시장보고서
상품코드
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보험 애널리틱스 시장 규모, 점유율, 성장률 및 세계 산업 분석 : 유형별, 용도별, 지역별 인사이트, 예측(2026-2034년)

Insurance Analytics Market Size, Share, Growth and Global Industry Analysis By Type & Application, Regional Insights and Forecast to 2026-2034

발행일: | 리서치사: Fortune Business Insights Pvt. Ltd. | 페이지 정보: 영문 160 Pages | 배송안내 : 문의

    
    
    



※ 본 상품은 영문 자료로 한글과 영문 목차에 불일치하는 내용이 있을 경우 영문을 우선합니다. 정확한 검토를 위해 영문 목차를 참고해주시기 바랍니다.

보험 애널리틱스 시장의 성장요인

세계의 보험 애널리틱스 시장은 2025년에 193억 달러로 평가되며, 2026년에는 223억 5,000만 달러에 달할 것으로 예측됩니다. 이후 2034년까지 545억 4,000만 달러로 성장하며, 예측 기간 중 13.90%의 CAGR을 나타낼 전망입니다. 북미는 2025년에 40.40%의 점유율로 시장을 선도하고 있으며, 이는 기술 발전, 분석 툴의 조기 도입, 보험사 전반의 디지털 솔루션에 대한 강력한 투자에 힘입은 것으로 분석됩니다.

보험 애널리틱스는 첨단 데이터 분석 및 모델링 기술을 활용하여 보험과 관련된 방대한 데이터로부터 실용적인 인사이트를 도출하는 것을 말합니다. 여기에는 보험계약자, 보험금 청구, 리스크 관리, 기타 업무에 관한 정보가 포함됩니다. 기업은 이러한 툴을 활용하여 의사결정 강화, 업무 효율성 최적화, 리스크 관리, 고객 이해도 향상을 위해 활용하고 있습니다. 보험업계의 경쟁 심화와 개인화된 실시간 서비스에 대한 수요와 맞물려 전 세계에서 분석 솔루션 도입이 가속화되고 있습니다.

COVID-19의 영향

COVID-19 팬데믹은 데이터베이스 인사이트에 대한 수요를 증가시킴으로써 보험 분석 시장에 큰 영향을 미쳤습니다. 보험사들은 팬데믹 관련 리스크 평가, 보험금 청구 동향 예측, 업무 최적화를 위해 애널리틱스에 의존하고 있습니다. 이번 위기는 보험사가 갑작스러운 도전에 적응하고, 회복력을 강화하며, 업계 전반의 혁신을 촉진하는 데 있으며, 애널리틱스의 중요성을 다시 한 번 일깨워주었습니다.

시장 동향

보험 분석 시장에서는 인공지능(AI)과 머신러닝(ML)이 광범위하게 통합되고 있습니다. 이러한 기술은 리스크 평가, 부정행위 감지, 인수 정확도 향상, 고객 서비스 개선에 기여합니다. 예를 들어 2022년 6월 SAS는 카마크라를 인수하여 금융 및 보험 기업이 전문적인 AI 및 분석 솔루션을 통해 효과적으로 리스크를 관리할 수 있도록 했습니다. AI를 통한 자동화는 보험금 청구 처리의 효율화, 관리 비용 절감, 고객 만족도 향상에도 기여하고 있습니다.

성장 요인

데이터베이스 의사결정에 대한 수요 증가가 시장 성장을 가속하고 있습니다. 보험사들은 업무 최적화를 위해 보험계약자의 행동, 보험금 청구 데이터, IoT가 만들어내는 인사이트, 외부 데이터세트을 분석하는 것의 가치를 점점 더 많이 인식하고 있습니다. 규제 준수, 리스크 관리, 업무 효율성 향상도 도입을 더욱 촉진하고 있습니다. 업계 전문가에 따르면 보험 전문가의 90%가 디지털 혁신에 분석이 필수적이라고 생각하고 있으며, 이는 데이터베이스 인사이트에 대한 의존도가 높아지고 있음을 보여줍니다.

