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人工智慧風險管理市場規模、佔有率和成長分析（按組件、部署模式、風險、應用、最終用途和地區分類）—產業預測，2026-2033年

市場調查報告書

商品編碼

1895850

人工智慧風險管理市場規模、佔有率和成長分析（按組件、部署模式、風險、應用、最終用途和地區分類）—產業預測，2026-2033年

AI For Risk Management Market Size, Share, and Growth Analysis, By Component (Software, Services), By Deployment Model (On-Premises, Cloud), By Risk, By Application, By End Use, By Region - Industry Forecast 2026-2033

出版日期: 2025年12月15日 | 出版商:

SkyQuest | 英文 257 Pages | 商品交期: 3-5個工作天內

價格

簡介目錄

預計到 2024 年，全球人工智慧風險管理市場規模將達到 58.9 億美元，到 2025 年將成長至 65.4 億美元，到 2033 年將成長至 151.9 億美元，在預測期（2026-2033 年）內複合年成長率為 11.1%。

人工智慧在風險管理領域的應用正日益普及，其應用範圍涵蓋構思、資料收集、模型開發和監控等多個面向。人工智慧透過識別監管風險和聲譽風險、進行符合組織價值觀的評估以及指導資料收集和處理，從而增強風險管理能力。數據選擇對於提高結果品質至關重要，以往適用於人工智慧分析的風險管理方法通常被用作參考。人工智慧利用機器學習處理大量資訊並進行即時預測，從而促進威脅分析、詐欺偵測和有效的資料分類。然而，整合專業的人工智慧服務也面臨許多挑戰，包括高成本以及對資料隱私和安全的重大擔憂。對於基於雲端的資料管理而言，加密和混淆等強大的安全措施至關重要。

全球人工智慧風險管理市場促進因素

推動全球人工智慧風險管理市場發展的關鍵因素之一是威脅情報資料的利用。威脅情報資料能夠洞察潛在攻擊者的來源、入侵徵兆以及與雲端帳戶使用和各種雲端服務相關的行為模式。借助機器學習技術，企業可以有效地聚合和分析各種威脅情報源，從而更好地了解和應對風險。這個過程也有助於開發評估潛在安全事件發生機率和可預測性的模型，進一步加強風險管理策略，並在日益複雜的數位環境中提升整體網路安全韌性。

限制全球人工智慧風險管理市場發展的因素

全球風險管理人工智慧市場面臨諸多限制因素，尤其是在新興企業和新興產業。即使雲端原生解決方案可用，處理大量資料的高昂成本也可能使部署專業人工智慧服務變得難以負擔。此外，這些機構還必須應對與資料隱私和保護相關的複雜挑戰，這構成了採用人工智慧和機器學習技術的主要障礙。這些財務和監管方面的障礙可能會阻礙新進入者充分利用人工智慧解決方案，從而抑制風險管理領域的整體市場成長和創新。

人工智慧風險管理市場的全球趨勢

由於先進技術（例如區塊鏈）的融合，全球風險管理人工智慧市場正經歷顯著成長。區塊鏈增強了資料安全性和交易追蹤能力，使組織能夠有效監控和管理風險，同時確保合規性和透明度。同時，風險管理中的倫理考量也日益受到重視。隨著組織採用人工智慧解決方案，解決潛在的偏見和倫理問題至關重要。這種對穩健的技術框架和倫理管治的雙重關注，不僅提高了風險管理的有效性，也促進了信任和課責，為企業更有效地應對複雜的風險環境奠定了基礎。

Alteryx（US）
Apparity（US）
Axioma（US）
Databricks（US）
DataRobot（US）
Empowered Systems（US）
FICO（US）
Friss（Netherlands）
Google（US）
IBM（US）
Kx Systems（US）
MathWorks（US）
Microsoft（US）
Quantiphi（US）
RiskLens（US）
SAS（US）
TIBCO Software（US）
ValidMind（US）
Yields.io（Belgium）
Zest AI（US）

結論與建議

簡介目錄

Product Code: SQMIG45F2059

Global AI For Risk Management Market size was valued at USD 5.89 Billion in 2024 and is poised to grow from USD 6.54 Billion in 2025 to USD 15.19 Billion by 2033, growing at a CAGR of 11.1% during the forecast period (2026-2033).

