Artificial Intelligence
Swedbank Assigned ESG Evaluation Score Of 75; Preparedness Adequate
S&P Global Ratings has assigned Swedbank AB an ESG Evaluation score of 75 (out of 100; see “Swedbank AB: ESG Evaluation” published today). The company’s ESG Evaluation score is the result of an ESG profile of 72, combined with an adequate (+3) preparedness. Higher numbers indicate stronger sustainability in our evaluations.
Headquartered in Stockholm, Swedbank is among the leading Nordic banks, with around €250 billion of assets. It provides a wide range of financial services to retail, midsize, and large corporate customers, with leading market positions in Sweden and the Baltic countries.
Our ESG Evaluation of 75 is supported by Swedbank’s established environmental, social, and governance (ESG) integration along its value chain, but is constrained by past governance deficiencies. These were brought to light by the 2019 money laundering controversy.
Swedbank’s asset management arm, Robur, was among the first to integrate ESG, with a particular focus on climate-related issues. The implementation of an advanced responsible investment framework has enabled Robur to reduce the carbon footprint of its portfolios and should support its commitment to align its investments with a 1.5 degrees Celsius climate scenario by 2025. Although the bank’s ESG integration in terms of its lending activities is less developed, in our view, it is on track to roll out additional sector-specific ESG guidance, including on mortgages, which should facilitate systematic implementation and monitoring.
Relative to the global industry average, Swedbank benefits from higher social standards in Sweden. On the other hand, like other large banks, it faces challenges regarding customer satisfaction, partly after the material reputational damage caused by the severity of its 2019 money laundering case. Indeed, Swedbank is still strengthening its risk culture and governance following the controversy. Although its new board and executive management have invested heavily to be among the leaders in combating financial crime, we believe these measures will take time to permeate across the entire organization.
Swedbank’s robust preparedness reflects its excellent awareness of potential long-term disruptions, including digitalization and climate change, balanced by the short track record of its board.
What Is An ESG Evaluation?
S&P Global Ratings’ ESG evaluation is a cross-sector, relative analysis of an entity’s capacity to continue to operate successfully. It is grounded in how ESG factors could affect stakeholders, potentially leading to a material direct or indirect financial impact on the entity.
Our definition of stakeholders for a particular entity goes beyond shareholders to include employees, the local community, government, regulators, customers, lenders, borrowers, policyholders, voters, members, and suppliers. A high ESG evaluation score indicates an entity is relatively less prone to experiencing material ESG-related events, and is relatively better positioned to capitalize on ESG-related growth opportunities than entities with lower ESG evaluation scores.
First, we establish an ESG profile for a given entity, which assesses the exposure of the entity’s operations to observable ESG risks and opportunities, and how the entity is mitigating these risks and capitalizing on these opportunities.
Second, we assess the entity’s long-term preparedness, namely its capacity to anticipate and adapt to a variety of long-term plausible disruptions.
S&P Global Ratings currently evaluates over 70 entities across the globe; they have an average score of 67. Since the first ESG evaluation, published in June 2019, we have finalized ESG Evaluations across 21 sectors globally. By region, the highest average score is 72, for companies headquartered in Europe.
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Artificial Intelligence
Data Center Chip Market Size was Valued at USD 11.7 Billion in 2022 and is Expected to Reach USD 45.3 Billion by 2032 at a CAGR of 14.6% | Valuates Reports
BANGALORE, India, July 26, 2024 /PRNewswire/ — Data Center Chip Market By Chip Type (GPU, ASIC, FPGA, CPU, Others), By Data Center Size (Small and Medium Size, Large Size), By Industry Verticals (BFSI, Manufacturing, Government, IT and Telecom, Retail, Transportation, Energy and Utilities, Others): Global Opportunity Analysis and Industry Forecast, 2023-2032.
The Data Center Chip Market was valued at USD 11.7 Billion in 2022, and is estimated to reach USD 45.3 Billion by 2032, growing at a CAGR of 14.6% from 2023 to 2032.
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Major Factors Driving the Growth of Data Center Chip Market
Because of the growing need for data processing and storage solutions brought about by the quick development of cloud computing, artificial intelligence, and big data analytics, the data center chip market is expanding significantly. High-performance chips are necessary for data centers to process massive volumes of data quickly and efficiently. As a result, advances in chip technology, including CPUs, GPUs, and specialist AI processors, have been made. The need for more resilient and scalable data center infrastructure is fueled in part by the expansion of digital services and Internet of Things (IoT) devices. The market is expanding due to key areas including Asia-Pacific, with its investments in technology and fast digital transformation, and North America, with its top tech businesses and vast data center networks.