제약 요인

성장 기회가 있는 반면, 시장은 한정된 자원과 데이터 분석 능력과 같은 문제에 직면해 있습니다. 방대한 데이터세트를 관리하고, GDPR(EU 개인정보보호규정)과 같은 규제를 준수하고, 실행 가능한 인사이트을 추출하기 위해서는 기술과 숙련된 인력에 대한 막대한 투자가 필요합니다. 이러한 요인으로 인해 특히 중소형 보험사의 도입 속도가 느려질 수 있습니다.

시장 세분화

도입 방식별:

  • 클라우드 기반 솔루션은 확장성, 실시간 처리, 인프라 비용 절감을 제공하며 2026년 68.14%의 점유율로 시장을 장악했습니다.
  • On-Premise형 솔루션은 제어성, 보안성, 커스터마이징이 가능하지만 초기 비용이 높기 때문에 성장이 더디게 진행되고 있습니다.

기업 규모별:

  • 대기업은 2026년 55.70%의 시장 점유율을 차지할 것으로 예상되며, 분석 기술을 활용하여 방대한 데이터세트를 처리하고, 인수 심사, 부정행위 감지, 보험금 청구 관리를 개선하기 위해 노력하고 있습니다.
  • 중소기업은 접근하기 쉽고 저렴한 솔루션으로 인해 빠르게 분석을 도입하고 있으며, 가장 높은 CAGR로 성장할 것으로 예측됩니다.

용도별:

  • 2026년 보험금 청구 프로세스 최적화는 자동화, 효율화, 사기 감소를 배경으로 29.71%로 가장 큰 시장 점유율을 차지할 것으로 예측됩니다.
  • 고객 참여 및 유지 부문은 보험사들이 개인화된 상품 제공과 적극적인 고객 서비스에 집중하면서 가장 빠른 성장이 예상됩니다.

최종사용자별:

  • 보험사는 리스크 관리, 가격 책정, 고객 서비스에서 분석에 대한 의존도가 높기 때문에 가장 큰 점유율(2026년 기준 39.15%)을 차지할 것으로 예측됩니다.
  • 정부 기관은 두 번째로 큰 부문으로, 업무 운영 및 공공 서비스 제공을 최적화하기 위해 분석 기술을 도입하고 있습니다.

지역별 인사이트

  • 북미: 2025년 67억 6,000만 달러로 평가되었고, 2026년에는 51억 9,000만 달러에 달할 것으로 예측됩니다. 강력한 기술 도입과 분석 솔루션에 대한 투자가 성장을 주도하고 있습니다.
  • 아시아태평양: 가장 빠르게 성장하는 지역으로, 디지털화와 정부 지원을 바탕으로 2026년에는 일본이 7억 8,000만 달러, 중국이 12억 7,000만 달러, 인도가 6억 9,000만 달러에 달할 것으로 예측됩니다.
  • 유럽: 영국과 독일 시장은 2026년까지 각각 12억 3,000만 달러, 11억 5,000만 달러에 달할 것으로 예상되며 꾸준한 성장이 예상됩니다. 이는 규제 준수와 업무 효율성이 주요 요인입니다.
  • 남미와 중동 및 아프리카: 도입 속도가 느리고, 이 지역에서는 분석 기능의 통합이 아직 개발 단계에 있습니다.

주요 기업

시장의 주요 기업은 IBM, Tableau Software, Wipro, LexisNexis Risk Solutions, Vertafore, SAS Institute, Verisk Analytics, ExlService Holdings, Altair Engineering, Moody's Analytics입니다. 이들 기업은 시장에서의 입지를 강화하기 위해 제품 혁신, 파트너십, 사업 확장에 집중하고 있습니다.

업계 주요 동향

  • 2024년 1월: 인슈리티가 손해보험을 위한 AI 기반 분석 솔루션 발표.
  • 2023년 8월: IBM과 FGH Parent는 자동화와 AI를 통해 생명보험 업무를 강화했습니다.
  • 2023년 6월: 아이파이프라인과 버터포어가 생명보험 유통을 효율화했습니다.
  • 2023년 4월: Verisk, 클라우드 기반 서비스형 평가(Rating-as-a-Service, RaaS) 및 부정행위 분석 솔루션 도입.
  • 2023년 3월: LexisNexis는 AI를 활용한 주택보험 분석 기능을 강화하여 인수 업무의 신속성을 높였습니다.

