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AI enabled startups is set to transform Insurtech Market

Insurtech is the use of technology to save time as well as costs from the traditional insurance industry model.

HYDERABAD, TELANGANA, INDIA, August 30, 2018 / -- Insurtech is the use of technology to save time as well as costs from the traditional insurance industry model. Artificial Intelligence is used in insurtech companies for fraud detection, customizing policy, claim management, virtual assistants, telematics and many other functionalities. Robo-advisors and chatbots are good examples of automation in the Insurtech sector.

Huge investments are made in all Insurtech companies worldwide. For example, Policybazaar received funding of $200 million in May, 2018. The US is leading with 60% funding in Insurtech in the first quarter of 2018, while UK and Germany are holding second and third positions with 7% and 5% funding respectively. The top five Insurtech companies ZhongAn, Lemonade, Metromile, Bought By Many and Oscar are giving tough competition to each other by launching various AI integrated tools for insurance.

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ZhongAn, being the market leader grabbed total funding of $931 million. It is an internet based property and casualty insurer. It sells its products online along with handling claim. The company offers e-commerce, mobile payment, and financing guarantee for internet business and users. For example, one of its policies offers customers protection against a cracked mobile phone screen. By using AI based image recognition technology, it can detect whether a photograph shows a mobile phone screen that is in good condition or is already cracked. 97% of ZhongAn queries are resolved by chatbots only.

Lemonade, founded in New York in 2015 with the funding of $180million, offers insurance to homeowners and renters. Lemonade offers zero paper work and instant policy generation and policy claim by replacing brokers and bureaucracy with bots and machine learning.
Bought By Many (BBM), is a multi-award winning insurtech company using social media to disrupt insurance distribution. It uses Facebook and other social platforms to connect with people to look for insurance product needs, build affinity groups and then negotiate deals with insurers. In 2017, BBM launched its range of cat and dog insurance product.

Metromile is a pay-per-mile insurance company, founded in 2011 with funding of $295.5 million. Its pay-per-mile car insurance model, offers the price on the basis of how people use their car. With the help of AI enabled driving app, it can access instant vehicle diagnosis.
Oscar, a health insurance company was founded in 2013 with funding of $892.5million. With the help of AI technology, it designs health insurance plan and settles claim. The company offers plans to individuals, couples, and families living in parts of New York, New Jersey, California, and Texas who don’t receive health insurance from their employer.

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The insurance industry has always been dominated by national brands and old fashioned approach so the new developments are changing the work flow dramatically. As investment is high in adopting technology oriented infrastructure, some firms are still not embracing AI. Cultural barrier and fear of replacing human is another challenge in the adoption of AI. In order to stay ahead with competitors and to fulfil customer expectation, all insurance institutions will have to embrace AI enabled system in the coming years.
Few insurtech companies are already enjoying benefits of having AI enabled system because of simplified access for end users, stronger customer experience and cost optimization. The auto and health insurance industry have already started adopting AI in their policies. AI in the insurance industry sector is still in its emerging phase. It is predicted that the chatbot technology will make huge growth in the future. AI for fraud detection and predictive analysis will make wave by 2020.

Artificial Intelligence in Insurtech Market is segmented as indicated below:
1. Artificial Intelligence in Insurtech Market – By Deployment
1.1. Introduction
1.2. On Premises
1.3. On Cloud
1.4. Hybrid

2. Artificial Intelligence in Insurtech Market – By Machine Learning
2.1. Unsupervised
2.2. Supervised
2.3. Reinforced
2.4. Semi Supervised
2.5. Deep Learning
2.6. Others

3. Artificial Intelligence in Insurtech Market – By Usage
3.1. Introduction
3.2. Consumer
3.3. Business

4. Artificial Intelligence in Insurtech Market – By Type
4.1. Service
4.1.1. Claims
4.1.2. Customer care assistants
4.1.3. Others
4.2. Product
4.2.1. Health Insurance
4.2.2. Life Insurance
4.2.3. Motor Insurance
4.2.4. Home Insurance
4.2.5. Travel Insurance
4.2.6. Cyber safe Insurance
4.2.7. Commercial Insurance
4.2.8. Crop Insurance
4.2.9. Others

5. Artificial Intelligence in Insurtech Market – Solution
5.1. Chatbots and AI assistants
5.2. Driver performance monitoring and real time assessments (Telematics)
5.3. Analytics
5.4. Claim management
5.5. Fraud detection
5.6. Underwriting and loss prevention
5.7. Customization of policy

6. Artificial Intelligence in Insurtech Market – By End Users
6.1. Introduction
6.2. Agriculture
6.3. Automotive
6.4. Healthcare
6.5. Travel and Tourism
6.6. Information Technology
6.7. Residential
6.8. Corporate

7. Artificial Intelligence in Insurtech Market By Entropy
8. Artificial Intelligence in Insurtech Market By Geography

Companies Cited/Interviewed/Referenced
Next IT Corp
Cape Analytics Inc.
Amazon web services
Company 15+

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What can you expect from the report?
The Artificial Intelligence in Insurtech Market Report is Prepared with the Main Agenda to Cover the following 20 points:
1. Market Size by Product Categories
2. Market trends
3. Manufacturer Landscape
4. Distributor Landscape
5. Pricing Analysis
6. Top 10 End user Analysis
7. Product Benchmarking
8. Product Developments
9. Mergers & Acquisition Analysis
10. Patent Analysis
11. Demand Analysis ( By Revenue & Volume )
12. Country level Analysis (15+)
13. Competitor Analysis
14. Market Shares Analysis
15. Value Chain Analysis
16. Supply Chain Analysis
17. Strategic Analysis
18. Current & Future Market Landscape Analysis
19. Opportunity Analysis
20. Revenue and Volume Analysis

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