The adoption of AI for Risk Management is gaining momentum due to its diverse applications, including ideation, data sourcing, model development, and monitoring. AI enhances risk management by detecting regulatory and reputational risks, conducting assessments aligned with organizational values, and guiding data collection and processing. The choice of data is crucial for improving outcome quality, often informed by historical risk management practices suitable for AI analysis. AI facilitates threat analysis, fraud detection, and effective data classification, leveraging machine learning to process vast amounts of information for real-time predictions. However, the integration of specialized AI services poses challenges, including high costs and significant concerns around data privacy and protection, necessitating robust security measures such as encryption and obfuscation for cloud-based data management.

Top-down and bottom-up approaches were used to estimate and validate the size of the Global AI For Risk Management market and to estimate the size of various other dependent submarkets. The research methodology used to estimate the market size includes the following details: The key players in the market were identified through secondary research, and their market shares in the respective regions were determined through primary and secondary research. This entire procedure includes the study of the annual and financial reports of the top market players and extensive interviews for key insights from industry leaders such as CEOs, VPs, directors, and marketing executives. All percentage shares split, and breakdowns were determined using secondary sources and verified through Primary sources. All possible parameters that affect the markets covered in this research study have been accounted for, viewed in extensive detail, verified through primary research, and analyzed to get the final quantitative and qualitative data.

Global AI For Risk Management Market Segments Analysis

Global AI For Risk Management Market is segmented by component, deployment model, risk, application, end use and region. Based on component, the market is segmented into software and services. Based on deployment model, the market is segmented into on-premises and cloud. Based on risk, the market is segmented into model risk, operational risk, compliance risk, reputational risk and strategic risk. Based on application, the market is segmented into credit risk management, fraud detection and prevention, algorithmic trading, predictive maintenance and others. Based on end use, the market is segmented into BFSI, IT & telecom, healthcare, automotive, retail and e-commerce, manufacturing, government and defense and others. Based on region, the market is segmented into North America, Europe, Asia Pacific, Latin America and Middle East & Africa.

Driver of the Global AI For Risk Management Market

A key element driving the Global AI for Risk Management market is the utilization of threat intelligence data, which offers insights into potential attacker origins, indicators of compromise, and behavioral patterns associated with cloud account usage and various cloud services. By employing machine learning techniques, organizations can effectively aggregate and analyze extensive threat intelligence feeds, allowing for enhanced understanding and response to risks. This processing also supports the development of models that assess the likelihood and predictability of potential security incidents, further strengthening risk management strategies and improving overall cybersecurity resilience in an increasingly complex digital landscape.

Restraints in the Global AI For Risk Management Market

The Global AI for Risk Management market faces significant restraints, particularly for startups and emerging industries. Implementing specialized AI services can be prohibitively expensive, even with the availability of cloud-native solutions, as the processing of large volumes of data incurs substantial costs. Additionally, these entities must navigate the complexities associated with data privacy and protection, which represent major challenges in the deployment of AI and machine learning technologies. These financial and regulatory hurdles can deter new entrants from fully embracing AI solutions, potentially hindering overall market growth and innovation in the risk management sector.

Market Trends of the Global AI For Risk Management Market

The Global AI for Risk Management market is witnessing significant growth driven by the integration of advanced technologies like blockchain, which offers enhanced data security and transaction tracking capabilities. This trend allows organizations to effectively monitor and manage risks while ensuring compliance and transparency. Concurrently, there is a heightened emphasis on ethical considerations in risk management. As organizations increasingly adopt AI solutions, addressing potential biases and ethical implications becomes crucial. This dual focus on robust technological frameworks and ethical governance not only enhances risk management efficacy but also fosters trust and accountability, positioning companies to navigate complex risk landscapes more effectively.

Introduction

Objectives of the Study
Scope of the Report
Definitions

Research Methodology

Information Procurement
Secondary & Primary Data Methods
Market Size Estimation
Market Assumptions & Limitations

Executive Summary

Global Market Outlook
Supply & Demand Trend Analysis
Segmental Opportunity Analysis

Market Dynamics & Outlook

Market Overview
Market Size
Market Dynamics
- Drivers & Opportunities
- Restraints & Challenges
Porters Analysis
- Competitive rivalry
- Threat of substitute
- Bargaining power of buyers
- Threat of new entrants
- Bargaining power of suppliers