목차

제1장 서론

제2장 개요

제3장 시장 역학

제4장 경쟁 구도

제5장 세계의 보험 애널리틱스 시장 규모(추정치·예측치) : 부문별(2021-2034년)

제6장 북미의 보험 애널리틱스 시장의 분석 : 인사이트와 예측(2021-2034년)

제7장 남미의 보험 애널리틱스 시장의 분석 : 인사이트와 예측(2021-2034년)

제8장 유럽의 보험 애널리틱스 시장의 분석 : 인사이트와 예측(2021-2034년)

제9장 중동 및 아프리카의 보험 애널리틱스 시장의 분석 : 인사이트와 예측(2021-2034년)

제10장 아시아태평양의 보험 애널리틱스 시장의 분석 : 인사이트와 예측(2021-2034년)

제11장 주요 10사의 기업 개요

제12장 주요 포인트

KSA 26.04.03

Growth Factors of insurance analytics Market

The global insurance analytics market was valued at USD 19.3 billion in 2025 and is projected to reach USD 22.35 billion in 2026, eventually growing to USD 54.54 billion by 2034, exhibiting a CAGR of 13.90% during the forecast period. North America dominated the market in 2025 with a 40.40% share, driven by technological advancements, early adoption of analytics tools, and strong investment in digital solutions across insurance firms.

Insurance analytics refers to the use of advanced data analysis and modeling techniques to derive actionable insights from large volumes of insurance-related data. This includes information on policyholders, claims, risk management, and other operations. Companies are leveraging these tools to enhance decision-making, optimize operational efficiency, manage risks, and improve customer understanding. The increasing competition in the insurance sector, combined with demand for personalized and real-time services, has accelerated adoption of analytics solutions globally.

Impact of COVID-19

The COVID-19 pandemic significantly impacted the insurance analytics market by increasing the demand for data-driven insights. Insurers relied on analytics to assess pandemic-related risks, predict claims trends, and optimize operations. The crisis reinforced the importance of analytics in enabling insurers to adapt to sudden challenges, enhance resilience, and foster innovation across the sector.

Market Trends

The insurance analytics market is witnessing widespread integration of Artificial Intelligence (AI) and Machine Learning (ML). These technologies improve risk assessment, fraud detection, underwriting accuracy, and customer service. For instance, in June 2022, SAS acquired Kamakura Corporation, enabling financial and insurance firms to effectively manage risks using specialized AI and analytics solutions. Automation through AI is also streamlining claims processing, reducing administrative costs, and enhancing customer satisfaction.

Growth Factors

The surge in demand for data-driven decision-making is fueling market growth. Insurers increasingly recognize the value of analyzing policyholder behavior, claims data, IoT-generated insights, and external datasets to optimize operations. Regulatory compliance, risk management, and improving operational efficiency further drive adoption. Industry experts report that 90% of insurance professionals consider analytics critical for digital transformation, underlining the growing reliance on data-driven insights.

Restraints

Despite growth opportunities, the market faces challenges such as limited resources and data analytics capabilities. Managing massive datasets, adhering to regulations like GDPR, and extracting actionable insights demand substantial investments in technology and skilled personnel. These factors may slow the adoption rate, particularly among smaller insurers.

Market Segmentation

By Deployment:

  • Cloud-based solutions dominated the market with a 68.14% share in 2026, offering scalability, real-time processing, and reduced infrastructure costs.
  • On-premise solutions provide control, security, and customization but involve higher upfront costs, resulting in moderate growth.

By Enterprise Type:

  • Large enterprises accounted for 55.70% market share in 2026, leveraging analytics to handle vast datasets and improve underwriting, fraud detection, and claims management.
  • SMEs are adopting analytics rapidly due to accessible and affordable solutions, expected to grow at the highest CAGR.

By Application:

  • Claims process optimization held the largest market share of 29.71% in 2026, driven by automation, efficiency, and fraud reduction.
  • Customer engagement and retention is projected to grow fastest, as insurers focus on personalized offerings and proactive customer service.

By End-User:

  • Insurance firms held the largest share (39.15% in 2026) due to reliance on analytics for risk management, pricing, and customer service.
  • Government agencies are the second-largest segment, adopting analytics to optimize operations and public service delivery.

