Artificial Intelligence in Insurance Market Global Analysis, Financial-Services, Technological-Advancements in AI, Size, Share, Trends, Segmentations, Business-Strategies, Development-Plans & Forecast-2025
Thousands of claims, customer queries and large amounts of diverse data make the insurance industry a natural use case for artificial intelligence and cognitive-technologies. “Artificial Intelligence in Insurance-Thematic Research” Latest Report added to Arcognizance.com Database Strategically Profile Key-Players and Analyze Plan and Strategies.
Manhattan, New York, United States – August 7, 2019 /MarketersMedia/ —
Machine learning is an artificial intelligence (AI) technology which allows machines to learn by using algorithms to interpret data from connected ‘things’ to predict outcomes and learn from successes and failures.
There are many other AI technologies – from image recognition to natural language processing, gesture control, context awareness and predictive APIs – but machine learning is where most of the investment community’s funding has flowed in recent years. It is also the technology most likely to allow machines to ultimately surpass the intelligence levels of humans.
Many companies, like Alphabet, have already become ‘AI-first’ companies, with machine learning at their core. At the same time, many ML techniques are getting commoditized by being open sourced and pre-packaged into developer toolkits that anyone can use.
This report focuses on Artificial Intelligence in Insurance.
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Scope
This report is part of our ecosystem of thematic investment research reports, supported by our “thematic engine”. About our Thematic Research Ecosystem –
– GlobalData has developed a unique thematic methodology for valuing technology, media and telecom companies based on their relative strength in the big investment themes that are impacting their industry. Whilst most investment research is underpinned by backwards looking company valuation models, GlobalData’s thematic methodology identifies which companies are best placed to succeed in a future filled with multiple disruptive threats. To do this, GlobalData tracks the performance of the top 600 technology, media and telecom stocks against the 50 most important themes driving their earnings, generating 30,000 thematic scores. The algorithms in GlobalData’s “thematic engine” help to clearly identify the winners and losers within the TMT sector. Our 600 TMT stocks are categorised into 18 sectors. Each sector scorecard has a thematic screen, a risk screen and a valuation screen. Our thematic research ecosystem has a three-tiered reporting structure: single theme, multi-theme and sector scorecard. This report is a Multi-Theme report, covering all stocks, all sectors and all themes, giving readers a strong sense of how everything fits together and how conflicting themes might interact with one another.
Reasons to buy
– Our thematic investment research product, supported by our thematic engine, is aimed at senior (C-Suite) executives in the corporate world as well as institutional investors.
– Corporations: Helps CEOs in all industries understand the disruptive threats to their competitive landscape
– Investors: Helps fund managers focus their time on the most interesting investment opportunities in global TMT.
– Our unique differentiator, compared to all our rival thematic research houses, is that our thematic engine has a proven track record of predicting winners and losers.
Browse entire Artificial Intelligence in Insurance Market report @ http://www.arcognizance.com/report/artificial-intelligence-in-insurance-thematic-research
Companies Mentioned
Alphabet
Amazon
Apple
Ayasdi
Ageas
AIG
Allstate
Aviva
AXA
Baidu
Blue Yonder
Cognex
Darktrace
DataFox
Descartes Labs
Facebook
Fukoku Mutual Life Insurance
GEICO
IBM
iFlytek
Ipsoft
Kensho
Lemonade
Liberty Mutual
LV=
Metromile
Mobvoi
Nvidia
Numenta
Palantir
Preferred Networks
Progressive
Quid
Salesforce
SAP
Sentient Technologies
Splunk
Swiss Re
Transamerica
USAA
Vicarious
XL Catlin
Zephyr Health
Zurich
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Table of Contents
PLAYERS 3
TRENDS 4
Technology trends 4
Macro-economic trends 6
Applications of AI in Retail 7
VALUE CHAIN 9
Ten categories of AI software 10
INDUSTRY ANALYSIS 19
The tech sector’s angle 19
M&A 25
Timeline 27
IMPACT OF AI ON RETAIL 29
Retail case studies 31
How AI vendors can sell into the retail sector 33
Recommendations for IT vendors 33
COMPANIES SECTION 34
Listed tech companies 34
Privately held tech companies 38
Retail companies 41
TECHNOLOGY BRIEFING 43
Definitions 43
History of machine learning 43
How does deep learning work? 43
APPENDIX: OUR “THEMATIC” RESEARCH METHODOLOGY 46
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