Key Market Insights

Key Success Factors
Degree of Competition
Top Investment Pockets
Market Ecosystem
Market Attractiveness Index, 2025
PESTEL Analysis
Macro-Economic Indicators
Value Chain Analysis
Pricing Analysis
Technology Analysis
Regulatory Analysis
Case Study Analysis
Patent Analysis

Global AI For Risk Management Market Size by Component & CAGR (2026-2033)

Market Overview
Software
Services
- Professional
- Managed

Global AI For Risk Management Market Size by Deployment Model & CAGR (2026-2033)

Market Overview
On-Premises
Cloud

Global AI For Risk Management Market Size by Risk & CAGR (2026-2033)

Market Overview
Model Risk
Operational Risk
Compliance Risk
Reputational Risk
Strategic Risk

Global AI For Risk Management Market Size by Application & CAGR (2026-2033)

Market Overview
Credit Risk Management
Fraud Detection and Prevention
Algorithmic Trading
Predictive Maintenance
Others

Global AI For Risk Management Market Size by End Use & CAGR (2026-2033)

Market Overview
BFSI
IT & Telecom
Healthcare
Automotive
Retail and E-Commerce
Manufacturing
Government and Defense
Others

Global AI For Risk Management Market Size & CAGR (2026-2033)

North America (Component, Deployment Model, Risk, Application, End Use)
- US
- Canada
Europe (Component, Deployment Model, Risk, Application, End Use)
- Germany
- Spain
- France
- UK
- Italy
- Rest of Europe
Asia Pacific (Component, Deployment Model, Risk, Application, End Use)
- China
- India
- Japan
- South Korea
- Rest of Asia-Pacific
Latin America (Component, Deployment Model, Risk, Application, End Use)
- Brazil
- Rest of Latin America
Middle East & Africa (Component, Deployment Model, Risk, Application, End Use)
- GCC Countries
- South Africa
- Rest of Middle East & Africa

Competitive Intelligence

Top 5 Player Comparison
Market Positioning of Key Players, 2025
Strategies Adopted by Key Market Players
Recent Developments in the Market
Company Market Share Analysis, 2025
Company Profiles of All Key Players
- Company Details
- Product Portfolio Analysis
- Company's Segmental Share Analysis
- Revenue Y-O-Y Comparison (2023-2025)

Key Company Profiles

Alteryx (US)
- Company Overview
- Business Segment Overview
- Financial Updates
- Key Developments
Apparity (US)
- Company Overview
- Business Segment Overview
- Financial Updates
- Key Developments
Axioma (US)
- Company Overview
- Business Segment Overview
- Financial Updates
- Key Developments
Databricks (US)
- Company Overview
- Business Segment Overview
- Financial Updates
- Key Developments
DataRobot (US)
- Company Overview
- Business Segment Overview
- Financial Updates
- Key Developments
Empowered Systems (US)
- Company Overview
- Business Segment Overview
- Financial Updates
- Key Developments
FICO (US)
- Company Overview
- Business Segment Overview
- Financial Updates
- Key Developments
Friss (Netherlands)
- Company Overview
- Business Segment Overview
- Financial Updates
- Key Developments
Google (US)
- Company Overview
- Business Segment Overview
- Financial Updates
- Key Developments
IBM (US)
- Company Overview
- Business Segment Overview
- Financial Updates
- Key Developments
Kx Systems (US)
- Company Overview
- Business Segment Overview
- Financial Updates
- Key Developments
MathWorks (US)
- Company Overview
- Business Segment Overview
- Financial Updates
- Key Developments
Microsoft (US)
- Company Overview
- Business Segment Overview
- Financial Updates
- Key Developments
Quantiphi (US)
- Company Overview
- Business Segment Overview
- Financial Updates
- Key Developments
RiskLens (US)
- Company Overview
- Business Segment Overview
- Financial Updates
- Key Developments
SAS (US)
- Company Overview
- Business Segment Overview
- Financial Updates
- Key Developments
TIBCO Software (US)
- Company Overview
- Business Segment Overview
- Financial Updates
- Key Developments
ValidMind (US)
- Company Overview
- Business Segment Overview
- Financial Updates
- Key Developments
Yields.io (Belgium)
- Company Overview
- Business Segment Overview
- Financial Updates
- Key Developments
Zest AI (US)
- Company Overview
- Business Segment Overview
- Financial Updates
- Key Developments