Regional Insights

  • North America: Valued at USD 6.76 billion in 2025, projected to reach USD 5.19 billion in 2026. Strong technological adoption and investment in analytics solutions drive growth.
  • Asia Pacific: Fastest-growing region, with Japan, China, and India projected at USD 0.78 billion, 1.27 billion, and 0.69 billion in 2026, fueled by digitalization and government support.
  • Europe: Steady growth, with UK and Germany markets reaching USD 1.23 billion and 1.15 billion by 2026, driven by regulatory compliance and operational efficiency.
  • South America and Middle East & Africa: Slower adoption, as analytics integration is still emerging in these regions.

Key Players

Leading companies in the market are IBM, Tableau Software, Wipro, LexisNexis Risk Solutions, Vertafore, SAS Institute, Verisk Analytics, ExlService Holdings, Altair Engineering, and Moody's Analytics. These players focus on product innovation, partnerships, and expansion to strengthen their market position.

Key Industry Developments

  • January 2024: Insurity launched AI-powered analytics solutions for property and casualty insurance.
  • August 2023: IBM and FGH Parent enhanced life insurance operations with automation and AI.
  • June 2023: iPipeline and Vertafore streamlined life insurance distribution.
  • April 2023: Verisk introduced cloud-based Rating-as-a-Service (RaaS) and fraud analytics solutions.
  • March 2023: LexisNexis upgraded AI-driven home insurance analytics for faster underwriting.

Conclusion

The insurance analytics market is projected to grow from USD 19.3 billion in 2025 to USD 54.54 billion by 2034, driven by AI and ML adoption, cloud deployment, automated claims processing, and data-driven decision-making. North America leads in market share, while Asia Pacific shows the fastest growth trajectory. As insurers and government agencies increasingly rely on analytics to manage risks, optimize operations, and enhance customer satisfaction, the insurance analytics market is poised for substantial growth in the coming decade.

Segmentation By Deployment

  • Cloud
  • On-premise

By Enterprise Type

  • Large Enterprises
  • Small and Medium Enterprises (SMEs)

By Application

  • Claims Process Optimization
  • Fraud Detection & Risk Assessment
  • Customer Engagement & Retention
  • Others (Data Visualization and others)

By End-user

  • Insurance Firms
  • Government Agencies
  • Others (Third-party Administrators, Brokers, and Consultants)

By Region

  • North America (By Deployment, By Enterprise Type, By Application, By End-user, and By Country)
    • U.S. (By End-user)
    • Canada (By End-user)
    • Mexico (By End-user)
  • South America (By Deployment, By Enterprise Type, By Application, By End-user, and By Country)
    • Brazil (By End-user)
    • Argentina (By End-user)
    • Rest of South America
  • Europe (By Deployment, By Enterprise Type, By Application, By End-user, and By Country)
    • U.K. (By End-user)
    • Germany (By End-user)
    • France (By End-user)
    • Italy (By End-user)
    • Spain (By End-user)
    • Russia (By End-user)
    • Benelux (By End-user)
    • Nordics (By End-user)
    • Rest of Europe
  • The Middle East & Africa (By Deployment, By Enterprise Type, By Application, By End-user, and By Country)
    • Turkey (By End-user)
    • Israel (By End-user)
    • GCC (By End-user)
    • North Africa (By End-user)
    • South Africa (By End-user)
    • Rest of Middle East & Africa
  • Asia Pacific (By Deployment, By Enterprise Type, By Application, By End-user, and By Country)
    • China (By End-user)
    • Japan (By End-user)
    • India (By End-user)
    • South Korea (By End-user)
    • ASEAN (By End-user)
    • Oceania (By End-user)
    • Rest of Asia Pacific

Table of Content

1. Introduction

  • 1.1. Definition, By Segment
  • 1.2. Research Methodology/Approach
  • 1.3. Data Sources

2. Executive Summary

3. Market Dynamics

  • 3.1. Macro and Micro Economic Indicators
  • 3.2. Drivers, Restraints, Opportunities and Trends

4. Competition Landscape

  • 4.1. Business Strategies Adopted by Key Players
  • 4.2. Consolidated SWOT Analysis of Key Players
  • 4.3. Global Insurance Analytics Key Players Market Share/Ranking, 2025

