It's time for big business to embrace the public chain – as a coordination tool, rather than as a place to carry out large-scale financial transactions. The group has come up with a new way of using the public ethereum mainnet to connect firms' internal systems for resource planning. Generative adversarial networks (GANs) -- two-part AI models consisting of a generator that creates samples and a discriminator that attempts to differentiate between the generated samples and real-world samples -- have been applied to tasks ranging from video, artwork, and music synthesis to drug discovery and misleading media detection. They've also made their way into ecommerce, as Amazon revealed in a blog post this morning. Frontline healthcare employees -- nurses, call center agents, among others -- have one of the toughest jobs in America.
As AI, image quality and cloud-based services improve, the insurance industry is slowly moving closer to an era where many claims may soon be processed without any human touch at all. One area where fully automated claims could bring new efficiencies and benefits is in commercial auto insurance. In a market where losses and claims are high, improving operational efficiencies is one of the most viable ways to gain profitability. Experts say most of the technology is already here, and while it must be refined to be ready for widespread adoption, it could be a mainstream reality within the next few years. Commercial auto insurance has been a tough market for many carriers in recent years.
From product development, underwriting and claims, to customer service chatbots, risk assessments, and quotations, technology are being deployed across the sector to provide faster, more accurate services. What is intriguing, however, is that while some major insurance companies are investing aggressively in AI, many are moving slowly, unsure of how best to deploy these technologies. In a recent AI survey, it says only half of the insurance executives consider AI technologies to be'extremely' or'very important' to their company's success, lower than for any other industry, such as financial services, healthcare, and manufacturing. Looking ahead three years, only 36% felt AI would be very important, again lower than any other industry. This lack of awareness around the importance of AI is worrying as new entrants to the market start making an impression.
Intel makes processors that act as the main computing brains for PCs and servers. Nomura Instinet chip analyst David Wong initiated coverage on Intel on Tuesday with a Buy rating, predicting long-term sales growth of 8% to 10% annually for the technology giant. "Intel is the world leader in processors for artificial intelligence and autonomous driving," he wrote. "We think that microprocessor growth could well be above overall semiconductor industry growth over the next decade, fueling long-term top-line growth for Intel." The analyst started his price target for Intel at $65, representing 17% upside to the current stock price.
From automating the most menial and repetitive tasks to free up the time to focus on higher level objectives, to assisting with customer service management and reducing the risk of frauds, AI is employed from back-office tasks to the frontend with nimbleness and agility. According to the Alan Turing Institute, with $70 billion USD spent by banks on compliance each year just in the U.S., the amount of money spent on fraud is staggering. And when the number of reported cases of payments-related fraud has increased by 66% between 2015 and 2016 in the United Kingdom, it's clear how this problem is much more than a momentary phenomenon. AI is a groundbreaking technology in the battle against financial fraud. ML algorithms are able to analyze millions of data points in a matter of seconds to identify anomalous transactional patterns.
Applying artificial intelligence to everything we're comfortable doing in banking is much easier than changing how we do things -- which would make the greatest use of AI. Few in financial services would argue that the future belongs to those institutions that harness data-driven machine intelligence to do more, better and faster. The insights and efficiencies needed to compete and thrive will come from AI-driven service personalization and optimization. But AI should do more than speed up a financial assembly line. As Ernst & Young stated in a report: "AI-driven financial health systems will become personal financial operating systems. Consumer finance will unbundle products and rebundle personalized and holistic value propositions based on life events."
JP Morgan is backing the use of machine learning for the future of foreign exchange algorithmic trading, after applying the technology to its FX algos earlier this year. The investment bank launched Deep Neural Network for Algo Execution (DNA) as a tool to bolster its FX algorithms in April, using machine learning to bundle its existing algos into a single execution strategy. "DNA is an optimisation feature that leverages simulated data from various types of market conditions to select the best order placement and execution style designed to minimise market impact," said Chi Nzelu, head of macro eCommerce at JP Morgan. "It then uses reinforcement learning – a subset of machine learning – to assess the performance of individual order placement choices." JP Morgan added that in recent years, algo trading strategies such as time-weighted average price (TWAP) and volume-weighted average price (VWAP) have multiplied, forcing clients to choose from a suite of algos with various execution methods.
The digital revolution in true sense has taken the world by storm. Ever since its introduction, the service industry has shifted its focus completely towards offering personalized experiences to the customers. The travel insurance industry is also sailing in the same boat and has been using new-age technology to offer the best products and services to its customers. But if you go by the experts, artificial intelligence is the key to offering personalised travel insurance services in future. Artificial intelligence (AI) is a widely used digital tool in the insurance industry today.
ResoluteAI, the Connect to Discover company, announced the addition of a News dataset to their Foundation search platform for scientific content. In partnership with FinTech Studios, the leading AI-based intelligent search and analytics platform for Wall Street, the News database provides ResoluteAI's clients with a robust offering of timely scientific content. Foundation is a multi-source research hub that allows public scientific content to be searched as if it's single-source. ResoluteAI applies the most sophisticated artificial intelligence and machine learning to unstructured content. This AI-driven solution creates structured metadata and organizes it into datasets that include Companies, Patents, Grants, Clinical Trials, Technology Transfer, and Publications.