The MarketWatch News Department was not involved in the creation of this content.
Oct 13, 2022 (Heraldkeepers) -- The Artificial Intelligence In Military Market research report encompasses a thorough study of the current situation of the global market along with several market dynamics. To formulate this report, detailed analysis has been performed with inputs from industry experts. Depending on the client's demand, a huge amount of business and market-related information has been brought together via this report that eventually helps businesses create better strategies. All of these features are strictly applied while building this Global Artificial Intelligence In Military Market research report for a client. It gives an explanation about various definitions and segmentation or classifications of the industry, application of the industry, and value chain structure.
The market size was determined by estimating the market through a top-down and bottom-up approach, which was further validated with industry interviews. Considering the nature of the market we derived it by segment aggregation, the contribution of the materials and vendor share.
Click Here to get and Understand Latest Key Trends on Global Artificial Intelligence In Military Market:
Companies involved in the Global Artificial Intelligence In Military Market research report are:
Lockheed Martin, Raytheon, Northrop Grumman, IBM, Thales Group, General Dynamics, NVIDIA, BAE Systems, Leidos, SAIC, SparkCognition, Charles River Analytics, L3 Harris
Artificial Intelligence In Military Market, By Segmentation:
Artificial Intelligence In Military Market segment by Type:
Learning and Intelligence
Artificial Intelligence In Military Market segment by Application:
Geographic Segment Covered in the Report:
The Global Artificial Intelligence In Military Market growth report offer insights and statistics about the market area which is further also divided into sub-regions and countries. For the purpose of this study, the report has been segmented into following regions and countries:-
1. North America (USA and Canada)
2. Europe (UK, Germany, France and the rest of Europe)
3. Asia Pacific (China, Japan, India, and the rest of the Asia Pacific region)
4. Latin America (Brazil, Mexico, and the rest of Latin America)
5. Middle East and Africa (GCC and rest of the Middle East and Africa)
The Global Artificial Intelligence In Military Market size report provides answers to the following key questions:
1. Which are Trending factors influencing the market shares of the top regions across the globe? What is the impact of Covid19 on the current industry? What is economic impact on market?
2. When is the recovery expected from the pandemic?
3. Which segments offer high-growth opportunities in the long run?
4. What are the key outcomes of the five forces analysis of the global market?
5. What are sales, revenue, and price analysis by regions of this market?
Highlights of the Global Artificial Intelligence In Military Market Report:
Market Development: Comprehensive information about emerging industry. This report analyses for various segments across geographies.
Development/Innovation: Detailed insights on the upcoming technologies, RandD activities, and product launches in the market.
Competitive Assessment: In-depth assessment of the market strategies, geographic and business segments of the leading players in the industry.
Market Diversification: Exhaustive information about new launching, untapped geographies, exact developments, and investments in the market.
If you have any query, Ask our analyst for more information: –
Contact us :-
The MarketWatch News Department was not involved in the creation of this content.
New Jersey, NJ -- (SBWIRE) -- 10/10/2022 -- The Global Artificial Intelligence (AI) in Insurance Market Report assesses developments relevant to the insurance industry and identifies key risks and vulnerabilities for the Artificial Intelligence (AI) in Insurance Industry to make stakeholders aware with current and future scenarios. To derive complete assessment and market estimates a wide list of Insurers, aggregators, agency were considered in the coverage; Some of the top players profiled are Google, Microsoft Corporation, Amazon Web Services Inc, IBM Corporation, Avaamo Inc, Baidu Inc, Cape Analytics LLC, Oracle Corporation & ?Artificial Intelligence (AI) in InsuranceMarket Scope and Market Breakdown.
Next step one should take to boost topline? Track exact strategic moves and product landscape of Artificial Intelligence (AI) in Insurance market.
Get Free Access of Global Artificial Intelligence (AI) in Insurance Market Research sample PDF https://www.htfmarketreport.com/sample-report/3570714-global-artificial-intelligence-205
Globally, the insurance industry experienced strong premium growth in 2022, at percent, whereas growth in 2022 is noticeably slower, at percent. Total premiums (GWP) are expected to reach ... by 2028. Artificial Intelligence (AI) in Insurance Companies seeking top growth opportunities in the global insurance markets can explore both the fastest-growing markets and the largest developed markets; the slowing growth rates suggest; however, most carriers would also need to search farther afield. "The growth during this period will be fuelled by the emerging markets in the APAC and Latin American regions"
The report depicts the total market of Artificial Intelligence (AI) in Insurance industry; further market is broken down by application [on, Life Insurance, Car Insurance, Property Insurance, Channel, By Channels, Market has been segmented into, Direct Sales, Distribution Channel, Regional & Country Analysis, North America Country (United States, Canada), South America (Brazil, Argentina, Peru, Chile, Rest of South America), Asia-Pacific (China, Japan, India, South Korea, Australia, Singapore, Malaysia, Indonesia, Philippines, Thailand, Vietnam, Others), Europe (Germany, United Kingdom, France, Italy, Spain, Switzerland, Netherlands, Austria, Sweden, Norway, Belgium, Rest of Europe) & Rest of World [GCC, South Africa, Egypt, Turkey, Israel, Others]], type [, Software & Platform] and country.
Geographically, the global version of report covers following regions and country:
- North America [United States, Canada and Mexico]
- Europe [Germany, the UK, France, Italy, Netherlands, Belgium, Russia, Spain, Sweden, and Rest of Europe]
- Asia-Pacific [China, Japan, South Korea, India, Australia, Southeast Asia and Others]
- South America [Brazil, Argentina, Chile and Rest of South America]
- Middle East and Africa (South Africa, Turkey, Israel, GCC Countries and Rest of Africa)
Browse Executive Summary and Complete Table of Content @ https://www.htfmarketreport.com/reports/3570714-global-artificial-intelligence-205
Research Approach & Assumptions:
- HTF MI describe major trends of Global Artificial Intelligence (AI) in Insurance Market using final data for 2022 and previous years, as well as quarterly or annual reports for 2022. In general, Years considered in the study i.e. base year as 2022, Historical data considered as 2022-2028and Forecast time frame is 2022-2028.
