AI In Fraud Detection Market Size 2025-2029
The ai in fraud detection market size is forecast to increase by USD 26.5 billion, at a CAGR of 21.6% between 2024 and 2029.
The global AI in fraud detection market is shaped by the escalating sophistication of criminal activities, where AI itself is used to create dynamic cyber threats. This compels organizations to adopt a symmetric, data-driven defense, making AI and machine learning in business essential. The emergence of generative AI represents a dual-edged sword, as it is weaponized by malicious actors for schemes like synthetic identity fraud while also driving the development of next-generation defensive AI systems. This technological arms race is fundamentally reshaping risk models and pushing organizations beyond legacy rule-based engines toward more adaptive defense mechanisms. This evolution highlights the importance of fraud detection and prevention across various industries.A key trend involves the use of generative adversarial networks to produce photorealistic faces for fake identities and voice-cloning AI for social engineering attacks, necessitating more advanced countermeasures. However, deploying these sophisticated systems is complicated by significant challenges related to data access and quality, including the scarcity of labeled fraud data and strict privacy regulations that hinder data aggregation. These constraints can limit the real-world effectiveness of AI models despite their potential. The need for high-quality data is paramount for both generative AI in e-commerce and AI in banking to ensure accurate and reliable outcomes in fraud management.
What will be the Size of the AI In Fraud Detection Market during the forecast period?
Explore in-depth regional segment analysis with market size data - historical 2019 - 2023 and forecasts 2025-2029 - in the full report.
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The landscape of fraud detection and prevention is continuously shaped by the application of AI and machine learning in business. The deployment of real-time fraud analysis and transaction monitoring systems is becoming standard practice, with organizations leveraging sophisticated risk scoring models to identify and mitigate threats. The focus is on developing a data-driven defense that can adapt to evolving fraudulent patterns, ensuring the security of digital transactions. AI in warehousing and other sectors is also seeing increased application of these principles.Core technological advancements center on the use of machine learning models and deep learning algorithms to process vast datasets. The integration of natural language processing and computer vision enables the analysis of unstructured data, while graph analytics helps in uncovering complex fraud networks. These technologies are crucial for effective payment fraud prevention and fraudulent transaction detection. Continuous innovation in these areas is essential for maintaining robust security postures in the artificial intelligence (AI) market in retail sector.The fight against identity fraud is intensifying, with a specific focus on combating synthetic identity fraud through advanced identity verification systems. AI-driven solutions are instrumental in this effort, providing the tools needed to authenticate users and protect against account takeovers. The development of more resilient systems is a key priority for organizations seeking to secure their digital platforms and maintain customer trust. The application of these systems is a core part of effective AI in fraud management.Advanced methodologies such as behavioral biometrics and liveness detection are being integrated into security frameworks to provide stronger authentication. These techniques analyze unique user behaviors and physical characteristics to prevent impersonation. The development of deepfake detection technologies is also a critical area of research, as it addresses the growing threat posed by AI-generated media. This is particularly relevant for AI in insurance claims processing to verify evidence.Ensuring compliance and ethical use of AI is a paramount concern, with a strong emphasis on model interpretability and the reduction of algorithmic bias. The implementation of explainable AI is critical for meeting regulatory requirements in areas like anti-money laundering and KYC processes, where transparency in automated decision-making is mandatory. The goal is to build trustworthy AI systems that are both effective and fair. This approach strengthens both AI in data quality and AI in accounting practices.
How is this AI In Fraud Detection Industry segmented?
The ai in fraud detection industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in "USD million" for the period 2025-2029, as well as historical data from 2019 - 2023 for the following segments.
- Component
- Technology
- Machine learning
- Deep learning
- NLP
- Others
- Application
- Payment fraud
- Anti-money laundering
- Identity fraud
- Insurance fraud
- Others
- Geography
- North America
- Europe
- UK
- Germany
- France
- Italy
- Spain
- The Netherlands
- APAC
- China
- India
- Japan
- South Korea
- Australia
- Indonesia
- Middle East and Africa
- South America
- Rest of World (ROW)
By Component Insights
The software segment is estimated to witness significant growth during the forecast period.
The software segment represents the core technological foundation of the market, comprising the platforms, applications, and algorithms organizations deploy to automate the identification and prevention of fraudulent activities. This segment, which accounts for over 60% of the market, is characterized by rapid innovation as vendors enhance offerings to combat evolving fraud tactics. A primary category is the end-to-end fraud detection platform, providing comprehensive tools for real-time transaction monitoring, risk scoring, and case management.
Another critical software type is the underlying AI and machine learning framework, which enables organizations to build and deploy custom fraud models. This approach is favored by large institutions requiring high degrees of model customization. A significant trend shaping the segment is the integration of advanced AI sub-disciplines like deep learning to analyze unstructured data and identify complex, non-linear patterns. The delivery model is also shifting toward cloud-based and SaaS deployments, offering lower upfront costs and easier implementation.
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The Software segment was valued at USD 6.4 billion in 2019 and showed a gradual increase during the forecast period.
Regional Analysis
North America is estimated to contribute 36.5% to the growth of the global market during the forecast period.Technavio’s analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.
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The North American market, comprising the United States and Canada, is the most mature and dominant region in the global landscape. This leadership is underpinned by a highly digitized economy, widespread adoption of advanced technologies, and a vast ecosystem of AI vendors and financial institutions. North America is projected to contribute about 36.5% of the market's incremental growth. Major banks, credit card companies, and insurance firms have been at the forefront of deploying AI-powered solutions to combat payment fraud and identity theft.
