Big Data in the Insurance Industry: Opportunities, Challenges, Strategies & Forecasts 2018 - 2030
“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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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.
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
Market forecasts are provided for each of the following submarkets and their subcategories:
Hardware, Software & Professional Services
Storage & Compute Infrastructure
Hadoop & Infrastructure Software
Analytic Platforms & Applications
Property & Casualty Insurance
Other Forms of Insurance
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
Latin & Central America
Middle East & Africa
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?
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
AMD (Advanced Micro Devices)
ASF (Apache Software Foundation)
AWS (Amazon Web Services)
BCG (Boston Consulting Group)
Booz Allen Hamilton
China Life Insurance Company
CSA (Cloud Security Alliance)
CSCC (Cloud Standards Customer Council)
Dai-ichi Life Holdings
DDN (DataDirect Networks)
Digital Reasoning Systems
DMG (Data Mining Group)
Dolphin Enterprise Solutions Corporation
Domino Data Lab
Dundas Data Visualization
Engineering Group (Engineering Ingegneria Informatica)
EV? (Big Cloud Analytics)
EXL (ExlService Holdings)
FICO (Fair Isaac Corporation)
GE (General Electric)
Hanse Orga Group
HPE (Hewlett Packard Enterprise)
IEC (International Electrotechnical Commission)
IEEE (Institute of Electrical and Electronics Engineers)
INCITS (InterNational Committee for Information Technology Standards)
InetSoft Technology Corporation
ISO (International Organization for Standardization)
ITU (International Telecommunication Union)
Kenko-Nenrei Shogaku Tanki Hoken
Looker Data Sciences
Manthan Software Services
MEAG (Munich Ergo Asset Management)
Neo First Life Insurance Company
NTT Data Corporation
OASIS (Organization for the Advancement of Structured Information Standards)
ODaF (Open Data Foundation)
ODCA (Open Data Center Alliance)
ODPi (Open Ecosystem of Big Data)
OGC (Open Geospatial Consortium)
Progress Software Corporation
PwC (PricewaterhouseCoopers International)
Salient Management Company
Samsung Fire & Marine Insurance
Strategy Companion Corporation
Supermicro (Super Micro Computer)
TCS (Tata Consultancy Services)
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TPC (Transaction Processing Performance Council)
U.S. NIST (National Institute of Standards and Technology)
W3C (World Wide Web Consortium)
Western Digital Corporation
Zurich Insurance Group
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