- Various analytical tools were used to assess how the insurance Sector and particularly Artificial Intelligence (AI) in Insurance Industry might respond over the next decade to global macroeconomic shifts. Our "consensus scenario" assumes a recovery of Global GDP growth in the coming years in addition to fluctuating interest rates; the results presented in Artificial Intelligence (AI) in Insurance Market report reflect the output of this model.
- While calculating growth of Artificial Intelligence (AI) in Insurance Market, we generally used nominal gross premium figures based on 2022 fixed exchange rates, since this data allowed us to compare local growth rates without the interference of currency fluctuations. The exceptions, which use floating exchange rates, are Argentina, Ukraine, and Venezuela, many African Countries etc due to high inflation rates.
Get full access to Global Artificial Intelligence (AI) in Insurance Market Report; Buy Latest Edition Now @: https://www.htfmarketreport.com/buy-now?format=1&report=3570714
Thanks for studying Artificial Intelligence (AI) in Insurance Industry research publication; you can also get individual chapter wise section or region wise report version like USA, China, Southeast Asia, LATAM, APAC etc.
HTF Market Intelligence consulting is uniquely positioned empower and inspire with research and consulting services to empower businesses with growth strategies, by offering services with extraordinary depth and breadth of thought leadership, research, tools, events and experience that assist in decision making.
For more information on this press release visit: http://www.sbwire.com/press-releases/artificial-intelligence-ai-in-insurance-market-may-see-a-big-move-google-microsoft-ibm-1358920.htm
PR & Marketing Manager
HTF Market Intelligence Consulting Pvt. Ltd.
Email: Click to Email Nidhi bhawsar
As you know, these machines didn’t stay simple; the mid-20th century computer modernized, compacted, and went on to change the world. This is the path many believe quantum computers are now on: elementary today — transformative tomorr... well, we’ll see.
The promise of computers based on subatomic physics is tantalizing. In theory, problems that would take classical computers years to solve could be handled by quantum computers in minutes, bursting open advancements in finance, chemistry, artificial intelligence, logistics, cybersecurity and more.
The possibilities of what quantum could accomplish are vast and hard to pinpoint. Researchers don’t know when a real-world quantum breakthrough will occur, but many do say “when,” not “if.”
“Quantum is progressing faster than many people are anticipating,” said Eric Ghysels, a finance and economics professor at Univerity of North Carolina-Chapel Hill. “This thing is coming, and you better be prepared.”
In 2018, IBM picked N.C. State’s Centennial Campus as the site of its first IBM Quantum Hub in North America.
Two years later, Duke partnered with the Maryland-based company IonQ to open the Duke Quantum Center inside downtown Durham’s Chesterfield building. Under their arrangement, IonQ has exclusive rights to the intellectual property the lab produces while Duke has received equity in the public company.
IBM and IonQ — and by extension N.C. State and Duke — are racing toward a common goal: to achieve what’s known as “quantum advantage,” the still-elusive moment when a quantum computer can perform a real-world task better than a classical computer. (The term “quantum supremacy” refers to a moment when a quantum computer achieves something a classical computer could never accomplish.)
But chasing quantum advantages is where similarities between the two facilities end, said Chris Monroe, cofounder of IonQ and the director of the Duke Quantum Center. “IBM’s approach and our approach couldn’t be more different,” he said.
To understand their differences, it helps to understand some of quantum’s underlying science.
Quantum computers reflect the physics of the subatomic world to manage information. While classical computers run on bits represented by digital 1s and 0s, quantum computers use quantum bits, called qubits, to display microscopic states in a much more complex manner.
A pair of quantum mechanical phenomena make these machines exponentially more advanced. The first is called superposition — the capacity of a qubit to be in multiple positions at once until it’s measured. The second is entanglement, which is how different qubits are interwoven.
All this can be quite confusing to the layman, and even to other scientists, quantum researchers acknowledge.
“The laws of microscopic physics look very, very different from what you and I experience on a normal day,” said Patrick Dreher, the chief scientist at N.C. State’s IBM Quantum Hub.
Instead of single answers, quantum computers spit out probability distributions. For example, they wouldn’t say 2 + 3 = 5 but would answer with a range of probabilities peaking around 5. This is one of the reasons researchers say quantum computers will augment, but never fully replace, digital Macs or PCs. Quantum machines could handle massive calculations, but quotidian tasks like Microsoft Word, basic mathematics and streaming videos may always be best served by classical computers.
So, what’s keeping quantum computers from reaching their potential? There are several hurdles.
As one might expect, the subatomic realm is difficult to control. Atoms naturally bounce around, which can cause contamination that leads to “noisy” results. The microscopic interactions computers must capture occur incredibly quickly, requiring extreme precision, and when errors arise, attempts to correct one qubit can easily interfere with other qubits.
“It’s a fragile machine,” Dreher said. “And because they are noisy, they have a limited ability to keep doing computations forever.”
Despite their limitations, quantum computers have evolved from theory to tangible, functioning machines. Researchers have named this current stage the Noisy Intermediate-Scale Quantum, or NISQ, era. There are several intermediate-scale, noisy computers running today, with Dreher saying no one knows which will be “the home run.”
Of all the quantum computers in the world, IBM’s are likely the most ornate. Nicknamed “chandeliers,” they feature gold-plated, five-level apparatuses with an orderly progression of tubes and wires running down to single silicon processor chips. At the bottom rung, each chandelier cools a superconducting chip.
And by cool, IBM means really, really frigid.
Quantum researchers attempt to control subatomic activity by creating extreme environments, and the chandelier does this with temperature. At its lowest level, the temperate is .01 degrees Kelvin, making it one of the coldest places in the universe.
