Wednesday, 27 February 2019

Big Data in the Insurance Industry : Market is set to boom in coming future 2018 – 2030

ResearchMoz presents professional and in-depth study of "Big Data in the Insurance Industry: 2018 - 2030 - Opportunities, Challenges, Strategies & Forecasts".

“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.

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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

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.

List of Companies Mentioned

    1010data
    Absolutdata
    Accenture
    Actian Corporation
    Adaptive Insights
    Adobe Systems
    Advizor Solutions
    Aegon
    AeroSpike
    Aetna
    AFS Technologies
    Alation
    Algorithmia
    Allianz Group
    Allstate Corporation
    Alluxio
    Alphabet
    ALTEN
    Alteryx
    AMD (Advanced Micro Devices)
    Anaconda
    Apixio
    Arcadia Data
    Arimo
    Arity
    ARM
    ASF (Apache Software Foundation)
    Atidot
    AtScale
    Attivio
    Attunity
    Automated Insights
    AVORA
    AWS (Amazon Web Services)
    AXA
    Axiomatics
    Ayasdi
    BackOffice Associates
    Basho Technologies
    BCG (Boston Consulting Group)
    Bedrock Data
    BetterWorks
    Big Panda
    BigML
    Birst
    Bitam
    Blue Medora
    BlueData Software
    BlueTalon
    BMC Software

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    BOARD International
    Booz Allen Hamilton
    Boxever
    CACI International
    Cambridge Semantics
    Cape Analytics
    Capgemini
    Cazena
    Centrifuge Systems
    CenturyLink
    Chartio
    China Life Insurance Company
    Cigna
    Cisco Systems
    Civis Analytics
    ClearStory Data
    Cloudability

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