The global AI Fraud Detection market was valued at USD 18.5 Billion in 2025 and is projected to grow from USD 21.8 Billion in 2026 to USD 95.2 Billion by 2035, at a CAGR of 17.8% from 2026–2035. North America held ~38.4% share (USD 7.1 billion) of the global market in 2025.
The AI Fraud Detection market is expanding rapidly from $18.5 billion in 2025 to $95.2 billion by 2035, driven by escalating fraud threats and enterprise investment in real-time detection systems. Solutions dominate the component segment, while payment fraud applications lead adoption across sectors. Large corporations accelerate market growth through substantial resource allocation and transaction volume handling.
According to Banking Industry Insights analysis, North America maintains market leadership with 38.2% share in 2025, while Asia-Pacific emerges as the fastest-growing region, expected to exceed 28% share by 2032. Enterprise consolidation around integrated platforms and generative AI capabilities is reshaping competitive dynamics, with major players expanding portfolios through strategic investments in real-time detection and agentic AI technologies.
The AI Fraud Detection market encompasses software solutions and professional services designed to identify, prevent, and investigate fraudulent activities across financial transactions, identity verification, and account security. This market includes machine learning algorithms, behavioral analytics platforms, and cloud-based detection systems deployed across banking, payments, e-commerce, and fintech sectors. The market serves enterprises of all sizes, from large corporations processing millions of daily transactions to small businesses protecting customer accounts. Solutions represent the dominant component, while payment fraud applications drive the largest revenue segment globally.
The market operates within an increasingly stringent regulatory environment shaped by directives including the EU's PSD2 and GDPR, the U.S. Consumer Financial Protection Bureau's updated Regulation E guidelines, and the Financial Action Task Force's revised wire transfer recommendations. These regulatory catalysts have created mandatory compliance timelines that directly accelerate AI deployment cycles across financial institutions. Organizations face escalating pressure to modernize fraud management infrastructure, moving away from obsolete rule-based systems toward adaptive AI technologies. Regulatory mandates around anti-money laundering, know-your-customer protocols, and data protection have become primary drivers of technology investment and market expansion.
| Parameter | Details |
|---|---|
| Market Size in 2025 | USD 18.5 Billion |
| Market Size in 2026 | USD 21.8 Billion |
| Revenue Forecast in 2035 | USD 95.2 Billion |
| Growth Rate | CAGR of 17.8% from 2026 to 2035 |
| Analysis period | 2025–2035 |
| Base Year | 2025 |
| Forecast Period | 2026–2035 |
Based on research conducted by Banking Industry Insights, we found that four structural trends are reshaping product development, sourcing, and stakeholder engagement across the AI Fraud Detection industry.
The following interactive matrix quantifies the forces shaping the market through 2035, each scored by its estimated impact on the market's CAGR, geographic focus, and timeline. Type in the search box to filter by driver, restraint, or opportunity.
| Factors ▲ | Type | Qualitative Impact | Geographic Focus | Timeline |
|---|---|---|---|---|
| Digital Transaction Volume Growth | DRIVER | +2.5% | Global | 2025-2035 |
| Regulatory Compliance Mandates (PSD2, GDPR, Regulation E) | DRIVER | +2.2% | North America, EU | 2025-2030 |
| Fraud Sophistication and Adaptive Threats | DRIVER | +1.8% | Global | 2025-2035 |
| Cloud-Based Deployment Models | DRIVER | +1.5% | Global | 2025-2035 |
| LLM-Assisted Compliance Automation | OPPORTUNITY | +2.0% | North America, EU | 2027-2035 |
| Fintech Ecosystem Expansion in Emerging Markets | OPPORTUNITY | +1.8% | Asia-Pacific, Latin America | 2025-2035 |
| Mobile Money and Digital Financial Inclusion | OPPORTUNITY | +1.6% | Asia-Pacific, Middle East & Africa | 2025-2035 |
| Model Bias and AI Fairness Concerns | RESTRAINT | -1.2% | Global | 2025-2035 |
| High Implementation Costs and Data Privacy Barriers | RESTRAINT | -1.0% | Asia-Pacific, Africa, Latin America | 2025-2030 |
| False Positive Rates Impacting Customer Experience | RESTRAINT | -0.7% | Global | 2025-2035 |
Digital transaction volume growth across banking, payments, and e-commerce sectors represents the primary market expansion driver, creating demand for AI fraud detection systems that scale with transaction throughput while maintaining low false-positive rates. Financial institutions process exponentially increasing transaction volumes daily, necessitating automated detection systems that human investigators cannot match in speed or scale. This driver is amplified by regulatory compliance requirements mandating advanced fraud prevention capabilities. According to Banking Industry Insights Analysis, the convergence of digital payment adoption and regulatory pressure creates sustained demand across all enterprise segments and geographic regions through 2035.