IBM operates more than 20 quantum computers around the world, from upstate New York to Japan, and they offer members of their quantum network — like N.C. State — exclusive access to advanced computers which are kept inside a metal silo and behind a glass cube like a museum art piece. As a member of the IBM Quantum Network, N.C. State scientists can run remote experiments on these computers through the cloud.
Duke students, on the other hand, have access to a quantum computer they can touch. The Duke Quantum Center studies a type of computer called ion-trap, which levitates individual atoms above a gold-plated silicon chip in an airless vacuum. Lasers are then shot at the atom to modify the state of the qubits inside the atom and affect how they interact. Chris Monroe compared the process to plucking a guitar string.
The handful of ion-trap computers at Chesterfield are aesthetically less impressive than IBM’s chandelier. They stretch out like a crowded city — vacuum chambers, camera lenses, modulators and lasers intricately huddled together. Monroe touts these machines as the most advanced ion-traps in the world and believes once the engineering obstacles are overcome (in short, it’s very difficult to precisely strike atoms with lasers), IonQ computers can be widely available.
“We envision a future where quantum computers are in people’s pockets,” he said.
While N.C. State and Duke focus on quantum research, UNC is a national leader on quantum technologies in finance.
In May 2020, the school started one of the country’s first webinar series on applying quantum to business. To meet the growing demand for quantum, the UNC Kenan-Flagler Business School has adjusted its curriculum to include more about quantum. “The stakes are high,” said Eric Ghysels. “A lot of financial institutions realize they better get started now, even if the science is a few years away.”
The financial industry is well positioned for early quantum applications. First, it’s an analytic-based industry where precise timing and price modeling can mean billions. Many foresee quantum optimizing portfolios and delivering unprecedented account security. Second, with so much money on the line, deep-pocketed companies are making significant investments in the field.
In March, Fidelity entered a partnership with N.C. State’s hub, and IBM itself is interested in the research its hub produces for finance purposes. “In terms of fintech, the Triangle is becoming a considerable force,” Ghysels said. “Companies want to hire here and settle here.”
The Triangle lacks the concentration of quantum companies seen in cities like San Francisco, Boston and New York, but there are signs the commercial side of quantum is burgeoning locally as larger companies like Apple and Google enter the market.
The California quantum computing manufacturer Atom Computing recently based its executive office in Cary, and startups like Dark Star Quantum Lab in Apex seek to find a niche in quantum consulting.
“It makes sense this would be a good place for quantum in terms of applications,” said Dark Star CEO Faisal Shah Khan.
Khan noted the Triangle’s relative proximity to the financial capital of New York City (same time zone, quick flight away) makes it an even more attractive place for quantum and fintech.
So when will quantum computers be ready?
“If I knew that, I wouldn’t be here as a professor,” Patrick Dreher said. “I’d be on Wall Street, or I’d be talking to (venture capitalists). You’re asking me in 1949, ‘When are we going to build a digital computer that won’t have vacuum tubes and need a whole room to make it work?’ This is why people win Nobel Prizes.”
In 2019, Google announced it had achieved quantum superiority on a contrived mathematical problem, meaning one that doesn’t relate to a real-world situation. IBM pushed back on Google’s claim, and the quantum superiority debate lingers.
Quantum technology remains in a “pre-competitive stage,” said Dennis Kekas, an associate vice chancellor at N.C. State’s Centennial Campus. By this, Kekas meant companies generally still share their findings in service of scientific advancement. In academia, UNC, Duke and N.C. State host a weekly Triangle Quantum Computing Seminar Series throughout the school year, inviting experts from around the globe.
At Chesterfield, Duke PhD students are on the front lines of quantum research. Their current lab work focuses on getting ion-trap computers to communicate with each other, sharing information between machines like classical computers can do now. In exact years, they have seen colleagues go on to jobs as quantum business consultants, continue in academia, join IonQ, or get brought into national labs like Los Alamos.
Asked about the future of quantum, the students’ perspectives were a reminder that no one knows for sure — not them, not their teachers, not the companies that might hire them — if the quantum dream will ever be realized. They spoke of keeping the long view in mind and noted quantum advantage isn’t likely to be right around the corner.
Jameson O’Reilly, a fourth-year PhD student at the lab, said he believes quantum advantage will eventually be achieved, but if it isn’t, he said it still will have been worth the effort.
“I think that if it doesn’t happen, it will fail in some interesting way,” he said. “In a way that gives us more understanding of the universe.”
©2022 The News & Observer. Distributed at Tribune Content Agency, LLC.
A four-year bachelor’s degree has long been the first rung to climbing America’s corporate ladder.
But the move to prioritize skills over a college education is sweeping through some of America’s largest companies, including Google, EY, Microsoft, and Apple. Strong proponents say the shift helps circumvent a needless barrier to workplace diversity.
“I really do believe an inclusive diverse workforce is better for your company, it’s good for the business,” Ginni Rometty, former IBM CEO, told Fortune Media CEO Alan Murray during a panel last month for Connect, Fortune’s executive education community. “That’s not just altruistic.”
Under Rometty’s leadership in 2016, tech giant IBM coined the term “new collar jobs” in reference to roles that require a specific set of skills rather than a four-year degree. It’s a personal commitment for Rometty, one that hits close to home for the 40-year IBM veteran.
When Rometty was 16, her father left the family, leaving her mother, who’d never worked outside the home, suddenly in the position to provide.
“She had four children and nothing past high school, and she had to get a job to…get us out of this downward spiral,” Rometty recalled to Murray. “What I saw in that was that my mother had aptitude; she wasn’t dumb, she just didn’t have access, and that forever stayed in my mind.”
When Rometty became CEO in 2012 following the Great Recession, the U.S. unemployment rate hovered around 8%. Despite the influx of applicants, she struggled to find employees who were trained in the particular cybersecurity area she was looking for.
“I realized I couldn’t hire them, so I had to start building them,” she said.
In 2011, IBM launched a corporate social responsibility effort called the Pathways in Technology Early College High School (P-TECH) in Brooklyn. It’s since expanded to 11 states in the U.S. and 28 countries.