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TRENDS INFLUENCING THE GROWTH OF THE DATA CENTER CHIP MARKET:
In data centers, Graphics Processing Units (GPUs) are essential for speeding up computing operations and data processing. They are perfect for managing workloads related to artificial intelligence (AI), machine learning, and large-scale data analytics because of their parallel processing capabilities. The need for GPUs in data centers is growing as these technologies become increasingly essential to corporate operations. Businesses are purchasing GPUs in order to increase the effectiveness of their data processing, lower latency, and boost overall performance. The need for data center chips is being driven by the increasing reliance on GPUs for sophisticated computing activities, which is considerably contributing to the market’s rise. This need is further increased by the growing use of AI and machine learning in a variety of sectors, which puts GPUs at the forefront of the data center semiconductor industry.
Compared to general-purpose chips, Application Specific Integrated Circuits (ASICs) provide better performance and efficiency since they are designed specifically for a given application. ASICs are extensively utilized in data centers for specific tasks including networking, data compression, and encryption. ASICs are becoming more and more common as a result of the growth of cloud computing, big data analytics, and blockchain technology, which has increased demand for high-performance, energy-efficient processors. Their capacity to provide tailored performance for certain applications aids data centers in better workload management, power conservation, and operating expense reduction. The market is expanding as a result of the increased preference for ASICs in data centers, which is fueling the need for specialized data center chips.
Large data centers are important users of data center chips; they are run by well-known IT firms and cloud service providers. To manage enormous volumes of data and provide a wide range of services, these facilities need a great deal of processing power and sophisticated computing skills. High-performance data center chips are becoming more and more necessary as a result of the growth of massive data centers and the rising demand for online streaming, cloud services, and digital transactions. These chips are necessary to ensure effective data management, processing, and storage, which helps big data centers fulfill the increasing expectations of its clientele. Large data center proliferation is anticipated to considerably boost the data center chip industry as the digital economy continues to grow.
Data centers are becoming more and more important to the Banking, Financial Services, and Insurance (BFSI) industry as a means of safely and effectively managing high transaction volumes, consumer data, and financial records. The need for sophisticated data center processors is being driven by the sector’s requirement for real-time data processing, high-performance computing, and strong security measures. BFSI organizations may improve their operational efficiency, guarantee data integrity, and deliver superior client services by utilizing data centers fitted with robust chips. The BFSI sector’s need for data center chips is being driven by the increasing use of online banking, digital banking, and financial analytics tools, all of which increase the requirement for sophisticated data center infrastructure.
The market for data center chips is significantly influenced by the cloud computing industry’s explosive growth. There is a growing need for scalable, effective, and high-performance data center infrastructure as more companies move their operations to the cloud. In order to handle enormous volumes of data, facilitate virtualization, and guarantee flawless service delivery, cloud service providers need sophisticated data center chips. Sturdy data center chips are becoming more and more necessary as cloud-based solutions become more and more popular. Benefits like cost savings, flexibility, and scalability are driving this trend. In places like North America and Europe, where cloud adoption rates are high and data center chip demand is rising rapidly, this tendency is especially significant.
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DATA CENTER CHIP MARKET SHARE
In 2022, North America gained a sizable portion of the market.
In 2022, the GPU made up the largest portion of the market share.
Throughout the projection period, large data centers are expected to gain a significant portion.
The BFSI market is anticipated to be one of the most profitable markets.
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Key Companies:
Advanced Micro Devices IncTaiwan Semiconductor Manufacturing Company LimitedBroadcomHuawei Technologies Co LtdIntel CorporationNVidia CorporationSamsung Electronics Co LtdQualcomm Technologies IncGlobalFoundriesARM LIMITED (SOFTBANK GROUP CORP.)Purchase Chapters @ https://reports.valuates.com/request/chaptercost/ALLI-Auto-2B326/Data_Center_Chip_Market
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DISCOVER MORE INSIGHTS: EXPLORE SIMILAR REPORTS!
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Artificial Intelligence
Industry 4.0 Market to Surpass USD 513.89 Billion by 2031 with Automation Surge | SkyQuest Technology
WESTFORD, Mass., July 26, 2024 /PRNewswire/ — According to SkyQuest, the global Industry 4.0 Market size was valued at USD 133.05 billion in 2022 and is poised to grow from USD 154.6 billion in 2023 to USD 513.89 billion by 2031, growing at a CAGR of 16.2% during the forecast period (2024-2031).