The region is home to a majority of the leading global AI and analytics companies, whose concentration of expertise and investment fosters continuous innovation. The sheer scale of fraud in North America is a powerful catalyst for market growth. The evolving regulatory environment, while fragmented, is also shaping the market, with rules on data usage directly impacting the development of AI models. This combination of factors ensures the region's continued leadership and innovation in AI-based fraud detection solutions.
Market Dynamics
Our researchers analyzed the data with 2024 as the base year, along with the key drivers, trends, and challenges. A holistic analysis of drivers will help companies refine their marketing strategies to gain a competitive advantage.
The global AI in fraud detection market is driven by the need for advanced security solutions. Financial institutions are deploying AI-powered real-time transaction monitoring to combat sophisticated threats, using machine learning for synthetic identity fraud and advanced deep learning models for deepfake detection. To meet regulations, firms leverage explainable AI for regulatory compliance. Furthermore, behavioral biometrics for continuous authentication and computer vision for identity document verification enhance user security. Specialized applications like NLP for insurance claims fraud analysis and graph analytics for detecting fraud rings are becoming standard. These powerful AI systems for anti-money laundering compliance are often bolstered by generative adversarial networks for data augmentation, creating more robust datasets and improving defense capabilities against evolving financial crimes.Effective proactive fraud detection defense mechanisms rely on a sophisticated mix of AI. This includes supervised learning for payment fraud classification and unsupervised learning for anomaly detection to uncover novel threats. A cornerstone of modern strategy is AI-driven customer risk profile building for dynamic security. The adoption of privacy-enhancing AI in fraud detection is crucial for maintaining trust, while a significant operational benefit is the deployment of AI models for reducing false positives. These systems enable real-time risk assessment in digital payments and are complemented by automated financial crime investigation tools. As the industry matures, focus is shifting toward mitigating algorithmic bias in fraud models and exploring the symbiotic integration of AI and blockchain.
What are the key market drivers leading to the rise in the adoption of AI In Fraud Detection Industry?
- The primary driver for the market is the escalating sophistication and proliferation of fraudulent activities, which are increasingly orchestrated using AI itself.
The escalating sophistication of fraudulent activities, increasingly orchestrated with AI, serves as a primary market driver. Legacy fraud prevention systems, which rely on static rules and historical pattern recognition, are becoming inadequate against the dynamic nature of modern cyber threats. Malicious actors now use generative AI and machine learning for attacks of unprecedented scale and complexity, including highly convincing phishing emails and synthetic identity fraud. This environment necessitates a symmetric defense, where organizations must fight AI with more advanced AI. This reactive yet necessary escalation in technological capability is a powerful market accelerant, with software applications for fraud detection seeing growth of over 15% in the last year alone.The accelerating global shift toward a digital-first economy is a foundational driver for the market. The massive volume, velocity, and variety of data from digital payments, e-commerce, and online banking are impossible to monitor effectively with manual processes. Each digital interaction represents a data point that must be analyzed for potential fraud indicators. The scale of this challenge requires AI and machine learning, which can process billions of events in real time to identify subtle correlations and anomalous patterns that are invisible to human analysts. This ability to automate and scale the defense mechanism directly addresses the big data challenge posed by modern commerce.
What are the market trends shaping the AI In Fraud Detection Industry?
- The global market is experiencing a significant shift due to the dual-edged nature of generative AI, which is being weaponized by fraudsters while simultaneously compelling the development of next-generation defensive systems.
The market is undergoing a paradigm shift driven by the proliferation of generative AI, which acts as a dual-edged sword. On one hand, it is weaponized by malicious actors to create fraud schemes of unprecedented scale and believability, including synthetic identity fraud using photorealistic faces generated by adversarial networks. On the other hand, it compels the development of next-generation defensive AI systems. This technological arms race is fundamentally reshaping risk models and forcing organizations to move beyond rule-based systems toward more adaptive, machine learning-driven defense mechanisms. This dynamic highlights the critical role of AI in fraud management and the growing importance of generative AI in banking and finance for both offensive and defensive strategies.A transformative trend is the increasing convergence of AI with other advanced technologies, notably blockchain and biometrics, creating a more resilient security architecture. The fusion of AI with blockchain is proving effective in combating financial crimes, as machine learning algorithms can analyze on-chain data to trace illicit fund flows and detect money laundering schemes. Simultaneously, the integration of AI with advanced biometrics is revolutionizing identity verification. Liveness detection and behavioral biometrics, which analyze subtle user interaction patterns, create a continuous and passive authentication layer that is extremely difficult for fraudsters to replicate. AI is central to applied AI in retail and e-commerce, where it enhances other security technologies to build a proactive, context-aware fraud prevention framework.
What challenges does the AI In Fraud Detection Industry face during its growth?
- A formidable challenge impeding market growth is the persistent issue of data scarcity and privacy constraints, which complicates the creation of high-quality training datasets for advanced AI models.