Through P-TECH, Rometty visited “a very poor high school in a bad neighborhood” that received the company’s support, as well as a community college where IBM was offering help with a technology-based curriculum and internships.
“Voilà! These kids could do the work. I didn’t have [applicants with] college degrees, so I learned that propensity to learn is way more important than just having a degree,” Rometty said.
Realizing the students were fully capable of the tasks that IBM needed moved Rometty to return to the drawing board when it came to IBM’s own application process and whom it was reaching. She said that at the time, 95% of job openings at IBM required a four-year degree. As of January 2021, less than half do, and the company is continuously reevaluating its roles.
For the jobs that now no longer require degrees and instead rely on skills and willingness to learn, IBM had always hired Ph.D. holders from the very best Ivy League schools, Rometty told Murray. But data shows that the degree-less hires for the same jobs performed just as well. “They were more loyal, higher retention, and many went on to get college degrees,” she said.
Rometty has since become cochair of OneTen, a civic organization committed to hiring, promoting, and advancing 1 million Black individuals without four-year degrees within the next 10 years.
If college degrees no longer become compulsory for white-collar jobs, many other qualifications—skills that couldn’t be easily taught in a boot camp, apprenticeship program, or in the first month on the job—could die off, too, University of Virginia Darden School of Business professor Sean Martin told Fortune last year.
“The companies themselves miss out on people that research suggests…might be less entitled, more culturally savvy, more desirous of being there,” Martin said. Rather than pedigree, he added, hiring managers should look for motivation.
That’s certainly the case at IBM. Once the company widened its scope, Rometty said, the propensity to learn quickly became more of an important hiring factor than just a degree.
This story was originally featured on Fortune.com
More from Fortune:
A 2007 flashback: home flippers are in trouble again
Managing Gen Z is like working with people ‘from a different country’
The Renault Nissan empire once held together by fugitive Carlos Ghosn may slowly be unraveling
PayPal tells users it will fine them $2,500 for misinformation, then backtracks immediately
The MarketWatch News Department was not involved in the creation of this content.
Oct 10, 2022 (Alliance News via COMTEX) -- Quadintel's exact global Artificial Intelligence In Fintech market research report gives detailed facts with consideration to market size, cost revenue, trends, growth, capacity, and forecast till 2030. In addition, it includes an in-depth analysis of This market, including key factors impacting the market growth.
The Global Artificial Intelligence In Fintech Market size is expected to reach $25.8 billion by 2028, rising at a market growth of 16.8% CAGR during the forecast period.
This study offers information for creating plans to increase the market’s growth and effectiveness and is a comprehensive quantitative survey of the market.
Download Free sample of This Strategic Report :-https://www.quadintel.com/request-sample/global-artificial-intelligence-in-fintech-market/QI046
For industry executives, marketing, sales, and product managers, consultants, analysts, and stakeholders searching for vital industry data in easily accessible documents with clearly presented tables and graphs, the research contains historical data from 2017 to 2020 and predictions through 2030.
GlobalArtificial Intelligence In Fintech MarketSize, Share & Industry Trends Analysis Report By Component (Solutions and Services), By Deployment (On-premise and Cloud), By Application, By Regional Outlook and Forecast, 2022 ? 2028
Insurance executives and future banking agents would ask the proper questions to robots rather than human experts as a result of data-driven management decisions at a reduced cost. Machines would then analyze the data and provide recommendations that will aid leaders and subordinates in making better decisions. Users can employ automated financial assistants and planners to help them make financial decisions. These include events tracking, stock and bond price trends based on the user's financial goals and personal portfolio, that can aid in the recommendation of bonds and stocks to buy or sell. These systems, dubbed "Robo-Advisors," are highly being provided by both traditional financial firms and Fintech startups.
Bright well Payments, a financial services firm that offers financial solutions to transport money safely anywhere in the world, announced the launching of ARDEN in May 2022. This risk-detection engine powered by AI helps fintech companies protect their cardholders and financial assets. Globally, banks are implementing AI-enabled solutions to enhance safety, and AI provides banks the advantage of digitization. Additionally, it enables them engage with other fintech businesses. Apps that necessitate UPI, a fingerprint, or facial recognition are available from financial institutions.
UPI is one of the most widely used digital payment systems in India, and the system was created to enable payments to be executed in seconds. To generate critical insights, financial firms utilize AI to handle and assess data from a variety of sources. Banks might use such inventive solutions to solve challenges they have when providing services like payment processing and loan management. Many banking apps offer personalized financial advice to assist users in achieving their financial goals, tracking their income & expenditures, and performing other financial chores. AI-powered finance advances are primarily responsible for this customization.
The latest coronavirus outbreak has been beneficial to the market. Due to the coronavirus pandemic, business activity has been halted, resulting in disruptions in border restrictions, supply chains, and travel restrictions imposed by government bodies. As a result, banks and fintech companies are adopting a work-from-home attitude. Moreover, banks and financial institutions are implementing AI technologies to extract information and insights from unstructured documents and automate the laborious procedure that banks have traditionally completed in shorter period of time. For example, Temenos, a banking software business, announced the introduction of eight propositions in April 2020, utilizing breakthrough Explainable AI (XAI) and cloud technologies to assist banks and financial institutions in responding to the COVID-19 situation.
Market Growth Factors
Reduction in cost and better efficiency along with enhanced wealth management
Artificial intelligence in fintech is enabling businesses to minimize costs, automate processes, and lessen the risk of human mistake. Companies utilize AI Chatbots as customer assistants for a variety of tasks, including sales, customer service (over the phone), and online chat. AI is enabling small finance organizations since it is cost-effective and has a minimal risk of error. Furthermore, the end user is gaining momentum for the insightful facts regarding cash flow, income, and expense, as this would assist organizations cut their expenses. Lesser net worth market groups are provided digital and wealth management advice services, leading to low fee-based commissions.
