Market Overview:
The global insurance big data analytics market is expected to grow at a CAGR of 16.5% during the forecast period from 2018 to 2030. The growth in this market can be attributed to the increasing demand for big data analytics services and software by insurers to improve their business operations. The application of big data analytics in pricing premiums, preventing and reducing fraud, gaining customer insights, and others are also contributing significantly to the growth of this market. North America is expected to lead the global insurance big data analytics market during the forecast period followed by Europe and Asia Pacific.
Product Definition:
Insurance big data analytics is the process of examining large data sets to identify patterns and trends that can be used to improve the accuracy of risk assessments and underwriting decisions. The use of big data analytics can help insurers more accurately price policies, identify high-risk customers, and prevent fraud.
Service:
Insurance big data analytics is the process that involves the use of advanced technology to extract insights from large volumes of information. The information that is being analyzed can be insurance claims, customer emails, social media interactions and so on. The main goal in using big data analytics in insurance industry is to understand consumer behavior and their needs to provide better services/products.
Software:
Software is any set of instructions, which can be used to solve a problem when followed correctly. It may include computer programs as well as specific tools or algorithms. The main function of software is to help people and businesses in their day-to-day activities by performing tasks more efficiently and effectively than the traditional methods.
Insurance companies use big data analytics software for collecting large volumes of data from multiple sources such as social media, blogs, newspapers etc.
Application Insights:
The pricing premiums segment accounted for the largest market share in 2017 and is expected to register a significant CAGR over the forecast period. The segment uses big data analytics to price risk appropriately and reduce underwriting losses. Insurers are using various techniques, such as claim prediction models based on historical claims data, social network analysis of claimants¢â‚¬â„¢ friends & family, online behavioral advertising campaigns to price risk appropriately.
Prevent frauds and gain customer insights segments are also expected to witness lucrative growth over the forecast period owing to increasing demand from organizations for managing risks associated with frauds or other criminal activities by identifying suspicious transactions or behavior patterns of customers that may lead them towards financial loss. Furthermore, several regulatory bodies have issued regulations regarding implementation of these solutions within organizations in order to prevent financial crimes such as identity theft or money laundering activities conducted by employees within organizationally secure environments which is further anticipated boost market growth across various regions during the forecast period.
Regional Analysis:
North America accounted for the largest share of over 40% in 2017. The growth is attributed to the presence of a large number of insurance companies that are using big data analytics to gain insights into their business operations and improve their competitive position. Moreover, technological advancements such as cloud computing, high-speed internet connectivity, and robust IT infrastructure have paved way for big data analytics in this region.
Asia Pacific is expected to witness significant growth over the forecast period owing to increasing government initiatives aimed at creating awareness about potential benefits associated with big data analytics among small & medium enterprises (SMEs). Furthermore, growing penetration of technology-driven smartphones has created a need for insurance SMEs across Asia Pacific to adopt advanced technologies such as big data analytics in order to offer value-added services/products thereby driving market demand across this region.
Growth Factors:
- Increasing demand for big data analytics services by insurance companies to improve their business performance.
- Emergence of new technologies and platforms that help in collecting, managing, and analyzing large amounts of data more effectively.
- Growing number of startups providing innovative big data analytics solutions for the insurance industry.
- Rising demand for cloud-based big data analytics solutions among insurers due to its scalability and cost-effectiveness.
- Increasing focus on customer retention and engagement through predictive analysis and other advanced analytical techniques
Scope Of The Report
Report Attributes
Report Details
Report Title
Insurance Big Data Analytics Market Research Report
By Type
Service, Software
By Application
Pricing Premiums, Prevent and Reduce Fraud, Gain Customer Insight, Others
By Companies
Deloitte, Verisk Analytics, IBM, SAP AG, LexisNexis, PwC, Guidewire, RSM, SAS, Pegasystems, Majesco, Tableau, OpenText, Oracle, TIBCO Software, ReSource Pro, BOARD International, Vertafore, Qlik
Regions Covered
North America, Europe, APAC, Latin America, MEA
Base Year
2021
Historical Year
2019 to 2020 (Data from 2010 can be provided as per availability)
Forecast Year
2030
Number of Pages
159
Number of Tables & Figures
112
Customization Available
Yes, the report can be customized as per your need.
Global Insurance Big Data Analytics Market Report Segments:
The global Insurance Big Data Analytics market is segmented on the basis of:
Types
Service, Software
The product segment provides information about the market share of each product and the respective CAGR during the forecast period. It lays out information about the product pricing parameters, trends, and profits that provides in-depth insights of the market. Furthermore, it discusses latest product developments & innovation in the market.