A formidable challenge is the persistent issue of data access and quality. The effectiveness of advanced machine learning models is directly proportional to the volume and quality of their training data. However, organizations face significant hurdles in assembling the necessary datasets. A major problem is the inherent scarcity of labeled fraud data, which constitutes a very small fraction of total transactions, leading to highly imbalanced datasets. This requires sophisticated techniques like synthetic data generation or advanced anomaly detection algorithms, which increase the complexity and cost of model development. The software component of these solutions accounts for over 60% of the market, reflecting the significant investment required in these complex systems.A significant challenge stems from the inherent complexity and opacity of many advanced machine learning models, often called the black box problem. While models like deep neural networks can achieve remarkable accuracy, their internal decision-making processes are often incomprehensible to human operators. This lack of interpretability poses a major hurdle in regulated industries, where clear explanations are legally required for adverse decisions like a flagged transaction. This creates a direct conflict between the most powerful predictive models and the regulatory imperative for transparency. The development and integration of robust explainable AI solutions are therefore becoming critical but remain a complex and evolving field.
Exclusive Customer Landscape
The ai in fraud detection market forecasting report includes the adoption lifecycle of the market, covering from the innovator’s stage to the laggard’s stage. It focuses on adoption rates in different regions based on penetration. Furthermore, the ai in fraud detection market report also includes key purchase criteria and drivers of price sensitivity to help companies evaluate and develop their market growth analysis strategies.
Customer Landscape
Key Companies & Market Insights
Companies are implementing various strategies, such as strategic alliances, ai in fraud detection market forecast, partnerships, mergers and acquisitions, geographical expansion, and product/service launches, to enhance their presence in the industry.
ACI Worldwide Inc. - The company provides a real-time fraud management solution that utilizes a combination of machine learning, predictive analytics, and expert rules. This offering is designed to effectively identify and prevent payment fraud across various transactional environments, helping organizations mitigate financial losses and secure their payment ecosystems.
The industry research and growth report includes detailed analyses of the competitive landscape of the market and information about key companies, including:
- ACI Worldwide Inc.
- Amazon Web Services Inc.
- BAE Systems Plc
- Consultadoria e Inovacao Tecnologica S.A.
- Fair Isaac Corp.
- Fiserv Inc.
- Google Cloud
- International Business Machines Corp.
- LexisNexis Risk Solutions.
- Microsoft Corp.
- Oracle Corp.
- RSA Security LLC
- SAS Institute Inc.
- Splunk Inc.
- SUBEX Ltd.
- Thales Group
- TransUnion
Qualitative and quantitative analysis of companies has been conducted to help clients understand the wider business environment as well as the strengths and weaknesses of key industry players. Data is qualitatively analyzed to categorize companies as pure play, category-focused, industry-focused, and diversified; it is quantitatively analyzed to categorize companies as dominant, leading, strong, tentative, and weak.
Recent Development and News in Ai In Fraud Detection Market
In April, 2024, Google Cloud announced new generative AI-powered security products at its Cloud Next conference, designed to assist security teams in summarizing threats, searching for malware, and analyzing suspicious files.In March, 2024, Microsoft introduced Copilot for Security, a generative AI assistant designed to help security professionals respond to threats, analyze signals, and assess risk exposure in minutes.In March, 2024, Feedzai enhanced its RiskOps Platform with generative AI tools aimed at simplifying the creation of fraud detection rules for analysts.In February, 2024, TransUnion launched its TruValidate Device Risk with Behavioral Analytics solution, which leverages behavioral biometric analysis to distinguish between legitimate customers and fraudsters.
Research Analyst Overview
The global AI in fraud detection market is shaped by the continuous integration of machine learning models and deep learning algorithms into risk management frameworks. Organizations deploy both supervised learning models and unsupervised learning techniques to advance anomaly detection and fraudulent transaction detection capabilities. This data-driven defense strengthens digital transaction security and payment fraud prevention through dynamic transaction monitoring and real-time fraud analysis. The refinement of risk scoring models is integral to improving compliance efficiency for anti-money laundering (AML) and KYC processes. These elements combine to form a multi-layered security architecture designed for adaptability and resilience against evolving financial crime tactics.As threats evolve to include synthetic identity fraud, the market is responding with sophisticated countermeasures. Advanced identity verification systems now incorporate behavioral biometrics, computer vision for liveness detection, and technologies for deepfake detection and spotting voice cloning AI, often developed via generative adversarial networks. Methods like graph analytics, natural language processing (NLP), and on-chain data analysis improve real-time transaction scoring and customer risk profiling. The industry also concentrates on false positive reduction and model interpretability through explainable AI (XAI) to manage algorithmic bias and adhere to data privacy regulations. This ongoing development of continuous authentication layers contributes to an expected sector expansion of approximately 22% annually.
Dive into Technavio’s robust research methodology, blending expert interviews, extensive data synthesis, and validated models for unparalleled AI In Fraud Detection Market insights. See full methodology.
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Market Scope
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Report Coverage
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Details
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Page number
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314
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Base year
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2024
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Historic period
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2019 - 2023 |
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Forecast period
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2025-2029
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Growth momentum & CAGR
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Accelerating at a CAGR of 21.6%
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Market growth 2024-2029
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USD 26.5 billion
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Market structure
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Fragmented
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YoY growth 2024-2029(%)
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19.5%
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Key countries
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US, Canada, Mexico, UK, Germany, France, Italy, Spain, The Netherlands, China, India, Japan, South Korea, Australia, Indonesia, UAE, Saudi Arabia, South Africa, Israel, Turkey, Brazil, Argentina, Colombia
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Competitive landscape
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Leading Companies, Market Positioning of Companies, Competitive Strategies, and Industry Risks
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What are the Key Data Covered in this AI In Fraud Detection Market Research and Growth Report?