Various technological enhancements would increase the popularity of AI in fintech
Credit card fraud is one of the most common types of cybercrime. As a result, firms are developing the next-generation of algorithms called Convolutional Neural Networks, which are based on the visual cortex, a small portion of cells in the human body that is sensitive to particular regions of the visual field. They can extract basic visual elements such as aligned edges, end-points, and corners in this way. This system can analyze an individual's funding data and establish whether they made the most exact credit card transaction or if their credit card data was used by someone else based on that data.
Market Restraining Factors
Data security and privacy concerns of the users
Most fintech businesses are dealing with the sensitive subject of data privacy and security that is the largest hurdle with AI. Because any data breach or security failure might be disastrous, the fintech sector is overseen by tight adherence to standards and governance. Since businesses nourish more and more user and provider information into advanced, AI-fueled algorithms, innovative bits of personal data are created without the knowledge of the way it affected clients and employees, which ultimately leads to the rising privacy concerns. This is especially true in the retail banking industry, in which the collection of consumer data is at the forefront of big data challenges.
Based on Component, the market is segmented into Solutions and Services. The solution segment procured the highest revenue share in the Artificial Intelligence In Fintech Market in 2021. The high proportion can be due to software tools, which help banks adopt AI-enabled solutions that extract correct and comprehensive data from large amounts of data in a timely manner. Some firms' solutions help them accomplish things like develop their retail banking company with next-best-action software, identify and battle financial fraud, and Strengthen client relationships with multichannel user experience solutions.
Based on Deployment, the market is segmented into On-premise and Cloud. The cloud segment garnered a substantial revenue share in the Artificial Intelligence In Fintech Market in 2021. From 2022 to 2030, the cloud segment will grow at the quickest rate. AI-based algorithms that learn from historical data in a public cloud, detect current norms, and make recommendations are credited with the increase. In data handling and authenticity, the cloud and AI may boost efficiency, and digital security, and this automated technique removes human errors throughout data processing
Based on Application, the market is segmented into Business Analytics & Reporting, Customer Behavioral Analytics, Fraud Detection, Virtual Assistant (Chatbots), Quantitative & Asset Management and Others. Business Analytics and Reporting segment witnessed the maximum revenue share in the Artificial Intelligence In Fintech Market in 2021. Regulatory and compliance management, as well as customer behaviour monitoring, benefit from business analytics and reporting. More efficiency, more educated decision, and higher revenues are all elements that have contributed to the segment's growth.
Based on Regions, the market is segmented into North America, Europe, Asia Pacific, and Latin America, Middle East & Africa. North America emerged as a leading region in the Artificial Intelligence In Fintech Market with the largest revenue share in 2021. It is due to the industrialized economies of the United States and Canada placing a major focus on R&D-derived technologies. In fintech, this region has the most competitive and rapidly developing AI technology. Many startups and rising firms that provide AI services to the finance sector are also fueling the trend.
The major strategies followed by the market participants are Partnerships. Based on the Analysis presented in the Cardinal matrix; Microsoft Corporation and Google LLC are the forerunners in the Artificial Intelligence In Fintech Market. Companies such as Oracle Corporation, Intel Corporation and IBM Corporation are some of the key innovators in the Market.
The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include IBM Corporation, Oracle Corporation, Microsoft Corporation, Google LLC, Intel Corporation, Salesforce.com, Inc., Amazon Web Services, Inc., ComplyAdvantage, Amelia US LLC, and Inbenta Technologies, Inc.
Access full Report Description, TOC, Table of Figure, Chart, etc. @https://www.quadintel.com/request-sample/global-artificial-intelligence-in-fintech-market/QI046
Recent Strategies deployed in Artificial Intelligence In Fintech Market
Partnerships, Collaborations and Agreements:
Jun-2022: Amazon Web Services (AWS) teamed up with Hong Kong Science and Technology Parks Corporation (HKSTP). This collaboration aimed to boost a robust Innovation and Technology (I&T) ecosystem in Hong Kong. Through this collaboration, AWS and HKSTP would introduce a series of programs under four key pillars to accelerate the innovation of IT companies, startups, and researchers across their whole growth cycle.
May-2022: Amazon Web Services (AWS) joined hands with RBL Bank and Amazon Pay. This collaboration aimed to introduce UPI payments, along with offering peer-to-peer and peer-to-merchant transactions. Through this integration, Amazon Pay would issue NPCI?s allocated UPI ID with the manage @rapl, to RBL Bank.
May-2022: Oracle PartnerNetwork (OPN) collaborated with Temenos, the cloud banking platform. The collaboration aimed to allow Oracle?s global customers like financial services organizations across the world, to implement its robust Explainable AI and machine learning capabilities through Oracle Cloud Marketplace.
May-2022: Salesforce came into a partnership with Upstart, a leading artificial intelligence (AI) lending platform. This partnership aimed to bring AI-enabled lending to the financial services industry, which can assist financial institutions to modernize lending, stay competitive, and delivering better customer service to users.
Apr-2022: ComplyAdvantage came into a partnership with Xapien, a deep-technology company. This partnership aimed to provide a ground-breaking due diligence solution to the market, wherein there is a huge requirement for a deep understanding of sanctioned parties or PEPs.
Apr-2022: IBM formed a partnership with Skyscend, a fintech start-up with headquarters in Atlanta, GA. Under this partnership, IBM's Embedded Solution Agreement (ESA) would enable Skyscend to integrate IBM's cutting-edge technologies with its Skyscend Pay B2B SaaS fintech platform to service the global marketplace.
Mar-2022: Google Cloud came into a partnership with Mizuho Financial Group (MFG), a Japanese bank holding company. This partnership aimed to show the firm modernize its systems, develop a new digital marketing platform on Google Cloud, and release a new digital financial service portfolio like Banking-as-a-Service (BaaS).