5. Global Insurance Analytics Market Size Estimates and Forecasts, By Segments, 2021-2034

  • 5.1. Key Findings
  • 5.2. By Deployment (USD)
    • 5.2.1. Cloud
    • 5.2.2. On-premise
  • 5.3. By Enterprise Type (USD)
    • 5.3.1. Large Enterprises
    • 5.3.2. Small and Medium Enterprises (SMEs)
  • 5.4. By Application (USD)
    • 5.4.1. Claims Process Optimization
    • 5.4.2. Fraud Detection & Risk Assessment
    • 5.4.3. Customer Engagement & Retention
    • 5.4.4. Others (Data Visualization, etc.)
  • 5.5. By End-user (USD)
    • 5.5.1. Insurance Firms
    • 5.5.2. Government Agencies
    • 5.5.3. Others (Third-party Administrators, Brokers, and Consultants)
  • 5.6. By Region (USD)
    • 5.6.1. North America
    • 5.6.2. South America
    • 5.6.3. Europe
    • 5.6.4. Middle East & Africa
    • 5.6.5. Asia Pacific

6. North America Insurance Analytics Market Size Estimates and Forecasts, By Segments, 2021-2034

  • 6.1. Key Findings
  • 6.2. By Deployment (USD)
    • 6.2.1. Cloud
    • 6.2.2. On-premise
  • 6.3. By Enterprise Type (USD)
    • 6.3.1. Large Enterprises
    • 6.3.2. Small and Medium Enterprises (SMEs)
  • 6.4. By Application (USD)
    • 6.4.1. Claims Process Optimization
    • 6.4.2. Fraud Detection & Risk Assessment
    • 6.4.3. Customer Engagement & Retention
    • 6.4.4. Others (Data Visualization, etc.)
  • 6.5. By End-user (USD)
    • 6.5.1. Insurance Firms
    • 6.5.2. Government Agencies
    • 6.5.3. Others (Third-party Administrators, Brokers, and Consultants)
  • 6.6. By Country (USD)
    • 6.6.1. United States
      • 6.6.1.1. End-user
    • 6.6.2. Canada
      • 6.6.2.1. End-user
    • 6.6.3. Mexico
      • 6.6.3.1. End-user

7. South America Insurance Analytics Market Size Estimates and Forecasts, By Segments, 2021-2034

  • 7.1. Key Findings
  • 7.2. By Deployment (USD)
    • 7.2.1. Cloud
    • 7.2.2. On-premise
  • 7.3. By Enterprise Type (USD)
    • 7.3.1. Large Enterprises
    • 7.3.2. Small and Medium Enterprises (SMEs)
  • 7.4. By Application (USD)
    • 7.4.1. Claims Process Optimization
    • 7.4.2. Fraud Detection & Risk Assessment
    • 7.4.3. Customer Engagement & Retention
    • 7.4.4. Others (Data Visualization, etc.)
  • 7.5. By End-user (USD)
    • 7.5.1. Insurance Firms
    • 7.5.2. Government Agencies
    • 7.5.3. Others (Third-party Administrators, Brokers, and Consultants)
  • 7.6. By Country (USD)
    • 7.6.1. Brazil
      • 7.6.1.1. End-user
    • 7.6.2. Argentina
      • 7.6.2.1. End-user
    • 7.6.3. Rest of South America

8. Europe Insurance Analytics Market Size Estimates and Forecasts, By Segments, 2021-2034

  • 8.1. Key Findings
  • 8.2. By Deployment (USD)
    • 8.2.1. Cloud
    • 8.2.2. On-premise
  • 8.3. By Enterprise Type (USD)
    • 8.3.1. Large Enterprises
    • 8.3.2. Small and Medium Enterprises (SMEs)
  • 8.4. By Application (USD)
    • 8.4.1. Claims Process Optimization
    • 8.4.2. Fraud Detection & Risk Assessment
    • 8.4.3. Customer Engagement & Retention
    • 8.4.4. Others (Data Visualization, etc.)
  • 8.5. By End-user (USD)
    • 8.5.1. Insurance Firms
    • 8.5.2. Government Agencies
    • 8.5.3. Others (Third-party Administrators, Brokers, and Consultants)
  • 8.6. By Country (USD)
    • 8.6.1. United Kingdom
      • 8.6.1.1. End-user
    • 8.6.2. Germany
      • 8.6.2.1. End-user
    • 8.6.3. France
      • 8.6.3.1. End-user
    • 8.6.4. Italy
      • 8.6.4.1. End-user
    • 8.6.5. Spain
      • 8.6.5.1. End-user
    • 8.6.6. Russia
      • 8.6.6.1. End-user
    • 8.6.7. Benelux
      • 8.6.7.1. End-user
    • 8.6.8. Nordics
      • 8.6.8.1. End-user
    • 8.6.9. Rest of Europe

