The Asia Pacific Anomaly Detection Market should witness market growth of 16.8% CAGR during the forecast period (2023-2030).
The market is anticipated to be driven by the growing number of connected devices in the government, healthcare, manufacturing, banking, and financial sectors, as well as in IT & telecom and manufacturing. The number of linked IoT devices was estimated to increase to over 20 billion by 2020, according to the Digitalization and Energy report published by the International Energy Agency in 2017.
The manufacturing industry has been the target of cyberattacks the most. Ransomware attacks on manufacturing plants more than doubled in 2022, with possible systemic effects on supply deliveries. Cyberattacks may disrupt supply chains and enterprises, negating the benefits of digitization and leading to losses in revenue and productivity that harm reputations.
Since it notifies human monitors of any departures from the standard, anomaly detection systems are growing in Favor. Machine learning technology has allowed the BFSI sector to interface with various financial institutions and activities via anomaly detection tools. In order to decrease reliance on human labour and increase processing effectiveness, this industry is quickly implementing IT solutions. The International Monetary Fund reports that 56% of central banks or regulatory agencies lack a national cyber strategy for the financial industry. A specific technology risk management or cybersecurity regulation is absent in 42% of cases, and in 68.3% of cases, there is no specialized risk unit within the department of supervision. Consequently, these tools have grown in Favor as even when no statutory law is present, they can aid in bolstering the security of financial institutions.
The use of new technologies, including big data and analytics, augmented reality, remote asset management, the industrial Internet of Things (IoT), cloud computing, cyber security, and the rapid development of IT infrastructure, are propelling the market's expansion. Governments in the Asia Pacific are enhancing their statistical skills, providing more e-government services, and creating strategies for the development of digital economy.
Many of these advancements have been made possible by cloud computing technologies, which have provided governments with numerous benefits, including reducing the cost of replacing out-of-date technology like on-site servers. A 60% cost decrease was recorded by Singapore's Land Transport Authority as a result of the migration from an on-premise system to the cloud. Fintech is also expanding in the nation. Additionally, the telecommunications industry is expanding in this region. India will overtake China as the second-largest telecom sector in the world as its subscriber base reached 1,170.38 million in December 2022. As a result, the adoption of cloud-based services by the region's various industries is boosting the need for anomaly detection. This will propel the growth of the market in the years to come.
The China market dominated the Asia Pacific Anomaly Detection Market by Country in 2022 and would continue to be a dominant market till 2030; thereby, achieving a market value of $1,134.7 million by 2030. The Japan market is showcasing a CAGR of 16.1% during (2023-2030). Additionally, The India market would register a CAGR of 17.6% during (2023-2030).
Based on Deployment, the market is segmented into On-premise, and Cloud. Based on Technology, the market is segmented into Big Data Analytics, Business Intelligence & Data Mining, and Machine Learning & Artificial Intelligence. Based on Component, the market is segmented into Solution (Network Behavior, and User Behavior), and Services. Based on End-Use, the market is segmented into BFSI, Government & Defense, IT & Telecom, Healthcare, Manufacturing, Retail, and Others. Based on countries, the market is segmented into China, Japan, India, South Korea, Singapore, Malaysia, and Rest of Asia Pacific.
The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Amazon Web Services, Inc., Broadcom, Inc., Cisco Systems, Inc., Dell Technologies, Inc., Dynatrace, Inc., Happiest Minds Technologies Limited, Hewlett Packard Enterprise Company, IBM Corporation, Microsoft Corporation and SAS Institute, Inc.
The market is anticipated to be driven by the growing number of connected devices in the government, healthcare, manufacturing, banking, and financial sectors, as well as in IT & telecom and manufacturing. The number of linked IoT devices was estimated to increase to over 20 billion by 2020, according to the Digitalization and Energy report published by the International Energy Agency in 2017.
The manufacturing industry has been the target of cyberattacks the most. Ransomware attacks on manufacturing plants more than doubled in 2022, with possible systemic effects on supply deliveries. Cyberattacks may disrupt supply chains and enterprises, negating the benefits of digitization and leading to losses in revenue and productivity that harm reputations.
Since it notifies human monitors of any departures from the standard, anomaly detection systems are growing in Favor. Machine learning technology has allowed the BFSI sector to interface with various financial institutions and activities via anomaly detection tools. In order to decrease reliance on human labour and increase processing effectiveness, this industry is quickly implementing IT solutions. The International Monetary Fund reports that 56% of central banks or regulatory agencies lack a national cyber strategy for the financial industry. A specific technology risk management or cybersecurity regulation is absent in 42% of cases, and in 68.3% of cases, there is no specialized risk unit within the department of supervision. Consequently, these tools have grown in Favor as even when no statutory law is present, they can aid in bolstering the security of financial institutions.