Feb-2022: Google Cloud entered into a partnership with KeyBank, and Deloitte. This partnership aimed to boost KeyBank?s commitment to a cloud-first approach to banking. In this partnership, KeyBank would become the largest regional banks in the United States to manage its primary platforms and applications on Google Cloud infrastructure, enabling the financial institution to shift the way it creates, operationalizes, and provides digital experiences to customers, partners, and teammates with security at its core.
Feb-2022: Microsoft came into partnership with U.S. Bank as part of a significant investment by US bank in its technology infrastructure. This partnership aimed to use Artificial intelligence (AI) and machine learning (ML) in order to support the bank?s applications and infrastructure along with augmenting customer privacy and the security of data and financial assets.
Oct-2021: Oracle NetSuite teamed up with HSBC, a British multinational universal bank and financial services holding company. This collaboration aimed to introduce a Banking as a Service (BaaS) offering, which would allow customers to provide business banking services via their own platforms.
Feb-2021: Google Cloud formed a partnership with BBVA, a customer-centric global financial services group. This partnership aimed to transform the bank?s security strategy by enhancing and optimizing its security infrastructure. Under this partnership, BBVA would collaborate with Google Cloud in the development of the new artificial intelligence (AI) and machine learning (ML) models to forecast and prevent cyberattacks against its banking infrastructure, offering a more secure experience for the bank and its customers.
Dec-2020: Google Cloud formed a partnership with Deutsche Bank, one of the world's leading financial service providers. This partnership aimed to boost the transformation of the bank to the cloud. For Deutsche Bank?s customers, the agreement would reshape the way products and services are developed and delivered.
Jul-2020: Microsoft signed a multi-year cloud agreement with Finastra, a financial software company. This agreement aimed to assist the digital transformation of financial services. Together, the companies would support banks, credit unions, and other firms in the sector to utilize Power Platform, Azure, and Microsoft 365.
Product Launches and Product Expansions:
Apr-2022: Salesforce released CRM Analytics, AI-based insights for sales, marketing, and service teams in every industry. These technologies would assist sales leaders, service leaders, and employees across any industry like financial services, consumer goods, manufacturing, and communications, put data at the center of each customer relationship, and eventually provide more customized experiences.
Apr-2022: IBM introduced IBM z16, Real-Time AI for Transaction Processing. This technology would bring AI inferencing, through its IBM Telum Processor, with highly protected and reliable high-volume transaction processing.
Jan-2022: Google introduced a Google Cloud digital assets team. This team would support customers' requirements in building, transacting, storing value, and deploying new products on blockchain-based platforms.
May-2021: IBM introduced new advances in artificial intelligence (AI), hybrid cloud, and quantum computing. These advanced would assist IBM's customers and partners boost their digital transformations, returning to work smarter, and developing strategic ecosystems that would generate better business results.
Apr-2021: ComplyAdvantage released a new early-stage anti-money laundering (AML) program. The program would offer qualified startups free access to the company?s leading AML and Know Your Customer (KYC) tools and resources required to uncover and decrease the threat of money-laundering activities.
Nov-2020: Google Cloud unveiled the new Document AI (DocAI) platform, a unified console for document processing. Through this latest DocAI platform, customers can rapidly access all parsers, tools, and solutions with a unified API, allowing an end-to-end document solution from evaluation to deployment.
Acquisitions and Mergers:
Mar-2022: Microsoft took over Nuance Communications, artificial intelligence (AI), and speech technology firm. This acquisition aimed to bring together Nuance?s best-in-class conversational AI and ambient intelligence with Microsoft?s safe and trusted industry cloud portfolio.
Jan-2022: Oracle took over Federos, a provider of unified service management solutions for service providers. This acquisition aimed to expand Oracle Communications? application portfolio by introducing AI-optimized assurance, analytics, and automation solutions to maintain the accessibility and performance of crucial networks and systems.
Dec-2020: IBM took over Expertus Technologies, a Montreal-based fintech company. This acquisition aimed to strengthen IBM's portfolio as an end-to-end digital payments solution provider and Strengthen IBM's hybrid cloud and AI strategy.
Oct-2020: Intel completed the acquisition of SigOpt, a startup out of San Francisco. Through this acquisition, Intel would double down on building chips and related architecture for the next generation of computing, which would boost Intel's expertise in the area of future technology: artificial intelligence.
Download sample Report, SPECIAL OFFER (Avail an Up-to 30% discount on this report ): -https://www.quadintel.com/request-sample/global-artificial-intelligence-in-fintech-market/QI046
Scope of the Study
Market Segments covered in the Report:
Business Analytics & Reporting
Customer Behavioral Analytics
Virtual Assistant (Chatbots)
Quantitative & Asset Management
Rest of North America
Rest of Europe
Rest of Asia Pacific
Rest of LAMEA
Amazon Web Services, Inc.
Amelia US LLC
Inbenta Technologies, Inc.
We are the best market research reports provider in the industry. Quadintel believes in providing quality reports to clients to meet the top line and bottom line goals which will boost your market share in today's competitive environment. Quadintel is a 'one-stop solution' for individuals, organizations, and industries that are looking for innovative market research reports.
We will help you in finding the upcoming trends that will entitle you as a leader in the industry. We are here to work with you on your objective which will create an immense opportunity for your organization. Our priority is to provide high-level customer satisfaction by providing innovative reports that enable them to take a strategic decision and generate revenue. We update our database on a day-to-day basis to provide the latest reports. We assist our clients in understanding the emerging trends so that they can invest smartly and can make optimum utilization of resources available.
Get in Touch with Us:
The MarketWatch News Department was not involved in the creation of this content.
IBM shook up the digital health space Friday with the news that it is selling its healthcare data and analytics assets, currently part of the Watson Health business, to an investment firm. The sale price is reportedly more than $1 billion, although the companies are not officially disclosing the financial terms.
There are a lot of interesting factors to consider as we unpack this news, although some thought leaders say the divestiture did not come as a surprise.