Regulatory compliance catalysts including the EU's PSD2 and PSD3 directives, GDPR requirements, and the U.S. Consumer Financial Protection Bureau's updated Regulation E guidelines create mandatory compliance timelines that directly accelerate AI deployment cycles. Financial institutions face escalating pressure from regulatory authorities to modernize fraud management infrastructure and implement advanced detection technologies. These regulatory mandates have become primary investment drivers, compelling organizations to transition from obsolete rule-based systems toward adaptive AI technologies. The regulatory environment particularly impacts North America and Europe, where stringent frameworks drive substantial technology investments and create competitive advantages for early adopters.
High implementation costs, data privacy concerns, and ethical risks present significant adoption barriers, particularly for smaller organizations and developing market participants. Model bias represents a critical concern, as AI fraud detection systems are only as effective as the training data they utilize, potentially perpetuating historical biases in fraud detection patterns. False positive rates, while improving, continue to negatively impact customer experience and operational efficiency. These restraints disproportionately affect Asia-Pacific, Africa, and Latin America regions where smaller enterprises and emerging financial institutions operate with constrained technology budgets and limited AI expertise, potentially slowing market penetration in these high-growth regions.
Source: Banking Industry Insights Analysis, 2026
Within the By Component Type category, the Solutions segment held the dominant market share in 2025. Meanwhile, the Services segment is anticipated to be the fastest-growing, expanding at a CAGR of 17.9% during the forecast period.
| Segment Item | 2025 (USD Bn) | 2026 (USD Bn) | 2035 (USD Bn) | CAGR (2026–2035) |
|---|---|---|---|---|
| Solutions | 11.5 | 13.5 | 59.0 | 17.8% |
| Services | 7.0 | 8.3 | 36.2 | 17.9% |
Source: Banking Industry Insights Analysis, 2026
Within the By Application category, the Payment Fraud segment held the dominant market share in 2025. Meanwhile, the Identity Fraud segment is anticipated to be the fastest-growing, expanding at a CAGR of 17.9% during the forecast period.
| Segment Item | 2025 (USD Bn) | 2026 (USD Bn) | 2035 (USD Bn) | CAGR (2026–2035) |
|---|---|---|---|---|
| Payment Fraud | 9.1 | 10.7 | 47.0 | 17.8% |
| Identity Fraud | 4.4 | 5.2 | 22.8 | 17.9% |
| Account Takeover | 2.7 | 3.2 | 13.7 | 17.6% |
| Other Applications | 2.3 | 2.7 | 11.7 | 17.7% |
Source: Banking Industry Insights Analysis, 2026
Within the By Enterprise Size category, the Large Corporations segment held the dominant market share in 2025. Meanwhile, the Small Businesses segment is anticipated to be the fastest-growing, expanding at a CAGR of 17.9% during the forecast period.
| Segment Item | 2025 (USD Bn) | 2026 (USD Bn) | 2035 (USD Bn) | CAGR (2026–2035) |
|---|---|---|---|---|
| Large Corporations | 11.1 | 13.1 | 57.1 | 17.8% |
| Mid-Market Enterprises | 5.2 | 6.1 | 26.7 | 17.8% |
| Small Businesses | 2.2 | 2.6 | 11.4 | 17.9% |
Source: Banking Industry Insights Analysis, 2026
The complete segmentation hierarchy used throughout this report. Click a category to view its sub-segments.
Our analysis shows that three forward-looking opportunities stand out for stakeholders positioning within this market over the forecast period.
Payment Fraud represents the largest application segment, valued at USD 9.1 billion in 2025 and projected to reach USD 47.0 billion by 2035 at 17.8% CAGR. This segment's dominance reflects escalating e-commerce fraud losses and digital payment proliferation. Financial institutions prioritize sophisticated detection systems to combat payment card fraud, account compromise, and transaction manipulation. The USD 37.9 billion absolute growth opportunity within this segment alone underscores substantial market potential for solution providers targeting payment security infrastructure modernization.
Identity Fraud and Account Takeover segments combined represent USD 26.5 billion in projected 2035 value (USD 22.8 billion and USD 13.7 billion respectively), growing from USD 7.1 billion in 2025. These segments address critical vulnerabilities in customer authentication and account security. Rising credential compromise incidents and synthetic identity fraud drive demand for behavioral analytics and multi-factor authentication solutions. The combined USD 19.4 billion growth opportunity reflects banks' urgent need to protect customer accounts and reduce account takeover losses across digital channels.