Applications
Pricing Premiums, Prevent and Reduce Fraud, Gain Customer Insight, Others
The application segment fragments various applications of the product and provides information on the market share and growth rate of each application segment. It discusses the potential future applications of the products and driving and restraining factors of each application segment.
Some of the companies that are profiled in this report are:
- Deloitte
- Verisk Analytics
- IBM
- SAP AG
- LexisNexis
- PwC
- Guidewire
- RSM
- SAS
- Pegasystems
- Majesco
- Tableau
- OpenText
- Oracle
- TIBCO Software
- ReSource Pro
- BOARD International
- Vertafore
- Qlik
Highlights of The Insurance Big Data Analytics Market Report:
- The market structure and projections for the coming years.
- Drivers, restraints, opportunities, and current trends of market.
- Historical data and forecast.
- Estimations for the forecast period 2030.
- Developments and trends in the market.
- By Type:
- Service
- Software
- By Application:
- Pricing Premiums
- Prevent and Reduce Fraud
- Gain Customer Insight
- Others
- Market scenario by region, sub-region, and country.
- Market share of the market players, company profiles, product specifications, SWOT analysis, and competitive landscape.
- Analysis regarding upstream raw materials, downstream demand, and current market dynamics.
- Government Policies, Macro & Micro economic factors are also included in the report.
We have studied the Insurance Big Data Analytics Market in 360 degrees via. both primary & secondary research methodologies. This helped us in building an understanding of the current market dynamics, supply-demand gap, pricing trends, product preferences, consumer patterns & so on. The findings were further validated through primary research with industry experts & opinion leaders across countries. The data is further compiled & validated through various market estimation & data validation methodologies. Further, we also have our in-house data forecasting model to predict market growth up to 2030.
Regional Analysis
- North America
- Europe
- Asia Pacific
- Middle East & Africa
- Latin America
Note: A country of choice can be added in the report at no extra cost. If more than one country needs to be added, the research quote will vary accordingly.
The geographical analysis part of the report provides information about the product sales in terms of volume and revenue in regions. It lays out potential opportunities for the new entrants, emerging players, and major players in the region. The regional analysis is done after considering the socio-economic factors and government regulations of the countries in the regions.
How you may use our products:
- Correctly Positioning New Products
- Market Entry Strategies
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- Consumer Insights
- Understanding Competition Scenario
- Product & Brand Management
- Channel & Customer Management
- Identifying Appropriate Advertising Appeals
8 Reasons to Buy This Report
- Includes a Chapter on the Impact of COVID-19 Pandemic On the Market
- Report Prepared After Conducting Interviews with Industry Experts & Top Designates of the Companies in the Market
- Implemented Robust Methodology to Prepare the Report
- Includes Graphs, Statistics, Flowcharts, and Infographics to Save Time
- Industry Growth Insights Provides 24/5 Assistance Regarding the Doubts in the Report
- Provides Information About the Top-winning Strategies Implemented by Industry Players.
- In-depth Insights On the Market Drivers, Restraints, Opportunities, and Threats
- Customization of the Report Available
Frequently Asked Questions?
Insurance big data analytics is the process of using big data to improve insurance operations. It can include things like detecting and preventing fraud, improving customer service, and predicting claims. Insurance companies use big data to understand their customers better and make more informed decisions about how to serve them.
Some of the major players in the insurance big data analytics market are Deloitte, Verisk Analytics, IBM, SAP AG, LexisNexis, PwC, Guidewire, RSM, SAS, Pegasystems, Majesco, Tableau, OpenText, Oracle, TIBCO Software, ReSource Pro, BOARD International, Vertafore, Qlik.
The insurance big data analytics market is expected to register a CAGR of 16.5%.