- CAGR of the AI In Fraud Detection industry during the forecast period
- Detailed information on factors that will drive the growth and forecasting between 2024 and 2029
- Precise estimation of the size of the market and its contribution of the industry in focus to the parent market
- Accurate predictions about upcoming growth and trends and changes in consumer behaviour
- Growth of the market across North America, Europe, APAC, Middle East and Africa, South America
- Thorough analysis of the market’s competitive landscape and detailed information about companies
- Comprehensive analysis of factors that will challenge the ai in fraud detection market growth of industry companies
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1 Executive Summary
- 1 Executive Summary
- 1.1 Market overview
- Executive Summary - Chart on Market Overview
- Executive Summary - Data Table on Market Overview
- Executive Summary - Chart on Global Market Characteristics
- Executive Summary - Chart on Market by Geography
- Executive Summary - Chart on Market Segmentation by Component
- Executive Summary - Chart on Market Segmentation by Technology
- Executive Summary - Chart on Market Segmentation by Application
- Executive Summary - Chart on Incremental Growth
- Executive Summary - Data Table on Incremental Growth
- Executive Summary - Chart on Company Market Positioning
2 Technavio Analysis
- 2 Technavio Analysis
- 2.1 Analysis of price sensitivity, lifecycle, customer purchase basket, adoption rates, and purchase criteria
- Analysis of price sensitivity, lifecycle, customer purchase basket, adoption rates, and purchase criteria
- 2.2 Criticality of inputs and Factors of differentiation
- Chart on Overview on criticality of inputs and factors of differentiation
- 2.3 Factors of disruption
- Chart on Overview on factors of disruption
- 2.4 Impact of drivers and challenges
- Chart on Impact of drivers and challenges in 2024 and 2029
3 Market Landscape
- 3 Market Landscape
- 3.1 Market ecosystem
- Chart on Parent Market
- Data Table on - Parent Market
- 3.2 Market characteristics
- Chart on Market characteristics analysis
- 3.3 Value chain analysis
- Chart on Value chain analysis
4 Market Sizing
- 4 Market Sizing
- 4.1 Market definition
- Data Table on Offerings of companies included in the market definition
- 4.2 Market segment analysis
- 4.3 Market size 2024
- 4.4 Market outlook: Forecast for 2024-2029
- Chart on Global - Market size and forecast 2024-2029 ($ billion)
- Data Table on Global - Market size and forecast 2024-2029 ($ billion)
- Chart on Global Market: Year-over-year growth 2024-2029 (%)
- Data Table on Global Market: Year-over-year growth 2024-2029 (%)
5 Historic Market Size
- 5 Historic Market Size
- 5.1 Global AI In Fraud Detection Market 2019 - 2023
- Historic Market Size - Data Table on Global AI In Fraud Detection Market 2019 - 2023 ($ billion)
- 5.2 Component segment analysis 2019 - 2023
- Historic Market Size - Component Segment 2019 - 2023 ($ billion)
- 5.3 Technology segment analysis 2019 - 2023
- Historic Market Size - Technology Segment 2019 - 2023 ($ billion)
- 5.4 Application segment analysis 2019 - 2023
- Historic Market Size - Application Segment 2019 - 2023 ($ billion)
- 5.5 Geography segment analysis 2019 - 2023
- Historic Market Size - Geography Segment 2019 - 2023 ($ billion)
- 5.6 Country segment analysis 2019 - 2023
- Historic Market Size - Country Segment 2019 - 2023 ($ billion)
6 Five Forces Analysis
- 6 Five Forces Analysis
- 6.1 Five forces summary
- Five forces analysis - Comparison between 2024 and 2029
- 6.2 Bargaining power of buyers
- Bargaining power of buyers - Impact of key factors 2024 and 2029
- 6.3 Bargaining power of suppliers
- Bargaining power of suppliers - Impact of key factors in 2024 and 2029
- 6.4 Threat of new entrants
- Threat of new entrants - Impact of key factors in 2024 and 2029
- 6.5 Threat of substitutes
- Threat of substitutes - Impact of key factors in 2024 and 2029
- 6.6 Threat of rivalry
- Threat of rivalry - Impact of key factors in 2024 and 2029
- 6.7 Market condition
- Chart on Market condition - Five forces 2024 and 2029
7 Market Segmentation by Component
- 7 Market Segmentation by Component
- 7.1 Market segments
- Chart on Component - Market share 2024-2029 (%)
- Data Table on Component - Market share 2024-2029 (%)
- 7.2 Comparison by Component
- Chart on Comparison by Component
- Data Table on Comparison by Component
- 7.3 Software - Market size and forecast 2024-2029
- Chart on Software - Market size and forecast 2024-2029 ($ billion)
- Data Table on Software - Market size and forecast 2024-2029 ($ billion)
- Chart on Software - Year-over-year growth 2024-2029 (%)
- Data Table on Software - Year-over-year growth 2024-2029 (%)
- 7.4 Services - Market size and forecast 2024-2029
- Chart on Services - Market size and forecast 2024-2029 ($ billion)
- Data Table on Services - Market size and forecast 2024-2029 ($ billion)
- Chart on Services - Year-over-year growth 2024-2029 (%)
- Data Table on Services - Year-over-year growth 2024-2029 (%)
- 7.5 Market opportunity by Component
