Deloitte Global's latest report, Artificial Intelligence--The next frontier for investment management firms, focuses on four pillars for transformation which can empower firms to develop new propositions, and deliver new kinds of value. The report suggests that when these four pillars are augmented with AI, investment management firms can rapidly transform business models, operations, and internal capabilities. However, to fully benefit from AI, firms will need to carefully consider and manage the intersection between technology and talent. Read this report to see how you can unlock the full potential of artificial intelligence for your business.
The impressive promise that smart contracts hold for the future of business will only grow more impressive in the near-future as blockchain services that make such clever agreements possible in the first place become more advanced. Businesses will rely on smart contracts for a wide number of reasons, but nowhere will they be more important than when it comes to negotiating complex agreements with other businesses. These companies will cut the costs of working together by removing third parties from the equation, as smart contracts will be able to manage and adjust themselves with minimal to no human oversight.
Two new artificial intelligence ETFs launched on the New York Stock Exchange on Tuesday via a partnership between Exchange Traded Concepts and Qraft Technologies. The pair of ETFs are the Qraft AI Enhanced U.S. Large-Cap ETF (NYSEArca: QRFT) and the Qraft AI Enhanced U.S. Large Cap Momentum ETF (NYSEArca: AMOM). Hyung-Sik Kim, CEO and co-founder of Qraft Technologies, said they have been working together with ETC to improve the performance of traditional quantitative investment strategies by applying AI technologies. "As our system is ready to compete in the heart of the global financial market, we feel happy but also feel a sense of responsibility for proving AI's capabilities in the financial market," Kim said. "In the future, we expect AI-enhanced products have the potential to become substitutes for broad market indices if we prove it with our technologies. I would like to thank everyone at Qraft and ETC for their hard work."
Stamford, CT, May 20, 2019 (GLOBE NEWSWIRE) -- Imperative Execution, Inc. – the financial technology company that created IntelligentCross, an AI-powered alternative trading system built to reduce implicit trading costs – today announced performance results for its first eight months of operations. The venue has matched more than 1.5 billion shares since its launch with an observed price impact following these trades of 0.13bp, which is nearly ten times less than the 1.37bp average following comparable execution on U.S. securities exchanges. At the current rate of U.S. equities daily turnover, savings of that magnitude could save investors $10B per year. IntelligentCross is the industry's first smart venue to use artificial intelligence to optimize order matching to help investment managers and brokers reduce trading costs and improve execution quality on behalf of their clients. Its design was borne out of its founders' years trading on the buy-side, where traders are obsessed with implementation shortfall (IS) costs – in other words, the difference, or "slippage," between the arrival price and the execution price for completing a trade.
We have come to the fifth month of the year, and technology especially the disruptive one that includes Artificial Intelligence (AI) is gaining strong-hold more than ever. Understanding its disruptive factors is important as it enables more accurate forecasting and better planning for civil society, policymakers and businesses. Identifying the main levers that drive the growth of AI applications can help to expedite the many positive use cases in the pipeline; like optimised renewable energy distribution at scale and Machine Learning disease diagnosis systems in healthcare. So how are the disruptive technologies redefining businesses sphere? Over the years, it is been seen that AI adaptability is increasing.
Allied Market Research recently published a report, titled, "Automotive Artificial Intelligence Market by Component (Hardware, Software, and Service), Technology (Machine Learning & Deep Learning, Computer Vision, and Natural Language Processing), and Application (Semi-Autonomous and Autonomous): Global Opportunity Analysis and Industry Forecast, 2017 – 2025." The report offers a detailed analysis of top investment pockets, top winning strategies, drivers & opportunities, market size & estimations, competitive landscape, key segments, and changing market trends. According to the report, the automotive AI market was pegged at $445.81 million in 2017 and is anticipated to hit $8.89 billion by 2025, registering a CAGR of 45.0% from 2018 to 2025. Rise in demand for enhanced user experience as well as convenience features and growing demand for autonomous vehicle have fueled the growth of the global automotive AI market. On the other hand, rise in various security & privacy concerns hamper the growth to certain extent.
This week, Nvidia reported earnings and revenues that were down compared to a year ago. But they did signal a return to growth after a couple of week quarters as the company worked off inventory pile-ups related to the collapse of cryptocurrency mining. People aren't buying graphics cards to mine for cryptocurrency anymore, but they are beefing up their gaming PCs to play high-end games, and developers are now embracing Nvidia's Turing architecture in its RTX graphics cards, said Jensen Huang, CEO of Nvidia, in an analyst call this week. But the artificial intelligence chip market had a pause with a slowdown in hyperscale deployments in data centers. We caught up with Huang for a few minutes on Thursday to talk about the state of the gaming market.
In recent reviews, trading bots, integrated with Artificial Intelligence have sought the attention of traders who don't have the knowledge of the cryptocurrency market but looking to completely rely on the robot to place trades for them. The crypto bots with artificial intelligence are a hybrid between off-the-shelf and custom-built trading robots. Since the bots are in-built with Artificial Intelligence, they are capable to customize and adjust the current trading strategies to survive the conditions of the cryptocurrency market. This means that the trader doesn't need to update the in-built program whereas the robot itself re-program depending on the current conditions.
Not all bubbles have negative consequences for the economy. An AI bubble is more likely to generate value than wreak havoc. With investments in artificial intelligence rising rapidly, especially in China and the United States, two questions arise: Are we heading toward an AI bubble? And if so, how bad would it be if the bubble were to burst? Having studied AI intensely for the past two years, our best guess to the first question is, yes, today's fascination with all things AI has most of the trappings of a financial bubble.
AI encompasses an array of technologies, from fully automated or autonomous intelligence to assisted or augmented intelligence. Financial firms are already deploying some relatively simple AI tools, such as intelligent process automation (IPA), which handles non-routine tasks and processes that require judgment and problem-solving to free employees to work on more valuable jobs. Banks have been using AI to redesign their fraud detection and anti-money laundering efforts for a while, and investment firms are starting to use AI to execute trades, manage portfolios, and provide personalized service to their clients. Insurance organizations, in turn, have been turning to AI--and especially machine learning (ML)--to enhance products, pricing, and underwriting; strengthen the claims process; predict and prevent fraud; and improve customer service and billing. But before financial institutions can reap all of AI's benefits, they must first overcome challenges, including security, privacy, bias, and regulatory issues.