“The Watson Health sale has been anticipated for quite some time. IBM was clearly not gaining much traction in the healthcare market while others such as Google and Microsoft have pulled ahead. Even Oracle has made a big splash in healthcare with its exact announcement to acquire Cerner," said Paddy Padmanabhan, founder and CEO of Damo Consulting, a growth strategy and digital transformation advisory firm that works with healthcare and technology companies.
IBM was one of the first big tech companies to dive into healthcare with its well-known Watson Health supercomputer known for defeating the greatest champions on “Jeopardy!" The platform created a lot of buzz back in 2011, and many people had high hopes for the platform's potential applications in healthcare. In exact years, however, that buzz has significantly died down.
"In the current competitive landscape, IBM would not be considered a significant player in healthcare. Selling off the data assets essentially means an end to the Watson Health experiment; however, it may allow IBM as an organization to refocus and develop a new approach to healthcare,” Padmanabhan said.
Assuming there are no regulatory snags, the deal is expected to close in the second quarter of this year.
“Today’s agreement with Francisco Partners is a clear next step as IBM becomes even more focused on our platform-based hybrid cloud and AI strategy,” said Tom Rosamilia, senior vice president of IBM Software. “IBM remains committed to Watson, our broader AI business, and to the clients and partners we support in healthcare IT. Through this transaction, Francisco Partners acquires data and analytics assets that will benefit from the enhanced investment and expertise of a healthcare industry focused portfolio.”
The agreement calls for the current management team to continue in similar roles in the new standalone company, serving existing clients in life sciences, provider, imaging, payer and employer, and government health and human services sectors.
“We have followed IBM’s journey in healthcare data and analytics for a number of years and have a deep appreciation for its portfolio of innovative healthcare products,” said Ezra Perlman, co-president at Francisco Partners. “IBM built a market-leading team and provides its customers with mission critical products and outstanding service.”
In 2016 IBM doubled the size of its Watson Health business through the $2.6 billion acquisition of Truven Health Analytics. Truven offers healthcare data services targeted at employers, hospitals, and drug companies, and makes software that can parse through millions of patient records. Truven's main offices are in Ann Arbor, MI, Chicago, and Denver. At the time of the acquisition, Truven had around 2,500 employees.
The Truven deal followed other major healthcare acquisitions in the company, including Cleveland-based Explorys, Dallas-based Phytel, and Chicago-based Merge Healthcare. The company paid about $1 billion for Merge.
IBM said the assets acquired by Francisco Partners include extensive and diverse data sets and products, including Health Insights, MarketScan, Clinical Development, Social Program Management, Micromedex, and imaging software offerings.
Padmanabhan said it will be interesting to see how the new owners are able to leverage those data assets.
“IBM’s decision to sell its data assets is an indication that it’s not just enough to have the data. Applying advanced analytics on the data to generate insights that can make a difference in real-world applications is where the true value lies. IBM had several missteps early on, especially in cancer care applications, that created significant setbacks for the business that they could not recover from.
In 2018, the Watson Health business went through a round of layoffs. The company declined to tell MD+DI at the time how many of employees were let go other than to say it was a "small percentage" of the global business, but online commenters on TheLayoff.com and Watching IBM, along with multiple news reports citing unnamed sources from within the organization painted a different picture of the situation. One Dallas-based commenter on TheLayoff.com said that "we all knew it was coming but nobody expected it to be this fast and rampant," while another commenter estimated that 80% of that same Dallas-based office was let go.
While we have seen a trend in exact years with big tech firms showing an interest in healthcare, some of those companies are finding those efforts to be easier said than done.
“IBM’s decision to sell the Watson Health assets is another instance of a big tech firm acknowledging the challenges of the healthcare space. Last year, Google and Apple had significant setbacks, and Amazon has acknowledged challenges in scaling its Amazon Care business," Padmanabhan said. "In IBM’s case, they have missed out on the cloud opportunity and have lagged behind peers in emerging technology areas such as voice. While IBM’s challenges with Watson Health may have been unique to the organization, the fact is that big tech firms have multiple irons in the fire at any time, and for some healthcare may just be too hard.”
Padmanabhan does not think, however, that IBM's decision to sell the Watson Health assets is an indictment of the promise of AI in healthcare.
"Our research indicates AI was one of the top technology investments for health systems in 2021," he said. "Sure, there are challenges such as data quality and bias in the application of AI in the healthcare context, but by and large there has been progress with AI in healthcare. The emergence of other players, notably Google with its Mayo Partnership, or Microsoft with its partnership with healthcare industry consortium Truveta are strong indicators of progress."
Padmanabhan is co-author with Edward W. Marx, of Healthcare Digital Transformation: How Consumerism, Technology and Pandemic are Accelerating the Future (2020), and the host of The Big Unlock, a podcast focusing on healthcare digital transformation.
New Jersey, United States, Oct. 14, 2022 /DigitalJournal/ The Artificial Intelligence (AI) in Energy Market research report provides all the information related to the industry. It gives the markets outlook by giving authentic data to its client which helps to make essential decisions. It gives an overview of the market which includes its definition, applications and developments, and manufacturing technology. This Artificial Intelligence (AI) in Energy market research report tracks all the exact developments and innovations in the market. It gives the data regarding the obstacles while establishing the business and guides to overcome the upcoming challenges and obstacles.
AI optimizes energy networks by managing energy flows between homes, businesses, storage batteries, renewable energy sources, microgrids, and the power grid itself. This reduces energy waste while increasing consumer engagement with energy consumption. The market is driven by rapid power demand and a lack of information networks in power generation. Artificial intelligence (AI) is an extension of computer technology that highlights the formation of intelligent machines that function and react like humans. The energy and utility sector produces and distributes energy consisting of oil and gas, power generation and others.
Get the PDF sample Copy (Including FULL TOC, Graphs, and Tables) of this report @:
This Artificial Intelligence (AI) in Energy research report throws light on the major market players thriving in the market; it tracks their business strategies, financial status, and upcoming products.
