Big Data in the Insurance Industry 2019
Description:-
“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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researcher 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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Table Of Contents – Major Key Points
Chapter 1: Introduction
Executive Summary
Topics Covered
Forecast Segmentation
Key Questions Answered
Key Findings
Methodology
Target Audience
Companies & Organizations Mentioned
Chapter 2: An Overview of Big Data
What is Big Data?
Key Approaches to Big Data Processing
Hadoop
NoSQL
MPAD (Massively Parallel Analytic Databases)
In-Memory Processing
Stream Processing Technologies
Spark
Other Databases & Analytic Technologies
Key Characteristics of Big Data
Volume
Velocity
Variety
Value
Market Growth Drivers
Awareness of Benefits
Maturation of Big Data Platforms
Continued Investments by Web Giants, Governments & Enterprises
Growth of Data Volume, Velocity & Variety
Vendor Commitments & Partnerships
Technology Trends Lowering Entry Barriers
Market Barriers
Lack of Analytic Specialists
Uncertain Big Data Strategies
Organizational Resistance to Big Data Adoption
Technical Challenges: Scalability & Maintenance
Security & Privacy Concerns
Chapter 3: Big Data Analytics
What are Big Data Analytics?
The Importance of Analytics
Reactive vs. Proactive Analytics
Customer vs. Operational Analytics
Technology & Implementation Approaches
Grid Computing
In-Database Processing
In-Memory Analytics
Machine Learning & Data Mining
Predictive Analytics
NLP (Natural Language Processing)
Text Analytics
Visual Analytics
Graph Analytics
Social Media, IT & Telco Network Analytics
Continued……
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