Big Data In The Insurance Market
IT & Telecom Software Technology

Future Growth of Big Data In The Insurance Market to Grow at a CAGR of +14% During and Forecasts, 2019 To 2025 Forecast Period: Key Vendors like Aetna, AFS Technologies, CACI International, Cambridge Semantics, HCL Technologies, Hitachi Vantara, IBM Corporation, Infosys

““Big Data” originally emerged as a term to describe datasets whose size is beyond the ability of traditional databases to capture, store, manage and analyse. 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 analyse large and variable collections of data, to solve complex problems.

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, insures specialists and other stakeholders, these investments are further expected to grow at a CAGR of approximately 14% over the next three years.

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The Top Key Players include: Aetna, AFS Technologies, Alation, Algorithmia, BackOffice Associates, Basho Technologies, BCG (Boston Consulting Group), Bedrock Data, BetterWorks, CACI International, Cambridge Semantics, Cape Analytics, Capgemini, Dataiku, Datalytyx, Datameer, HCL Technologies, Hedvig, Hitachi Vantara, IBM Corporation, iDashboards, IDERA, Informatica, Information Builders, Infosys, Infoworks, NTT Data Corporation among others.

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

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Global Big Data In The Insurance Market Key Segments:

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

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.

Table of Contents

Global Big Data In The Insurance Market Research Report

Chapter 1 Global Big Data In The Insurance Market Overview

Chapter 2 Global Economic Impact on Industry

Chapter 3 Global Market Competition by Manufacturers

Chapter 4 Global Production, Revenue (Value) by Region

Chapter 5 Global Supply (Production), Consumption, Export

Chapter 6 Production, Revenue (Value), Price Trend by Type

Chapter 7 Market Analysis by Application

Chapter 8 Manufacturing Cost Analysis

Chapter 9 Industrial Chain, Sourcing Strategy and Downstream Buyers

Chapter 10 Marketing Strategy Analysis, Distributors/Traders

Chapter 11 Market Effect Factors Analysis

Chapter 12 Market Forecast

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