- Market opportunity by Component ($ billion)
- Data Table on Market opportunity by Component ($ billion)
8 Market Segmentation by Technology
- 8 Market Segmentation by Technology
- 8.1 Market segments
- Chart on Technology - Market share 2024-2029 (%)
- Data Table on Technology - Market share 2024-2029 (%)
- 8.2 Comparison by Technology
- Chart on Comparison by Technology
- Data Table on Comparison by Technology
- 8.3 Machine learning - Market size and forecast 2024-2029
- Chart on Machine learning - Market size and forecast 2024-2029 ($ billion)
- Data Table on Machine learning - Market size and forecast 2024-2029 ($ billion)
- Chart on Machine learning - Year-over-year growth 2024-2029 (%)
- Data Table on Machine learning - Year-over-year growth 2024-2029 (%)
- 8.4 Deep learning - Market size and forecast 2024-2029
- Chart on Deep learning - Market size and forecast 2024-2029 ($ billion)
- Data Table on Deep learning - Market size and forecast 2024-2029 ($ billion)
- Chart on Deep learning - Year-over-year growth 2024-2029 (%)
- Data Table on Deep learning - Year-over-year growth 2024-2029 (%)
- 8.5 NLP - Market size and forecast 2024-2029
- Chart on NLP - Market size and forecast 2024-2029 ($ billion)
- Data Table on NLP - Market size and forecast 2024-2029 ($ billion)
- Chart on NLP - Year-over-year growth 2024-2029 (%)
- Data Table on NLP - Year-over-year growth 2024-2029 (%)
- 8.6 Others - Market size and forecast 2024-2029
- Chart on Others - Market size and forecast 2024-2029 ($ billion)
- Data Table on Others - Market size and forecast 2024-2029 ($ billion)
- Chart on Others - Year-over-year growth 2024-2029 (%)
- Data Table on Others - Year-over-year growth 2024-2029 (%)
- 8.7 Market opportunity by Technology
- Market opportunity by Technology ($ billion)
- Data Table on Market opportunity by Technology ($ billion)
9 Market Segmentation by Application
- 9 Market Segmentation by Application
- 9.1 Market segments
- Chart on Application - Market share 2024-2029 (%)
- Data Table on Application - Market share 2024-2029 (%)
- 9.2 Comparison by Application
- Chart on Comparison by Application
- Data Table on Comparison by Application
- 9.3 Payment fraud - Market size and forecast 2024-2029
- Chart on Payment fraud - Market size and forecast 2024-2029 ($ billion)
- Data Table on Payment fraud - Market size and forecast 2024-2029 ($ billion)
- Chart on Payment fraud - Year-over-year growth 2024-2029 (%)
- Data Table on Payment fraud - Year-over-year growth 2024-2029 (%)
- 9.4 Anti-money laundering - Market size and forecast 2024-2029
- Chart on Anti-money laundering - Market size and forecast 2024-2029 ($ billion)
- Data Table on Anti-money laundering - Market size and forecast 2024-2029 ($ billion)
- Chart on Anti-money laundering - Year-over-year growth 2024-2029 (%)
- Data Table on Anti-money laundering - Year-over-year growth 2024-2029 (%)
- 9.5 Identity fraud - Market size and forecast 2024-2029
- Chart on Identity fraud - Market size and forecast 2024-2029 ($ billion)
- Data Table on Identity fraud - Market size and forecast 2024-2029 ($ billion)
- Chart on Identity fraud - Year-over-year growth 2024-2029 (%)
- Data Table on Identity fraud - Year-over-year growth 2024-2029 (%)
- 9.6 Insurance fraud - Market size and forecast 2024-2029
- Chart on Insurance fraud - Market size and forecast 2024-2029 ($ billion)
- Data Table on Insurance fraud - Market size and forecast 2024-2029 ($ billion)
- Chart on Insurance fraud - Year-over-year growth 2024-2029 (%)
- Data Table on Insurance fraud - Year-over-year growth 2024-2029 (%)
- 9.7 Others - Market size and forecast 2024-2029
- Chart on Others - Market size and forecast 2024-2029 ($ billion)
- Data Table on Others - Market size and forecast 2024-2029 ($ billion)
- Chart on Others - Year-over-year growth 2024-2029 (%)
- Data Table on Others - Year-over-year growth 2024-2029 (%)
- 9.8 Market opportunity by Application
- Market opportunity by Application ($ billion)
- Data Table on Market opportunity by Application ($ billion)
10 Customer Landscape
- 10 Customer Landscape
- 10.1 Customer landscape overview
- Analysis of price sensitivity, lifecycle, customer purchase basket, adoption rates, and purchase criteria
11 Geographic Landscape
- 11 Geographic Landscape
- 11.1 Geographic segmentation
- Chart on Market share by geography 2024-2029 (%)
- Data Table on Market share by geography 2024-2029 (%)
- 11.2 Geographic comparison
- Chart on Geographic comparison
- Data Table on Geographic comparison
- 11.3 North America - Market size and forecast 2024-2029
- Chart on North America - Market size and forecast 2024-2029 ($ billion)
- Data Table on North America - Market size and forecast 2024-2029 ($ billion)
- Chart on North America - Year-over-year growth 2024-2029 (%)
- Data Table on North America - Year-over-year growth 2024-2029 (%)
- Chart on Regional Comparison - North America
- Data Table on Regional Comparison - North America
- 11.3.1 US - Market size and forecast 2024-2029
- Chart on US - Market size and forecast 2024-2029 ($ billion)
- Data Table on US - Market size and forecast 2024-2029 ($ billion)
