Analysis & Forecast
  • 6.2.1. By Component
    • 6.2.1.1. Software
    • 6.2.1.2. Services
  • 6.2.2. By Deployment Mode
    • 6.2.2.1. On-premises
    • 6.2.2.2. Cloud
  • 6.2.3. By Application
    • 6.2.3.1. Claims Management
    • 6.2.3.2. Risk Management
    • 6.2.3.3. Customer Management and Personalization
    • 6.2.3.4. Fraud Detection
    • 6.2.3.5. Others
  • 6.2.4. By End-user
    • 6.2.4.1. Insurance Companies
    • 6.2.4.2. Third-party Administrators
    • 6.2.4.3. Brokers and Agencies
    • 6.2.4.4. Others
  • 6.2.5. By Country Share
    • 6.2.5.1. United States
    • 6.2.5.2. Canada
    • 6.2.5.3. Mexico
• 6.3. Country Market Assessment
  • 6.3.1. United States Insurance Analytics Market Outlook, 2018-2032F*
    • 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 Component
        • 6.3.1.2.1.1. Software
        • 6.3.1.2.1.2. Services
      • 6.3.1.2.2. By Deployment Mode
        • 6.3.1.2.2.1. On-premises
        • 6.3.1.2.2.2. Cloud
      • 6.3.1.2.3. By Application
        • 6.3.1.2.3.1. Claims Management
        • 6.3.1.2.3.2. Risk Management
        • 6.3.1.2.3.3. Customer Management and Personalization
        • 6.3.1.2.3.4. Fraud Detection
        • 6.3.1.2.3.5. Others
      • 6.3.1.2.4. By End-user
        • 6.3.1.2.4.1. Insurance Companies
        • 6.3.1.2.4.2. Third-party Administrators
        • 6.3.1.2.4.3. Brokers and Agencies
        • 6.3.1.2.4.4. Others
  • 6.3.2. Canada
  • 6.3.3. Mexico

All segments will be provided for all regions and countries covered

7. Europe Insurance Analytics Market Outlook, 2018-2032F

• 7.1. Germany
• 7.2. France
• 7.3. Italy
• 7.4. United Kingdom
• 7.5. Russia
• 7.6. Netherlands
• 7.7. Spain
• 7.8. Turkey
• 7.9. Poland

8. Asia-Pacific Insurance Analytics Market Outlook, 2018-2032F

• 8.1. India
• 8.2. China
• 8.3. Japan
• 8.4. Australia
• 8.5. Vietnam
• 8.6. South Korea
• 8.7. Indonesia
• 8.8. Philippines

9. South America Insurance Analytics Market Outlook, 2018-2032F

• 9.1. Brazil
• 9.2. Argentina

10. Middle East and Africa Insurance Analytics Market Outlook, 2018-2032F

• 10.1. Saudi Arabia
• 10.2. UAE
• 10.3. South Africa

11. Demand Supply Analysis

12. Value Chain Analysis

13. Porter's Five Forces Analysis

14. PESTLE Analysis

15. Market Dynamics

• 15.1. Market Drivers
• 15.2. Market Challenges

16. Market Trends and Developments

17. Subscription Models (Usage-Based vs Fixed)

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. SAS Institute 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. Salesforce, Inc.
  • 19.3.3. International Business Machines Corporation (IBM)
  • 19.3.4. Oracle Corporation
  • 19.3.5. Guidewire Software, Inc.
  • 19.3.6. Microsoft Corporation
  • 19.3.7. Verisk Analytics, Inc.
  • 19.3.8. Tableau Software, LLC
  • 19.3.9. OpenText Corporation
  • 19.3.10. Palantir Technologies Inc.

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