9. Middle East & Africa Insurance Analytics Market Size Estimates and Forecasts, By Segments, 2021-2034

  • 9.1. Key Findings
  • 9.2. By Deployment (USD)
    • 9.2.1. Cloud
    • 9.2.2. On-premise
  • 9.3. By Enterprise Type (USD)
    • 9.3.1. Large Enterprises
    • 9.3.2. Small and Medium Enterprises (SMEs)
  • 9.4. By Application (USD)
    • 9.4.1. Claims Process Optimization
    • 9.4.2. Fraud Detection & Risk Assessment
    • 9.4.3. Customer Engagement & Retention
    • 9.4.4. Others (Data Visualization, etc.)
  • 9.5. By End-user (USD)
    • 9.5.1. Insurance Firms
    • 9.5.2. Government Agencies
    • 9.5.3. Others (Third-party Administrators, Brokers, and Consultants)
  • 9.6. By Country (USD)
    • 9.6.1. Turkey
      • 9.6.1.1. End-user
    • 9.6.2. Israel
      • 9.6.2.1. End-user
    • 9.6.3. GCC
      • 9.6.3.1. End-user
    • 9.6.4. North Africa
      • 9.6.4.1. End-user
    • 9.6.5. South Africa
      • 9.6.5.1. End-user
    • 9.6.6. Rest of MEA

10. Asia Pacific Insurance Analytics Market Size Estimates and Forecasts, By Segments, 2021-2034

  • 10.1. Key Findings
  • 10.2. By Deployment (USD)
    • 10.2.1. Cloud
    • 10.2.2. On-premise
  • 10.3. By Enterprise Type (USD)
    • 10.3.1. Large Enterprises
    • 10.3.2. Small and Medium Enterprises (SMEs)
  • 10.4. By Application (USD)
    • 10.4.1. Claims Process Optimization
    • 10.4.2. Fraud Detection & Risk Assessment
    • 10.4.3. Customer Engagement & Retention
    • 10.4.4. Others (Data Visualization, etc.)
  • 10.5. By End-user (USD)
    • 10.5.1. Insurance Firms
    • 10.5.2. Government Agencies
    • 10.5.3. Others (Third-party Administrators, Brokers, and Consultants)
  • 10.6. By Country (USD)
    • 10.6.1. China
      • 10.6.1.1. End-user
    • 10.6.2. India
      • 10.6.2.1. End-user
    • 10.6.3. Japan
      • 10.6.3.1. End-user
    • 10.6.4. South Korea
      • 10.6.4.1. End-user
    • 10.6.5. ASEAN
      • 10.6.5.1. End-user
    • 10.6.6. Oceania
      • 10.6.6.1. End-user
    • 10.6.7. Rest of Asia Pacific