Industry 4.0 or the fourth industrial revolution emphasizes the use of automation and interconnectivity. Employment of advanced technologies such as artificial intelligence, machine learning, robotics, and connected devices to improve the productivity and efficiency of industries. Rapid digitization and advancements in technology are forecasted to bolster the Industry 4.0 market growth over the coming years. The global Industry 4.0 market is segmented into technology, industry vertical, and region.
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Industry 4.0 Market Overview:
Report Coverage
Details
Market Revenue in 2023
$ 154.6 billion
Estimated Value by 2031
$ 513.89 billion
Growth Rate
Poised to grow at a CAGR of 16.2%
Forecast Period
2024–2031
Forecast Units
Value (USD Billion)
Report Coverage
Revenue Forecast, Competitive Landscape, Growth Factors, and Trends
Segments Covered
Technology, Industry and Region
Geographies Covered
North America, Europe, Asia Pacific, Latin America, and Middle East and Africa.
Report Highlights
Internet of Things (IoT) technology takes centerstage for Industry 4.0 adoption
Key Market Opportunities
Adoption of smart manufacturing and additive manufacturing practices
Key Market Drivers
Rising demand for automation across all industry verticals
Segments covered in Industry 4.0 Market are as follows:
TechnologyRobots (Traditional Industrial Robots {Articulated robots, Cartesian Robots, Selective Compliance Assembly Robot Arm (SCARA), Cylindrical Robots, Others}, Collaborative Robots), Blockchain in Manufacturing, Industrial Sensors (Level Sensors, Temperature Sensors, Flow Sensors, Position Sensors, Pressure Sensors, Force Sensors, Humidity & Moisture Sensors, Gas Sensors), Industrial 3D Printing, Machine Vision (Camera {Digital Camera, Smart Camera}, Frame Grabbers, Optics, and LED Lighting, Processor and Software), HMI (Offering {Hardware [Basic HMI, Advanced Panel-based HMI, Advanced PC-based HMI, Others], Software [On-premises HMI, Cloud-based HMI], Services}), Configuration ({Embedded HMI, Standalone HMI}, Technology {Motion HMI, Bionic HMI, Tactile HMI, Acoustic HMI}, End-user Industry {Process industries [Oil & Gas, Food & beverages, Pharmaceuticals, Chemicals, Energy & power, Metals & mining, Water & wastewater, Others], Discrete industry [Automotive, Aerospace & defense, Packaging, Medical devices, Semiconductor & electronics, Others]}), AI In Manufacturing (Offering {Hardware [Processor MPU, GPU, FPGA, ASIC, Memory, Network], Software [AI solutions- | On-premises, Cloud |, AI platform- | Machine learning framework, Application program interface |], Services [Deployment & integration, Support & maintenance]}, Technology {Machine learning [Deep learning, Supervised learning, Reinforcement learning, Reinforcement learning, Others], Natural language processing [Context-aware computing, Computer vision]}, Application {Predictive maintenance and machinery inspection, Material movement, Production planning, Field services, Quality control, Cybersecurity, Industrial robots, Reclamation}, Digital Twin {Technology [Internet of Things (IOT), Blockchain, Artificial intelligence & machine learning, Artificial intelligence & machine learning, Big data analytics, 5G], Usage Type [Product digital twin, Process digital twin, System digital twin], Application [Product design & development, Performance monitoring, Predictive maintenance, Inventory management, Business optimization, Others]}, Automated Guided Vehicles (AGV) {Type [Tow vehicles, Unit load carriers, Pallet trucks, Assembly line vehicles, Forklift trucks, Others], Navigation Technology [Laser guidance, Magnetic guidance, Inductive guidance, Optical tape guidance, Vision guidance, Others]}, Machine Condition Monitoring {Monitoring Technique [Vibration monitoring, Embedded systems, Vibration analyzers and meters, Thermography, Oil analysis, Corrosion monitoring, Ultrasound emission, Motor current analysis], Offering [Hardware – Vibration sensors, Accelerometers, Tachometers, Infrared sensors, Spectrometers, Ultrasound detectors, Spectrum analyzers, Corrosion probes], Software [Data integration, Diagnostic reporting, Order tracking analysis, Parameter calculation], Deployment Type [On-premises deployment, Cloud deployment], Monitoring Process [Online condition monitoring, Portable condition monitoring]})IndustryManufacturing, Automotive, Energy, Medical, Semiconductor & Electronics, Food & Beverage, Oil & Gas, Aerospace, Metals & Mining, Chemicals, and OthersRequest Free Customization of this report:
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Internet of Things (IoT) Technology to Remain Indispensable for Industry 4.0
Internet of Things (IoT) remains the most crucial technology in global Industry 4.0 market growth owing to its role in interconnectivity and automation across different verticals. Advancements in connectivity technologies and rising use of automation in different industry verticals are also estimated to help this sub-segment gain an impressive market share. Surging demand for predictive maintenance will also boost the adoption of IoT technology in the long run.