The use of new technologies, including big data and analytics, augmented reality, remote asset management, the industrial Internet of Things (IoT), cloud computing, cyber security, and the rapid development of IT infrastructure, are propelling the market's expansion. Governments in the Asia Pacific are enhancing their statistical skills, providing more e-government services, and creating strategies for the development of digital economy.
Many of these advancements have been made possible by cloud computing technologies, which have provided governments with numerous benefits, including reducing the cost of replacing out-of-date technology like on-site servers. A 60% cost decrease was recorded by Singapore's Land Transport Authority as a result of the migration from an on-premise system to the cloud. Fintech is also expanding in the nation. Additionally, the telecommunications industry is expanding in this region. India will overtake China as the second-largest telecom sector in the world as its subscriber base reached 1,170.38 million in December 2022. As a result, the adoption of cloud-based services by the region's various industries is boosting the need for anomaly detection. This will propel the growth of the market in the years to come.
The China market dominated the Asia Pacific Anomaly Detection Market by Country in 2022 and would continue to be a dominant market till 2030; thereby, achieving a market value of $1,134.7 million by 2030. The Japan market is showcasing a CAGR of 16.1% during (2023-2030). Additionally, The India market would register a CAGR of 17.6% during (2023-2030).
Based on Deployment, the market is segmented into On-premise, and Cloud. Based on Technology, the market is segmented into Big Data Analytics, Business Intelligence & Data Mining, and Machine Learning & Artificial Intelligence. Based on Component, the market is segmented into Solution (Network Behavior, and User Behavior), and Services. Based on End-Use, the market is segmented into BFSI, Government & Defense, IT & Telecom, Healthcare, Manufacturing, Retail, and Others. Based on countries, the market is segmented into China, Japan, India, South Korea, Singapore, Malaysia, and Rest of Asia Pacific.
The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include Amazon Web Services, Inc., Broadcom, Inc., Cisco Systems, Inc., Dell Technologies, Inc., Dynatrace, Inc., Happiest Minds Technologies Limited, Hewlett Packard Enterprise Company, IBM Corporation, Microsoft Corporation and SAS Institute, Inc.
Scope of the Study
By Deployment
- On-premise
- Cloud
By Technology
- Big Data Analytics
- Business Intelligence & Data Mining
- Machine Learning & Artificial Intelligence
By Component
- Solution
- Network Behavior
- User Behavior
- Services
By End-Use
- BFSI
- Government & Defense
- IT & Telecom
- Healthcare
- Manufacturing
- Retail
- Others
By Country
- China
- Japan
- India
- South Korea
- Singapore
- Malaysia
- Rest of Asia Pacific
Key Market Players
List of Companies Profiled in the Report:
- Amazon Web Services, Inc.
- Broadcom, Inc.
- Cisco Systems, Inc.
- Dell Technologies, Inc.
- Dynatrace, Inc.
- Happiest Minds Technologies Limited
- Hewlett Packard Enterprise Company
- IBM Corporation
- Microsoft Corporation
- SAS Institute, Inc.
Unique Offerings
- Exhaustive coverage
- The highest number of Market tables and figures
- Subscription-based model available
- Guaranteed best price
- Assured post sales research support with 10% customization free
Table of Contents
Chapter 1. Market Scope & Methodology
Chapter 2. Market At a Glance
Chapter 3. Market Overview
Chapter 4. Competition Analysis - Global
Chapter 5. Asia Pacific Anomaly Detection Market by Deployment
Chapter 6. Asia Pacific Anomaly Detection Market by Technology
Chapter 7. Asia Pacific Anomaly Detection Market by Component
Chapter 8. Asia Pacific Anomaly Detection Market by End-use
Chapter 9. Asia Pacific Anomaly Detection Market by Country
Chapter 10. Company Profiles
Companies Mentioned
- Amazon Web Services, Inc.
- Broadcom, Inc.
- Cisco Systems, Inc.
- Dell Technologies, Inc.
- Dynatrace, Inc.
- Happiest Minds Technologies Limited
- Hewlett Packard Enterprise Company
- IBM Corporation
- Microsoft Corporation
- SAS Institute, Inc.
Methodology
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