11. Company Profiles for Top 10 Players (Based on data availability in public domain and/or on paid databases)

  • 11.1. IBM Corporation
    • 11.1.1. Overview
      • 11.1.1.1. Key Management
      • 11.1.1.2. Headquarters
      • 11.1.1.3. Offerings/Business Segments
    • 11.1.2. Key Details (Key details are consolidated data and not product/service specific)
      • 11.1.2.1. Employee Size
      • 11.1.2.2. Past and Current Revenue
      • 11.1.2.3. Geographical Share
      • 11.1.2.4. Business Segment Share
      • 11.1.2.5. Recent Developments
  • 11.2. Tableau Software, LLC
    • 11.2.1. Overview
      • 11.2.1.1. Key Management
      • 11.2.1.2. Headquarters
      • 11.2.1.3. Offerings/Business Segments
    • 11.2.2. Key Details (Key details are consolidated data and not product/service specific)
      • 11.2.2.1. Employee Size
      • 11.2.2.2. Past and Current Revenue
      • 11.2.2.3. Geographical Share
      • 11.2.2.4. Business Segment Share
      • 11.2.2.5. Recent Developments
  • 11.3. Wipro
    • 11.3.1. Overview
      • 11.3.1.1. Key Management
      • 11.3.1.2. Headquarters
      • 11.3.1.3. Offerings/Business Segments
    • 11.3.2. Key Details (Key details are consolidated data and not product/service specific)
      • 11.3.2.1. Employee Size
      • 11.3.2.2. Past and Current Revenue
      • 11.3.2.3. Geographical Share
      • 11.3.2.4. Business Segment Share
      • 11.3.2.5. Recent Developments
  • 11.4. LexisNexis Risk Solution
    • 11.4.1. Overview
      • 11.4.1.1. Key Management
      • 11.4.1.2. Headquarters
      • 11.4.1.3. Offerings/Business Segments
    • 11.4.2. Key Details (Key details are consolidated data and not product/service specific)
      • 11.4.2.1. Employee Size
      • 11.4.2.2. Past and Current Revenue
      • 11.4.2.3. Geographical Share
      • 11.4.2.4. Business Segment Share
      • 11.4.2.5. Recent Developments
  • 11.5. Vertafore, Inc.
    • 11.5.1. Overview
      • 11.5.1.1. Key Management
      • 11.5.1.2. Headquarters
      • 11.5.1.3. Offerings/Business Segments
    • 11.5.2. Key Details (Key details are consolidated data and not product/service specific)
      • 11.5.2.1. Employee Size
      • 11.5.2.2. Past and Current Revenue
      • 11.5.2.3. Geographical Share
      • 11.5.2.4. Business Segment Share
      • 11.5.2.5. Recent Developments
  • 11.6. SAS Institute Inc.
    • 11.6.1. Overview
      • 11.6.1.1. Key Management
      • 11.6.1.2. Headquarters
      • 11.6.1.3. Offerings/Business Segments
    • 11.6.2. Key Details (Key details are consolidated data and not product/service specific)
      • 11.6.2.1. Employee Size
      • 11.6.2.2. Past and Current Revenue
      • 11.6.2.3. Geographical Share
      • 11.6.2.4. Business Segment Share
      • 11.6.2.5. Recent Developments
  • 11.7. Verisk Analytics, Inc.
    • 11.7.1. Overview
      • 11.7.1.1. Key Management
      • 11.7.1.2. Headquarters
      • 11.7.1.3. Offerings/Business Segments
    • 11.7.2. Key Details (Key details are consolidated data and not product/service specific)
      • 11.7.2.1. Employee Size
      • 11.7.2.2. Past and Current Revenue
      • 11.7.2.3. Geographical Share
      • 11.7.2.4. Business Segment Share
      • 11.7.2.5. Recent Developments
  • 11.8. ExlService Holdings, Inc.
    • 11.8.1. Overview
      • 11.8.1.1. Key Management
      • 11.8.1.2. Headquarters
      • 11.8.1.3. Offerings/Business Segments
    • 11.8.2. Key Details (Key details are consolidated data and not product/service specific)
      • 11.8.2.1. Employee Size
      • 11.8.2.2. Past and Current Revenue
      • 11.8.2.3. Geographical Share
      • 11.8.2.4. Business Segment Share
      • 11.8.2.5. Recent Developments
  • 11.9. Altair Engineering Inc.
    • 11.9.1. Overview
      • 11.9.1.1. Key Management
      • 11.9.1.2. Headquarters
      • 11.9.1.3. Offerings/Business Segments
    • 11.9.2. Key Details (Key details are consolidated data and not product/service specific)
      • 11.9.2.1. Employee Size
      • 11.9.2.2. Past and Current Revenue
      • 11.9.2.3. Geographical Share
      • 11.9.2.4. Business Segment Share
      • 11.9.2.5. Recent Developments
  • 11.10. Moody's Analytics, Inc.
    • 11.10.1. Overview
      • 11.10.1.1. Key Management
      • 11.10.1.2. Headquarters
      • 11.10.1.3. Offerings/Business Segments
    • 11.10.2. Key Details (Key details are consolidated data and not product/service specific)
      • 11.10.2.1. Employee Size
      • 11.10.2.2. Past and Current Revenue
      • 11.10.2.3. Geographical Share
      • 11.10.2.4. Business Segment Share
      • 11.10.2.5. Recent Developments

12. Key Takeaways

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