Advanced robotic technologies are also slated to gain traction in the Industry 4.0 market. Growing acceptance of robots and high investments in advancements of robotic technologies are also slated to create new opportunities for providers of advanced robotics in the Industry 4.0 market. The low margin of error and the immense scope of automation are key benefits of robotics that help this sub-segment flourish.
Artificial intelligence (AI) will be another popular technology in the Industry 4.0 world going forward. Increasing demand for continuous monitoring, real-time analytics, and predictive maintenance are slated to help the demand for artificial intelligence in the future. The rising use of IoT devices will also boost the demand for cloud computing technology in the long run.
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Manufacturing Vertical to Spearhead Industry 4.0 Market Development
The manufacturing vertical is estimated to be at the forefront when it comes to Industry 4.0 adoption. The surge in use of robotics, advanced technologies, and smart manufacturing practices sets the tone for Industry 4.0 in this industry vertical. High emphasis on improving manufacturing efficiency, reducing downtime, and maximizing profits are all contributing to the high market share of this sub-segment.
The automotive industry is another vertical where Industry 4.0 market players could invest to get good returns. The high adoption of advanced robotics and other smart manufacturing technologies to maximize production allows this sub-segment to become a crucial one for Industry 4.0 providers. The aerospace and defense industry vertical also shows a lot of promise for Industry 4.0 companies going forward. Growing demand for advanced manufacturing techniques and technologies to create complex aerospace components is helping Industry 4.0 market growth via this segment.
The oil & gas industry is also estimated to embrace Industry 4.0 trend with open hands as they try to improve their operations and promote better resource utilization. High demand for predictive maintenance to reduce downtime and the growing adoption of digital oilfield solutions are estimated to bolster Industry 4.0 market development in the long run.
To sum it up, the application scope for Industry 4.0 is endless as automation and digitization pick up pace around the world. High investments in development of IoT and AI technologies will create better opportunities for Industry 4.0 companies in the future. The manufacturing industry will remain the top revenue generating sub-segment and more opportunities for aerospace, automotive, and oil & gas verticals will be seen over the coming years.
Related Report:
Digital Twin Market
Cyber Security Market
Artificial Intelligence (AI) Market
Internet Of Things (IoT) Market
Machine Learning Market
About Us:
SkyQuest is an IP focused Research and Investment Bank and Accelerator of Technology and assets. We provide access to technologies, markets and finance across sectors viz. Life Sciences, CleanTech, AgriTech, NanoTech and Information & Communication Technology.
We work closely with innovators, inventors, innovation seekers, entrepreneurs, companies and investors alike in leveraging external sources of R&D. Moreover, we help them in optimizing the economic potential of their intellectual assets. Our experiences with innovation management and commercialization has expanded our reach across North America, Europe, ASEAN and Asia Pacific.
Contact: Mr. Jagraj SinghSkyQuest Technology1 Apache Way,Westford,Massachusetts 01886USA (+1) 351-333-4748Email: [email protected] Our Website: https://www.skyquestt.com/
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Artificial Intelligence
Generative AI Cybersecurity Market worth $40.1 billion by 2030 – Exclusive Report by MarketsandMarkets™
CHICAGO, July 26, 2024 /PRNewswire/ — The Generative AI cybersecurity Market is anticipated to experience substantial expansion, ascending from a value of USD 7.1 billion in 2024 to a substantial worth of USD 40.1 billion by the year 2030, according to a new report by MarketsandMarkets™. This growth trajectory reflects a robust compound annual growth rate (CAGR) of 33.4% over the forecast period.