- Chart on US - Year-over-year growth 2024-2029 (%)
- Data Table on US - Year-over-year growth 2024-2029 (%)
- 11.3.2 Canada - Market size and forecast 2024-2029
- Chart on Canada - Market size and forecast 2024-2029 ($ billion)
- Data Table on Canada - Market size and forecast 2024-2029 ($ billion)
- Chart on Canada - Year-over-year growth 2024-2029 (%)
- Data Table on Canada - Year-over-year growth 2024-2029 (%)
- 11.3.3 Mexico - Market size and forecast 2024-2029
- Chart on Mexico - Market size and forecast 2024-2029 ($ billion)
- Data Table on Mexico - Market size and forecast 2024-2029 ($ billion)
- Chart on Mexico - Year-over-year growth 2024-2029 (%)
- Data Table on Mexico - Year-over-year growth 2024-2029 (%)
- 11.4 Europe - Market size and forecast 2024-2029
- Chart on Europe - Market size and forecast 2024-2029 ($ billion)
- Data Table on Europe - Market size and forecast 2024-2029 ($ billion)
- Chart on Europe - Year-over-year growth 2024-2029 (%)
- Data Table on Europe - Year-over-year growth 2024-2029 (%)
- Chart on Regional Comparison - Europe
- Data Table on Regional Comparison - Europe
- 11.4.1 UK - Market size and forecast 2024-2029
- Chart on UK - Market size and forecast 2024-2029 ($ billion)
- Data Table on UK - Market size and forecast 2024-2029 ($ billion)
- Chart on UK - Year-over-year growth 2024-2029 (%)
- Data Table on UK - Year-over-year growth 2024-2029 (%)
- 11.4.2 Germany - Market size and forecast 2024-2029
- Chart on Germany - Market size and forecast 2024-2029 ($ billion)
- Data Table on Germany - Market size and forecast 2024-2029 ($ billion)
- Chart on Germany - Year-over-year growth 2024-2029 (%)
- Data Table on Germany - Year-over-year growth 2024-2029 (%)
- 11.4.3 France - Market size and forecast 2024-2029
- Chart on France - Market size and forecast 2024-2029 ($ billion)
- Data Table on France - Market size and forecast 2024-2029 ($ billion)
- Chart on France - Year-over-year growth 2024-2029 (%)
- Data Table on France - Year-over-year growth 2024-2029 (%)
- 11.4.4 Italy - Market size and forecast 2024-2029
- Chart on Italy - Market size and forecast 2024-2029 ($ billion)
- Data Table on Italy - Market size and forecast 2024-2029 ($ billion)
- Chart on Italy - Year-over-year growth 2024-2029 (%)
- Data Table on Italy - Year-over-year growth 2024-2029 (%)
- 11.4.5 Spain - Market size and forecast 2024-2029
- Chart on Spain - Market size and forecast 2024-2029 ($ billion)
- Data Table on Spain - Market size and forecast 2024-2029 ($ billion)
- Chart on Spain - Year-over-year growth 2024-2029 (%)
- Data Table on Spain - Year-over-year growth 2024-2029 (%)
- 11.4.6 The Netherlands - Market size and forecast 2024-2029
- Chart on The Netherlands - Market size and forecast 2024-2029 ($ billion)
- Data Table on The Netherlands - Market size and forecast 2024-2029 ($ billion)
- Chart on The Netherlands - Year-over-year growth 2024-2029 (%)
- Data Table on The Netherlands - Year-over-year growth 2024-2029 (%)
- 11.5 APAC - Market size and forecast 2024-2029
- Chart on APAC - Market size and forecast 2024-2029 ($ billion)
- Data Table on APAC - Market size and forecast 2024-2029 ($ billion)
- Chart on APAC - Year-over-year growth 2024-2029 (%)
- Data Table on APAC - Year-over-year growth 2024-2029 (%)
- Chart on Regional Comparison - APAC
- Data Table on Regional Comparison - APAC
- 11.5.1 China - Market size and forecast 2024-2029
- Chart on China - Market size and forecast 2024-2029 ($ billion)
- Data Table on China - Market size and forecast 2024-2029 ($ billion)
- Chart on China - Year-over-year growth 2024-2029 (%)
- Data Table on China - Year-over-year growth 2024-2029 (%)
- 11.5.2 India - Market size and forecast 2024-2029
- Chart on India - Market size and forecast 2024-2029 ($ billion)
- Data Table on India - Market size and forecast 2024-2029 ($ billion)
- Chart on India - Year-over-year growth 2024-2029 (%)
- Data Table on India - Year-over-year growth 2024-2029 (%)
- 11.5.3 Japan - Market size and forecast 2024-2029
- Chart on Japan - Market size and forecast 2024-2029 ($ billion)
- Data Table on Japan - Market size and forecast 2024-2029 ($ billion)
- Chart on Japan - Year-over-year growth 2024-2029 (%)
- Data Table on Japan - Year-over-year growth 2024-2029 (%)
- 11.5.4 South Korea - Market size and forecast 2024-2029
- Chart on South Korea - Market size and forecast 2024-2029 ($ billion)
- Data Table on South Korea - Market size and forecast 2024-2029 ($ billion)
- Chart on South Korea - Year-over-year growth 2024-2029 (%)
- Data Table on South Korea - Year-over-year growth 2024-2029 (%)
- 11.5.5 Australia - Market size and forecast 2024-2029
- Chart on Australia - Market size and forecast 2024-2029 ($ billion)
- Data Table on Australia - Market size and forecast 2024-2029 ($ billion)
- Chart on Australia - Year-over-year growth 2024-2029 (%)
- Data Table on Australia - Year-over-year growth 2024-2029 (%)
- 11.5.6 Indonesia - Market size and forecast 2024-2029
- Chart on Indonesia - Market size and forecast 2024-2029 ($ billion)
- Data Table on Indonesia - Market size and forecast 2024-2029 ($ billion)
