Big Data Emerged in the Insurance Industry with Challenging Opportunities,Trends and Forecasts to 2030 | Radiant Insights,Inc

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Scope of the term Big Data has significantly expanded over the years, It is a set of technologies that capture, store, manage and analyze large and variable collections of data, to solve complex problems.

“Big Data” originally emerged as a term to describe datasets whose size is beyond the ability of traditional databases to capture, store, manage and analyze. However, the scope of the term has significantly expanded over the years. Big Data not only refers to the data itself but also a set of technologies that capture, store, manage and analyze large and variable collections of data, to solve complex problems.

Amid the proliferation of real-time and historical data from sources such as connected devices, web, social media, sensors, log files and transactional applications, Big Data is rapidly gaining traction from a diverse range of vertical sectors. The insurance industry is no exception to this trend, where Big Data has found a host of applications ranging from targeted marketing and personalized products to usage-based insurance, efficient claims processing, proactive fraud detection and beyond.

SNS Telecom & IT estimates that Big Data investments in the insurance industry will account for more than $2.4 Billion in 2018 alone. Led by a plethora of business opportunities for insurers, reinsurers, insurance brokers, InsurTech specialists and other stakeholders, these investments are further expected to grow at a CAGR of approximately 14% over the next three years.

The “Big Data in the Insurance Industry: 2018 – 2030 – Opportunities, Challenges, Strategies & Forecasts” report presents an in-depth assessment of Big Data in the insurance industry including key market drivers, challenges, investment potential, application areas, use cases, future roadmap, value chain, case studies, vendor profiles and strategies. The report also presents market size forecasts for Big Data hardware, software and professional services investments from 2018 through to 2030. The forecasts are segmented for 8 horizontal submarkets, 8 application areas, 9 use cases, 6 regions and 35 countries.

The report comes with an associated Excel datasheet suite covering quantitative data from all numeric forecasts presented in the report.

Topics Covered
The report covers the following topics:
– Big Data ecosystem
– Market drivers and barriers
– Enabling technologies, standardization and regulatory initiatives
– Big Data analytics and implementation models
– Business case, application areas and use cases in the insurance industry
– 20 case studies of Big Data investments by insurers, reinsurers, InsurTech specialists and other stakeholders in the insurance industry
– Future roadmap and value chain
– Profiles and strategies of over 270 leading and emerging Big Data ecosystem players
– Strategic recommendations for Big Data vendors and insurance industry stakeholders
– Market analysis and forecasts from 2018 till 2030

Forecast Segmentation
Market forecasts are provided for each of the following submarkets and their subcategories:

Hardware, Software & Professional Services
– Hardware
– Software
– Professional Services

Horizontal Submarkets
– Storage & Compute Infrastructure
– Networking Infrastructure
– Hadoop & Infrastructure Software
– SQL
– NoSQL
– Analytic Platforms & Applications
– Cloud Platforms
– Professional Services

Application Areas
– Auto Insurance
– Property & Casualty Insurance
– Life Insurance
– Health Insurance
– Multi-Line Insurance
– Other Forms of Insurance
– Reinsurance
– Insurance Broking

Use Cases
– Personalized & Targeted Marketing
– Customer Service & Experience
– Product Innovation & Development
– Risk Awareness & Control
– Policy Administration, Pricing & Underwriting
– Claims Processing & Management
– Fraud Detection & Prevention
– Usage & Analytics-Based Insurance
– Other Use Cases

Regional Markets
– Asia Pacific
– Eastern Europe
– Latin & Central America
– Middle East & Africa
– North America
– Western Europe

Country Markets
– Argentina, Australia, Brazil, Canada, China, Czech Republic, Denmark, Finland, France, Germany, India, Indonesia, Israel, Italy, Japan, Malaysia, Mexico, Netherlands, Norway, Pakistan, Philippines, Poland, Qatar, Russia, Saudi Arabia, Singapore, South Africa, South Korea, Spain, Sweden, Taiwan, Thailand, UAE, UK, USA

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Key Questions Answered
The report provides answers to the following key questions:
– How big is the Big Data opportunity in the insurance industry?
– How is the market evolving by segment and region?
– What will the market size be in 2021, and at what rate will it grow?
– What trends, challenges and barriers are influencing its growth?
– Who are the key Big Data software, hardware and services vendors, and what are their strategies?
– How much are insurers, reinsurers, InsurTech specialists and other stakeholders investing in Big Data?
– What opportunities exist for Big Data analytics in the insurance industry?
– Which countries, application areas and use cases will see the highest percentage of Big Data investments in the insurance industry?

Key Findings
The report has the following key findings:
– In 2018, Big Data vendors will pocket more than $2.4 Billion from hardware, software and professional services revenues in the insurance industry. These investments are further expected to grow at a CAGR of approximately 14% over the next three years, eventually accounting for nearly $3.6 Billion by the end of 2021.
– Through the use of Big Data technologies, insurers and other stakeholders are beginning to exploit their data assets in a number of innovative ways ranging from targeted marketing and personalized products to usage-based insurance, efficient claims processing, proactive fraud detection and beyond.
– The growing adoption of Big Data technologies has brought about an array of benefits for insurers and other stakeholders. Based on feedback from insurers worldwide, these include but are not limited to an increase in access to insurance services by more than 30%, a reduction in policy administration workload by up to 50%, prediction of large loss claims with an accuracy of nearly 80%, cost savings in claims processing and management by 40-70%, accelerated processing of non-emergency insurance claims by a staggering 90%; and improvements in fraud detection rates by as much as 60%.
– In addition, Big Data technologies are playing a pivotal role in facilitating the adoption of on-demand insurance models – particularly in auto, life and health insurance, as well as the insurance of new and underinsured risks such as cyber crime.

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