Chapter 1 Executive Summary
Chapter 2 Assumptions and Acronyms Used
Chapter 3 Research Methodology
Chapter 4 Insurance Big Data Analytics Market Overview
4.1 Introduction
4.1.1 Market Taxonomy
4.1.2 Market Definition
4.1.3 Macro-Economic Factors Impacting the Market Growth
4.2 Insurance Big Data Analytics Market Dynamics
4.2.1 Market Drivers
4.2.2 Market Restraints
4.2.3 Market Opportunity
4.3 Insurance Big Data Analytics Market - Supply Chain Analysis
4.3.1 List of Key Suppliers
4.3.2 List of Key Distributors
4.3.3 List of Key Consumers
4.4 Key Forces Shaping the Insurance Big Data Analytics Market
4.4.1 Bargaining Power of Suppliers
4.4.2 Bargaining Power of Buyers
4.4.3 Threat of Substitution
4.4.4 Threat of New Entrants
4.4.5 Competitive Rivalry
4.5 Global Insurance Big Data Analytics Market Size & Forecast, 2018-2028
4.5.1 Insurance Big Data Analytics Market Size and Y-o-Y Growth
4.5.2 Insurance Big Data Analytics Market Absolute $ Opportunity
Chapter 5 Global Insurance Big Data Analytics Market Analysis and Forecast by Type
5.1 Introduction
5.1.1 Key Market Trends & Growth Opportunities by Type
5.1.2 Basis Point Share (BPS) Analysis by Type
5.1.3 Absolute $ Opportunity Assessment by Type
5.2 Insurance Big Data Analytics Market Size Forecast by Type
5.2.1 Service
5.2.2 Software
5.3 Market Attractiveness Analysis by Type
Chapter 6 Global Insurance Big Data Analytics Market Analysis and Forecast by Applications
6.1 Introduction
6.1.1 Key Market Trends & Growth Opportunities by Applications
6.1.2 Basis Point Share (BPS) Analysis by Applications
6.1.3 Absolute $ Opportunity Assessment by Applications
6.2 Insurance Big Data Analytics Market Size Forecast by Applications
6.2.1 Pricing Premiums
6.2.2 Prevent and Reduce Fraud
6.2.3 Gain Customer Insight
6.2.4 Others
6.3 Market Attractiveness Analysis by Applications
Chapter 7 Global Insurance Big Data Analytics Market Analysis and Forecast by Region
