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Artificial intelligence: Delivering on insurance industry expectations

#artificialintelligence

Artificial intelligence (AI), where machines can effectively mimic the cognitive function of the human mind, is the driving force behind machine and deep-learning technology. Simply put, AI is a set of digital tools that make machines smarter, allowing them to perform certain automated activities that would normally require human intelligence.


Future Vision & Direction of AI Part II: Scaling AI Whilst Preventing a Big Brother World & Solving The Curse of the Modern Data Scientist

#artificialintelligence

Venture Capitalists are hoping to find the next superstar tech unicorn, AI startup founders dreaming of creating the next unicorn, and corporates adopting AI need to consider their data growth strategy in order to be able to scale their AI-enabled services or products. The past decade has been one of explosive growth in digital data and AI capabilities across the digital media and e-commerce space. And it is no accident that the strongest AI capabilities reside in the Tech majors. The author argues that there will be no AI winter in the 2020s as there was in 1974 and 1987 as the internet (social media and e-commerce) are so dependent upon AI capabilities and so too with being the Metaverse, and the era of 5G enabled Edge Computing with the Internet of Things (IoT). Furthermore, the following infographics illustrate how many people globally use social media and hence how central these channels have become to the everyday lives of people. Likewise, the size of the e-commerce market is vast. Although the era of standalone 5G networks may enable a window of opportunity for a new wave of consumer-facing applications in the business to consumer (B2C) in relation to e-commerce and perhaps even new digital media platforms that may challenge the current incumbents, after all the arrival of 4G provided a window for the likes of Airbnb, Uber, and leading social media platforms such as Facebook, Instagram, etc. to scale.


Future Vision & Direction of AI Part II: Scaling AI Whilst Preventing a Big Brother World & Solving The Curse of the Modern Data Scientist

#artificialintelligence

Venture Capitalists are hoping to find the next superstar tech unicorn, AI startup founders dreaming of creating the next unicorn, and corporates adopting AI need to consider their data growth strategy in order to be able to scale their AI-enabled services or products. The past decade has been one of explosive growth in digital data and AI capabilities across the digital media and e-commerce space. And it is no accident that the strongest AI capabilities reside in the Tech majors. The author argues that there will be no AI winter in the 2020s as there was in 1974 and 1987 as the internet (social media and e-commerce) are so dependent upon AI capabilities and so too with being the Metaverse, and the era of 5G enabled Edge Computing with the Internet of Things (IoT). Furthermore, the following infographics illustrate how many people globally use social media and hence how central these channels have become to the everyday lives of people. Likewise, the size of the e-commerce market is vast. Although the era of standalone 5G networks may enable a window of opportunity for a new wave of consumer-facing applications in the business to consumer (B2C) in relation to e-commerce and perhaps even new digital media platforms that may challenge the current incumbents, after all the arrival of 4G provided a window for the likes of Airbnb, Uber, and leading social media platforms such as Facebook, Instagram, etc. to scale.


Moving on from AI/ML: the future of insurance distribution is embedded

#artificialintelligence

Speaking to Intelligent Insurer's Re/insurance Lounge, Angus McDonald, chief executive officer and co-founder of Cover Genius, explained why embedded insurance will be the next big thing in a crowded insurtech market. Cover Genius offers end-to-end embedded insurance using proprietary technology that can be plugged into a third party's digital platform, allowing it to sell products, services, or platforms with insurance coverage or warranty protection embedded in it. Embedded insurance can be seen as an alternative to getting insurance from carriers --but one that benefits the customers with seamless digital experience, automated quotes, policy issuance and claims settlement within their purchase funnel. For example, travel insurance offered as part of flight or hotel reservation process, or auto insurance coverage that tags along with car rental or car-sharing services.


Insurance AI company Lemonade acquires Metromile to boost automotive offering

ZDNet

Lemonade, the AI-powered insurance company, announced Monday that it's acquiring Metromile for the proprietary data and machine learning algorithms behind Metromile's personalized auto insurance offerings. Lemonade will acquire Metromile in an all-stock transaction that implies a fully diluted equity value of approximately $500 million, or just over $200 million net of cash. Founded in 2015, Lemonade primarily uses big data and AI to sell home and pet insurance. Metromile, founded in 2011, is on its third generation of machine learning models that leverage telematics data to predict risk. Lemonade launched its auto insurance product, Lemonade Car, just last week.


Machine learning: Practical applications for the insurance industry

#artificialintelligence

One specific area of advanced technology being used extensively across the insurance value chain is machine learning (ML), which is helping insurance companies save time and money by improving operational efficiencies in areas such as fraud detection, claims management, quoting, billing and customer service. But what exactly is ML? Machine learning is a subfield of artificial intelligence (AI). Its job is to analyze data so computers can learn from and use information in the identification of specific patterns -- all with minimal human intervention or having to program an entire system. As data continues to be produced, ML solutions adapt autonomously, learning from new information as well as from previous processes. An example would be an insurance chatbot or an online insurance quote.



Artificial intelligence in Finance

#artificialintelligence

Artificial intelligence has specified the world of banking and therefore the financial industry as a whole how to fulfill the stress of consumers who want smarter, more convenient, harmless ways to access, spend, save and invest their money. AI in finance is changing the way we relate to money. AI provides assistance to the financial industry to rationalize and optimize processes starting from credit decisions to measurable trading and financial risk management. A current study established 77% of consumers favored paying with a debit or MasterCard related to only 12% who favored cash. But easier payment options are not the only reason the supply of credit is vital to consumers.


Make Lemonade Out of Lemonade - Insurance Thought Leadership

#artificialintelligence

Lemonade's recent glitch sheds light on public fears about AI -- and about what must be done to keep AI innovation from slowing. Being a disruptor is hard. It requires taking disproportionate risks, pushing the status quo and -- more often than not -- hitting speed bumps. Recently, Lemonade hit a speed bump in their journey as a visible disruptor and innovator in the insurance industry. I am not privy to any details or knowledge about the case or what Lemonade is or isn't doing, but the Twitter event and public dialogue that built up to this moment brings forward some reflections and opportunities every carrier should pause to consider.


AI, machine learning may be key to further insurance digital transformation

#artificialintelligence

The pandemic has pushed IT departments to adapt quickly to various challenges. A new report, IT's Changing Mandate in an Age of Disruption, suggests that to continue with various digital transformations and increase adaptability for the future some IT improvements must be made. For the insurance industry, artificial intelligence and machine learning may be key, according to the report, which was conducted by the Economist Intelligence Unit, supported by Appian, an enterprise software company. The report includes information from two surveys, conducted in May and June of this year, and responses from 1,002 IT and senior business executives, who worked across six different sectors including financial services and insurance and were from nine countries. Forty-one percent of respondents from the insurance industry said expanding the use of AI and machine learning is the most impactful way that technology can help organizations respond to potential changes.