Big Data In The Insurance Market Expected to Grow with Top Player’s Like-Absolutdata, Accenture, Actian Corporation, Adaptive Insights, Adobe Systems, Advizor Solutions, Aegon

Market Highlights

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.

Market Overview

“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.

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Market Key Player’s

1010data, Absolutdata, Accenture, Actian Corporation, Adaptive Insights, Adobe Systems, Advizor Solutions, Aegon, AeroSpike, Aetna, AFS Technologies, Alation, Algorithmia, Allianz Group, Allstate Corporation, Alluxio, Alphabet

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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Market Segments

Horizontal Sub markets
• 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,MultiLine 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 & AnalyticsBased Insurance,Other Use Cases

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

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This release was published on openPR.