Some of the Top companies Influencing this Market include:Ibm Corporation, Microsoft Corporation, Accenture Plc, Amazon Web Services, Inc., Intel Corporation, Oracle Corporation, Sap Se, Huawei Technology, Cisco Systems, General Electric Company, Rockwell Automation, C3.Ai, Autogrid Systems, Hcl Technologies, And Wipro Limited.
Firstly, this Artificial Intelligence (AI) in Energy research report introduces the market by providing an overview that includes definitions, applications, product launches, developments, challenges, and regions. The market is forecasted to reveal strong development by driven consumption in various markets. An analysis of the current market designs and other basic characteristics is provided in the Artificial Intelligence (AI) in Energy report.
The region-wise coverage of the market is mentioned in the report, mainly focusing on the regions:
Segmentation Analysis of the market
The market is segmented based on the type, product, end users, raw materials, etc. the segmentation helps to deliver a precise explanation of the market
Market Segmentation: By Type
Services, Hardware, Software,
Market Segmentation: By Application
Power Industry (Generation,Transmission,Distribution), Oil & Gas Industry (Upstream, Midstream, Downstream),
For Any Query or Customization: https://a2zmarketresearch.com/ask-for-customization
An assessment of the market attractiveness about the competition that new players and products are likely to present to older ones has been provided in the publication. The research report also mentions the innovations, new developments, marketing strategies, branding techniques, and products of the key participants in the global Artificial Intelligence (AI) in Energy market. To present a clear vision of the market the competitive landscape has been thoroughly analyzed utilizing the value chain analysis. The opportunities and threats present in the future for the key market players have also been emphasized in the publication.
This report aims to provide:
Table of Contents
Global Artificial Intelligence (AI) in Energy Market Research Report 2022 – 2029
Chapter 1 Artificial Intelligence (AI) in Energy Market Overview
Chapter 2 Global Economic Impact on Industry
Chapter 3 Global Market Competition by Manufacturers
Chapter 4 Global Production, Revenue (Value) by Region
Chapter 5 Global Supply (Production), Consumption, Export, Import by Regions
Chapter 6 Global Production, Revenue (Value), Price Trend by Type
Chapter 7 Global Market Analysis by Application
Chapter 8 Manufacturing Cost Analysis
Chapter 9 Industrial Chain, Sourcing Strategy and Downstream Buyers
Chapter 10 Marketing Strategy Analysis, Distributors/Traders
Chapter 11 Market Effect Factors Analysis
Chapter 12 Global Artificial Intelligence (AI) in Energy Market Forecast
Buy Exclusive Report @: https://www.a2zmarketresearch.com/checkout
1887 WHITNEY MESA DR HENDERSON, NV 89014
+1 775 237 4157
Investors this year increasingly turned away from dividend stocks in favor of the rising yields being offered on bonds. Given that investors can now earn a 4.3% return on a 2-year Treasury note, many prefer that guaranteed return to the risks of putting money into the stock market.
International Business Machines (IBM 1.61%) offers a dividend yield that exceeds that bond return. But with a bear market in progress, are investors better served to take a chance on the cloud stock or to take the 4.3% return at virtually zero risk?
IBM didn't participate in the bull market of the 2010s. The stock dropped as its tech businesses suffered a considerable growth slowdown. In an effort to change that, IBM pivoted into the cloud computing sector aggressively, in part via its $34 billion purchase of Red Hat in 2019. Grand View Research forecasts a compound annual growth rate of 16% through 2030 for the cloud industry. Growth like that could certainly help both IBM and its stock.
Also, IBM spun off its managed infrastructure business into a new public company, Kyndryl. This business was less of a fit with the parent company amid its pivot to the cloud. Separating it off should make it easier for IBM to grow its revenue.
Time will tell if these moves can help the stock price recover. Nonetheless, IBM currently pays its shareholders $1.65 per share every quarter, or $6.60 per share annually. At the current stock price, that adds up to a yield of 5.6% per year. Moreover, depending on your financial situation, the IRS may tax your dividends at a lower capital gains rate, which can offer an added advantage.
Additionally, IBM hiked its payout annually for 27 consecutive years, making it a Dividend Aristocrat. That status carries some importance as many income investors will be more inclined to buy and hold IBM stock because of this status. Also, since abandoning Dividend Aristocrat status tends to hurt a stock, management will probably prioritize maintaining it by continuing to raise those payouts.
Investors also can also reinvest their dividend payments into more IBM stock. However, such newly purchased shares will pay you the dividend yield at that time. The return will rise if the stock falls since investors can buy the exact cash return at a lower price. Conversely, cash yields will drop if the stock rises, but those investors still benefit since the stock has increased in value.
U.S. Treasury notes offer more stability than stocks such as IBM. Investors who purchase the 2-year Treasury note receive semiannual interest payments. At the current interest rate of 4.3%, investors will receive a 2.15% cash return on their invested amount in each of the subsequent three six-month periods. In the fourth period, when the note matures, investors receive the final 2.15% payment along with the return of their principal.
Investors should also be aware that bond values can fluctuate. If interest rates drop, the value of the bond will fall; the opposite will happen if rates rise. This affects investors if they decide to sell the bond early. Upon maturity, the note will return to its par (or nominal) value.
Additionally, bond interest payments are subject to federal income tax but exempt from state and local taxes. In some cases, this is higher than taxes on dividends. Still, bond issuers are obligated to make such payments. In contrast, IBM faces no legal obligation to continue its dividend.
Also, like with a stock, investors can reinvest their interest payments into more notes or other forms of Treasury bonds. However, those purchases will be subject to the prevailing interest rates at that time.
Investors who lack much risk tolerance should choose the Treasury note. Given its guaranteed return, they will not have to worry about volatility.
Nonetheless, for investors comfortable with buying stocks, IBM is a surprisingly strong buy. The cloud industry is in growth mode, which should propel IBM stock to a long-awaited turnaround. Moreover, IBM has repeatedly shown it wants to hold on to its Dividend Aristocrat status. This should supply its income investors returns that are not only larger than the bonds offer, but also likely to increase in size.