- Chart on Indonesia - Year-over-year growth 2024-2029 (%)
- Data Table on Indonesia - Year-over-year growth 2024-2029 (%)
- 11.6 Middle East and Africa - Market size and forecast 2024-2029
- Chart on Middle East and Africa - Market size and forecast 2024-2029 ($ billion)
- Data Table on Middle East and Africa - Market size and forecast 2024-2029 ($ billion)
- Chart on Middle East and Africa - Year-over-year growth 2024-2029 (%)
- Data Table on Middle East and Africa - Year-over-year growth 2024-2029 (%)
- Chart on Regional Comparison - Middle East and Africa
- Data Table on Regional Comparison - Middle East and Africa
- 11.6.1 UAE - Market size and forecast 2024-2029
- Chart on UAE - Market size and forecast 2024-2029 ($ billion)
- Data Table on UAE - Market size and forecast 2024-2029 ($ billion)
- Chart on UAE - Year-over-year growth 2024-2029 (%)
- Data Table on UAE - Year-over-year growth 2024-2029 (%)
- 11.6.2 Saudi Arabia - Market size and forecast 2024-2029
- Chart on Saudi Arabia - Market size and forecast 2024-2029 ($ billion)
- Data Table on Saudi Arabia - Market size and forecast 2024-2029 ($ billion)
- Chart on Saudi Arabia - Year-over-year growth 2024-2029 (%)
- Data Table on Saudi Arabia - Year-over-year growth 2024-2029 (%)
- 11.6.3 South Africa - Market size and forecast 2024-2029
- Chart on South Africa - Market size and forecast 2024-2029 ($ billion)
- Data Table on South Africa - Market size and forecast 2024-2029 ($ billion)
- Chart on South Africa - Year-over-year growth 2024-2029 (%)
- Data Table on South Africa - Year-over-year growth 2024-2029 (%)
- 11.6.4 Israel - Market size and forecast 2024-2029
- Chart on Israel - Market size and forecast 2024-2029 ($ billion)
- Data Table on Israel - Market size and forecast 2024-2029 ($ billion)
- Chart on Israel - Year-over-year growth 2024-2029 (%)
- Data Table on Israel - Year-over-year growth 2024-2029 (%)
- 11.6.5 Turkey - Market size and forecast 2024-2029
- Chart on Turkey - Market size and forecast 2024-2029 ($ billion)
- Data Table on Turkey - Market size and forecast 2024-2029 ($ billion)
- Chart on Turkey - Year-over-year growth 2024-2029 (%)
- Data Table on Turkey - Year-over-year growth 2024-2029 (%)
- 11.7 South America - Market size and forecast 2024-2029
- Chart on South America - Market size and forecast 2024-2029 ($ billion)
- Data Table on South America - Market size and forecast 2024-2029 ($ billion)
- Chart on South America - Year-over-year growth 2024-2029 (%)
- Data Table on South America - Year-over-year growth 2024-2029 (%)
- Chart on Regional Comparison - South America
- Data Table on Regional Comparison - South America
- 11.7.1 Brazil - Market size and forecast 2024-2029
- Chart on Brazil - Market size and forecast 2024-2029 ($ billion)
- Data Table on Brazil - Market size and forecast 2024-2029 ($ billion)
- Chart on Brazil - Year-over-year growth 2024-2029 (%)
- Data Table on Brazil - Year-over-year growth 2024-2029 (%)
- 11.7.2 Argentina - Market size and forecast 2024-2029
- Chart on Argentina - Market size and forecast 2024-2029 ($ billion)
- Data Table on Argentina - Market size and forecast 2024-2029 ($ billion)
- Chart on Argentina - Year-over-year growth 2024-2029 (%)
- Data Table on Argentina - Year-over-year growth 2024-2029 (%)
- 11.7.3 Colombia - Market size and forecast 2024-2029
- Chart on Colombia - Market size and forecast 2024-2029 ($ billion)
- Data Table on Colombia - Market size and forecast 2024-2029 ($ billion)
- Chart on Colombia - Year-over-year growth 2024-2029 (%)
- Data Table on Colombia - Year-over-year growth 2024-2029 (%)
- 11.8 Market opportunity by geography
- Market opportunity by geography ($ billion)
- Data Tables on Market opportunity by geography ($ billion)
12 Drivers, Challenges, and Opportunity
- 12 Drivers, Challenges, and Opportunity
- 12.1 Market drivers
- Escalating sophistication and proliferation of AI-powered fraud
- Proliferation of digital transactions and big data challenge
- Stringent regulatory mandates and imperative for compliance efficiency
- 12.2 Market challenges
- Data scarcity, privacy constraints, and challenge of high-quality training data
- Lack of model interpretability and ensuring ethical AI
- Prohibitive implementation costs and a persistent talent deficit
- 12.3 Impact of drivers and challenges
- Impact of drivers and challenges in 2024 and 2029
- 12.4 Market opportunities
- Dual-edged sword of generative AI in fraud detection landscapes
- Symbiotic integration of AI with blockchain and advanced biometrics
- Imperative of explainable AI (XAI) for transparency and regulatory adherence
13 Competitive Landscape
- 13 Competitive Landscape
- 13.1 Overview
- 13.2 Competitive Landscape
- Overview on criticality of inputs and factors of differentiation
- 13.3 Landscape disruption
- Overview on factors of disruption
- 13.4 Industry risks
- Impact of key risks on business
14 Competitive Analysis
- 14 Competitive Analysis
- 14.1 Companies profiled
- 14.2 Company ranking index
- 14.3 Market positioning of companies
- Matrix on companies position and classification
- 14.4 ACI Worldwide Inc.