Browse in-depth TOC on “Generative AI cybersecurity Market”
350 – Tables 60 – Figures450 – Pages
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Scope of the Report
Report Metrics
Details
Market size available for years
2019–2030
Base year considered
2023
Forecast period
2024–2030
Forecast units
USD (Million)
Segments Covered
Offering, Generative AI-based Cybersecurity, Cybersecurity for Generative AI, Security Type, End-user, and Region
Geographies covered
North America, Europe, Asia Pacific, Middle East & Africa, and Latin America
Companies covered
Microsoft (US), IBM (US), Google (US), SentinelOne (US), AWS (US), NVIDIA (US), Cisco (US), CrowdStrike (US), Fortinet (US), Zscaler (US), Trend Micro (Japan), Palo Alto Networks (US), BlackBerry (Canada), Darktrace (UK), F5 (US), Okta (US), Sangfor (China), SecurityScorecard (US), Sophos (UK), Broadcom (US), Trellix (US), Veracode (US), LexisNexis (US), Abnormal Security (US), Adversa AI (Israel), Aquasec (US), BigID (US), Checkmarx (US), Cohesity (US), Credo AI (US), Cybereason (US), DeepKeep (Israel), Elastic NV (US), Flashpoint (US), Lakera (US), MOSTLY AI (Austria), Recorded Future (US), Secureframe (US), Skyflow (US), SlashNext (US), Snyk (US), Tenable (US), TrojAI (Canada), VirusTotal (Spain), XenonStack (UAE), and Zerofox (US).
This dramatic surge is being fueled by a number of causes. The primary growth driver is the enhancement of existing cybersecurity tools through generative AI algorithms by improving anomaly detection, automating threat hunting and penetration testing, and providing complex simulations for security testing purposes. These techniques enable various cyber-attack scenarios that can be simulated using the Generative Adversarial Networks (GANs), thus enabling the development of better preparedness and response strategies. On the other hand, it requires special cyber security tools to protect generative AI workloads against unique vulnerabilities such as adversarial attacks, model inversions and LLM poisoning. These tools include differential privacy and secure multi-party computation that are integrated into AI systems for training and deployment data protection purposes.
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Generative AI apps security segment will account for largest market share during the forecast period.
The cybersecurity landscape is rapidly changing for generative AI apps, which are already making their way into chatbots, content creation tools like word processors, and personalized recommendation systems. According to McAfee, 55% of these programs have had security breaches. This highlights the dire need for stronger protective measures from unauthorized access. Several generative AI applications that use adversarial techniques to force the desired reaction out of intelligent machines.
Therefore, there is a pressing demand in the number of developers who ensure that such machines are made more robust through techniques like adversarially trained models and resistant architectures. Finally, the usage of secure enclaves plus hardware-based security measures is growing off late, mainly aimed at safeguarding vulnerable AI computations from being tampered with. For instance, OpenAI has very strict security rules meant to protect GPT models thereby ensuring data integrity and user privacy.
By end-user, government & defense sector is poised to account for larger market share in 2024.
Government as well as defense industries are increasingly resorting to generative AI for cyber security purposes due to the urgency of protecting sensitive information and national security. According to a recent CSIS report, AI is being integrated into the cybersecurity framework of 43% of government agencies which resultantly improves their ability to identify and counter threats. As an example, the United States Department of Defense has started using artificial intelligence (AI) based security solutions backed by generative AI that can create fictitious cyber-attacks, thereby providing them with enhanced preparedness against advanced types of threats.
This technology also helps these sectors handle and analyze large volumes of data more effectively, giving valuable insights that will enable them prevent or mitigate cyber threats. This trend demonstrates an increasing reliance on generative AI in fortifying cyber security measures so as to ensure that critical infrastructure and sensitive data remain secure in today’s intricate digital landscape.
By region, North America to hold the largest share by market value in 2024.
In 2024, North America will be the leading region based on market share due to its excellent technology infrastructure, substantial investments in AI-enabled cybersecurity and the presence of key players. Major cyber security research universities and tech companies such as Google, AWS, CrowdStrike, SentinelOne and IBM are present in this area, pushing them on the forefront of potent risk management technologies and generative AI tools for threat detection. For example, IBM’s security platform powered by AI has improved detection rates for threats up by 40%, thus proving the relevance of AI technology to enhancing cybersecurity.
Moreover, legislative instruments such as Cybersecurity Information Sharing Act (CISA) are being put in place to promote advanced cybersecurity technologies. As internet attacks continue getting more complicated, North American enterprises prefer generative artificial intelligence (AI), so as to enhance their safety measures pertaining to personal data and digital infrastructure.
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Top Key Companies in Generative AI cybersecurity Market:
The major players in the generative AI cybersecurity market include Palo Alto Networks (US), AWS (US), CrowdStrike (US), SentinelOne (US), and Google (US), along with SMEs and startups such as MOSTLY AI (Austria), XenonStack (UAE), BigID (US), Abnormal Security (US), and Adversa AI (Israel).
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