7.1 Introduction
7.1.1 Key Market Trends & Growth Opportunities by Region
7.1.2 Basis Point Share (BPS) Analysis by Region
7.1.3 Absolute $ Opportunity Assessment by Region
7.2 Insurance Big Data Analytics Market Size Forecast by Region
7.2.1 North America
7.2.2 Europe
7.2.3 Asia Pacific
7.2.4 Latin America
7.2.5 Middle East & Africa (MEA)
7.3 Market Attractiveness Analysis by Region
Chapter 8 Coronavirus Disease (COVID-19) Impact
8.1 Introduction
8.2 Current & Future Impact Analysis
8.3 Economic Impact Analysis
8.4 Government Policies
8.5 Investment Scenario
Chapter 9 North America Insurance Big Data Analytics Analysis and Forecast
9.1 Introduction
9.2 North America Insurance Big Data Analytics Market Size Forecast by Country
9.2.1 U.S.
9.2.2 Canada
9.3 Basis Point Share (BPS) Analysis by Country
9.4 Absolute $ Opportunity Assessment by Country
9.5 Market Attractiveness Analysis by Country
9.6 North America Insurance Big Data Analytics Market Size Forecast by Type
9.6.1 Service
9.6.2 Software
9.7 Basis Point Share (BPS) Analysis by Type
9.8 Absolute $ Opportunity Assessment by Type
9.9 Market Attractiveness Analysis by Type
9.10 North America Insurance Big Data Analytics Market Size Forecast by Applications
9.10.1 Pricing Premiums
9.10.2 Prevent and Reduce Fraud
9.10.3 Gain Customer Insight
9.10.4 Others
9.11 Basis Point Share (BPS) Analysis by Applications
9.12 Absolute $ Opportunity Assessment by Applications
9.13 Market Attractiveness Analysis by Applications
Chapter 10 Europe Insurance Big Data Analytics Analysis and Forecast
10.1 Introduction
10.2 Europe Insurance Big Data Analytics Market Size Forecast by Country
10.2.1 Germany
10.2.2 France
10.2.3 Italy
10.2.4 U.K.
10.2.5 Spain
10.2.6 Russia
10.2.7 Rest of Europe
10.3 Basis Point Share (BPS) Analysis by Country
10.4 Absolute $ Opportunity Assessment by Country
10.5 Market Attractiveness Analysis by Country
10.6 Europe Insurance Big Data Analytics Market Size Forecast by Type
10.6.1 Service
10.6.2 Software
10.7 Basis Point Share (BPS) Analysis by Type
10.8 Absolute $ Opportunity Assessment by Type
10.9 Market Attractiveness Analysis by Type
10.10 Europe Insurance Big Data Analytics Market Size Forecast by Applications
10.10.1 Pricing Premiums
10.10.2 Prevent and Reduce Fraud
10.10.3 Gain Customer Insight
10.10.4 Others
10.11 Basis Point Share (BPS) Analysis by Applications
10.12 Absolute $ Opportunity Assessment by Applications
10.13 Market Attractiveness Analysis by Applications
Chapter 11 Asia Pacific Insurance Big Data Analytics Analysis and Forecast
11.1 Introduction
11.2 Asia Pacific Insurance Big Data Analytics Market Size Forecast by Country
11.2.1 China
11.2.2 Japan
11.2.3 South Korea
11.2.4 India
11.2.5 Australia
11.2.6 South East Asia (SEA)
11.2.7 Rest of Asia Pacific (APAC)
11.3 Basis Point Share (BPS) Analysis by Country
11.4 Absolute $ Opportunity Assessment by Country
11.5 Market Attractiveness Analysis by Country
11.6 Asia Pacific Insurance Big Data Analytics Market Size Forecast by Type
11.6.1 Service
11.6.2 Software
11.7 Basis Point Share (BPS) Analysis by Type
11.8 Absolute $ Opportunity Assessment by Type
11.9 Market Attractiveness Analysis by Type
11.10 Asia Pacific Insurance Big Data Analytics Market Size Forecast by Applications
11.10.1 Pricing Premiums
11.10.2 Prevent and Reduce Fraud
11.10.3 Gain Customer Insight
11.10.4 Others
11.11 Basis Point Share (BPS) Analysis by Applications
11.12 Absolute $ Opportunity Assessment by Applications
11.13 Market Attractiveness Analysis by Applications
Chapter 12 Latin America Insurance Big Data Analytics Analysis and Forecast
12.1 Introduction
12.2 Latin America Insurance Big Data Analytics Market Size Forecast by Country
12.2.1 Brazil
12.2.2 Mexico
12.2.3 Rest of Latin America (LATAM)
12.3 Basis Point Share (BPS) Analysis by Country
12.4 Absolute $ Opportunity Assessment by Country
12.5 Market Attractiveness Analysis by Country
12.6 Latin America Insurance Big Data Analytics Market Size Forecast by Type
12.6.1 Service
12.6.2 Software
12.7 Basis Point Share (BPS) Analysis by Type
12.8 Absolute $ Opportunity Assessment by Type
12.9 Market Attractiveness Analysis by Type
12.10 Latin America Insurance Big Data Analytics Market Size Forecast by Applications
12.10.1 Pricing Premiums
12.10.2 Prevent and Reduce Fraud
12.10.3 Gain Customer Insight
12.10.4 Others
12.11 Basis Point Share (BPS) Analysis by Applications
12.12 Absolute $ Opportunity Assessment by Applications
12.13 Market Attractiveness Analysis by Applications
Chapter 13 Middle East & Africa (MEA) Insurance Big Data Analytics Analysis and Forecast
13.1 Introduction
13.2 Middle East & Africa (MEA) Insurance Big Data Analytics Market Size Forecast by Country
13.2.1 Saudi Arabia
13.2.2 South Africa
13.2.3 UAE
13.2.4 Rest of Middle East & Africa (MEA)
13.3 Basis Point Share (BPS) Analysis by Country
13.4 Absolute $ Opportunity Assessment by Country
13.5 Market Attractiveness Analysis by Country
13.6 Middle East & Africa (MEA) Insurance Big Data Analytics Market Size Forecast by Type
13.6.1 Service
13.6.2 Software
13.7 Basis Point Share (BPS) Analysis by Type
13.8 Absolute $ Opportunity Assessment by Type
13.9 Market Attractiveness Analysis by Type
13.10 Middle East & Africa (MEA) Insurance Big Data Analytics Market Size Forecast by Applications
13.10.1 Pricing Premiums
13.10.2 Prevent and Reduce Fraud
13.10.3 Gain Customer Insight
13.10.4 Others
13.11 Basis Point Share (BPS) Analysis by Applications
13.12 Absolute $ Opportunity Assessment by Applications
13.13 Market Attractiveness Analysis by Applications
Chapter 14 Competition Landscape
14.1 Insurance Big Data Analytics Market: Competitive Dashboard
14.2 Global Insurance Big Data Analytics Market: Market Share Analysis, 2019
14.3 Company Profiles (Details – Overview, Financials, Developments, Strategy)
14.3.1 Deloitte
14.3.2 Verisk Analytics
14.3.3 IBM
14.3.4 SAP AG
14.3.5 LexisNexis
14.3.6 PwC
14.3.7 Guidewire
14.3.8 RSM
14.3.9 SAS
14.3.10 Pegasystems
14.3.11 Majesco
14.3.12 Tableau
14.3.13 OpenText
14.3.14 Oracle
14.3.15 TIBCO Software
14.3.16 ReSource Pro
14.3.17 BOARD International
14.3.18 Vertafore
14.3.19 Qlik