- ACI Worldwide Inc. - Overview
- ACI Worldwide Inc. - Business segments
- ACI Worldwide Inc. - Key news
- ACI Worldwide Inc. - Key offerings
- ACI Worldwide Inc. - Segment focus
- SWOT
- 14.5 Amazon Web Services Inc.
- Amazon Web Services Inc. - Overview
- Amazon Web Services Inc. - Product / Service
- Amazon Web Services Inc. - Key news
- Amazon Web Services Inc. - Key offerings
- SWOT
- 14.6 BAE Systems Plc
- BAE Systems Plc - Overview
- BAE Systems Plc - Business segments
- BAE Systems Plc - Key news
- BAE Systems Plc - Key offerings
- BAE Systems Plc - Segment focus
- SWOT
- 14.7 Consultadoria e Inovacao Tecnologica S.A.
- Consultadoria e Inovacao Tecnologica S.A. - Overview
- Consultadoria e Inovacao Tecnologica S.A. - Product / Service
- Consultadoria e Inovacao Tecnologica S.A. - Key offerings
- SWOT
- 14.8 Fair Isaac Corp.
- Fair Isaac Corp. - Overview
- Fair Isaac Corp. - Business segments
- Fair Isaac Corp. - Key news
- Fair Isaac Corp. - Key offerings
- Fair Isaac Corp. - Segment focus
- SWOT
- 14.9 Fiserv Inc.
- Fiserv Inc. - Overview
- Fiserv Inc. - Business segments
- Fiserv Inc. - Key news
- Fiserv Inc. - Key offerings
- Fiserv Inc. - Segment focus
- SWOT
- 14.10 Google Cloud
- Google Cloud - Overview
- Google Cloud - Product / Service
- Google Cloud - Key offerings
- SWOT
- 14.11 International Business Machines Corp.
- International Business Machines Corp. - Overview
- International Business Machines Corp. - Business segments
- International Business Machines Corp. - Key news
- International Business Machines Corp. - Key offerings
- International Business Machines Corp. - Segment focus
- SWOT
- 14.12 LexisNexis Risk Solutions.
- LexisNexis Risk Solutions. - Overview
- LexisNexis Risk Solutions. - Product / Service
- LexisNexis Risk Solutions. - Key offerings
- SWOT
- 14.13 Microsoft Corp.
- Microsoft Corp. - Overview
- Microsoft Corp. - Business segments
- Microsoft Corp. - Key news
- Microsoft Corp. - Key offerings
- Microsoft Corp. - Segment focus
- SWOT
- 14.14 Oracle Corp.
- Oracle Corp. - Overview
- Oracle Corp. - Business segments
- Oracle Corp. - Key news
- Oracle Corp. - Key offerings
- Oracle Corp. - Segment focus
- SWOT
- 14.15 SAS Institute Inc.
- SAS Institute Inc. - Overview
- SAS Institute Inc. - Product / Service
- SAS Institute Inc. - Key news
- SAS Institute Inc. - Key offerings
- SWOT
- 14.16 Splunk Inc.
- Splunk Inc. - Overview
- Splunk Inc. - Product / Service
- Splunk Inc. - Key offerings
- SWOT
- 14.17 Thales Group
- Thales Group - Overview
- Thales Group - Business segments
- Thales Group - Key news
- Thales Group - Key offerings
- Thales Group - Segment focus
- SWOT
- 14.18 TransUnion
- TransUnion - Overview
- TransUnion - Business segments
- TransUnion - Key news
- TransUnion - Key offerings
- TransUnion - Segment focus
- SWOT
15 Appendix
- 15 Appendix
- 15.1 Scope of the report
- Market definition
- Objectives
- Notes and caveats
- 15.2 Inclusions and exclusions checklist
- Inclusions checklist
- Exclusions checklist
- 15.3 Currency conversion rates for US$
- Currency conversion rates for US$
- 15.4 Research methodology
- 15.5 Data procurement
- 15.6 Data validation
- 15.7 Validation techniques employed for market sizing
- Validation techniques employed for market sizing
- 15.8 Data synthesis
- 15.9 360 degree market analysis
- 360 degree market analysis
- 15.10 List of abbreviations
INFORMATION SOURCES
DATA ANALYSIS
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