Services segment is projected to grow from USD 7.0 billion in 2025 to USD 36.2 billion by 2035 at 17.9% CAGR, representing USD 29.2 billion in absolute value expansion. This fastest-growing component type reflects increasing demand for consulting, system integration, managed services, and ongoing support. Financial institutions require expert implementation and continuous optimization of AI fraud detection systems. The services opportunity encompasses staff augmentation, model training, and managed detection services, creating substantial revenue potential for system integrators and managed service providers supporting enterprise fraud prevention programs.
The AI Fraud Detection market is experiencing significant capital inflows driven by rising fraud sophistication and regulatory mandates. According to market analysis, the sector is projected to grow from USD 18.5 billion in 2025 to USD 95.2 billion by 2035, representing a 15.0% CAGR. Strategic acquisitions like LexisNexis's IDVerse purchase demonstrate investor confidence in consolidation-driven growth, while venture capital continues funding innovative startups developing specialized detection technologies for emerging fraud vectors including deepfakes and synthetic identities.
Infrastructure investment in AI Fraud Detection centers on cloud-based platforms, real-time monitoring systems, and integrated data networks. Major players like Fiserv, FIS Global, and NICE Actimize are investing in omnichannel fraud detection infrastructure that identifies fraudulent transactions across multiple payment channels simultaneously. Advanced case management systems, behavioral analytics platforms, and external threat intelligence integration are becoming standard infrastructure components. These investments enable financial institutions to deploy scalable, adaptive fraud detection systems that process high transaction volumes while maintaining investigation efficiency and reducing false positives.
ESG considerations in AI Fraud Detection focus on data privacy, algorithmic fairness, and cybersecurity governance. As systems analyze vast customer datasets for anomaly detection, companies must ensure compliance with GDPR, CCPA, and emerging data protection regulations. Algorithmic bias in fraud detection models can disproportionately impact certain demographics, requiring transparent model governance and regular bias audits. Additionally, robust cybersecurity infrastructure protects sensitive financial data and identity information from breaches. Companies demonstrating strong ESG practices in data governance and fair AI implementation gain competitive advantages and stakeholder trust in this privacy-sensitive market.
Our assessment indicates that the following strengths, weaknesses, opportunities, and threats characterize the competitive position of the AI Fraud Detection heading into 2035.
AI fraud detection systems significantly reduce false positives compared to traditional rule-based approaches, enabling organizations to focus investigative resources on high-risk transactions. Solutions segment dominance demonstrates strong market validation and sustained enterprise investment in software-based fraud prevention. Real-time monitoring and immediate detection capabilities minimize financial losses and reputational damage compared to post-incident investigations, creating compelling value propositions across all enterprise sizes.
Model bias and AI fairness concerns limit deployment confidence among risk-averse organizations and regulators. High implementation costs and data privacy compliance requirements create adoption barriers for smaller enterprises and emerging market participants. False positive rates, while improving, continue to negatively impact customer experience and operational efficiency, requiring ongoing model refinement and tuning.
LLM-assisted Suspicious Activity Report drafting reduces investigator time from hours to minutes while improving regulatory compliance consistency, creating substantial operational efficiency gains. Fintech ecosystem expansion in Asia-Pacific and emerging markets presents significant growth potential as digital payment adoption accelerates and regulatory frameworks mature. Mobile money expansion and digital financial inclusion initiatives in Middle East & Africa and Asia-Pacific regions drive demand for scalable fraud detection infrastructure supporting financial inclusion objectives.
Fraud sophistication, including synthetic identity creation and deepfake-enabled social engineering, continues to outpace detection capabilities, requiring continuous AI model updates and investment. Regulatory fragmentation across jurisdictions creates compliance complexity and increases implementation costs. Cybersecurity threats targeting fraud detection systems themselves present emerging risks that could undermine system reliability and market confidence in AI-based solutions.
35+ Countries · 20 Profiled · 10-year forecast with YoY data tables · Free Excel data file included
Click a region to explore its key national markets and growth drivers.
North America maintains its position as the largest regional market for AI fraud detection, driven by advanced infrastructure, regulatory compliance requirements, and high digital transaction volumes. The region benefits from established fintech ecosystems, significant investment in AI technologies, and stringent fraud prevention mandates. Financial institutions across the US and Canada prioritize sophisticated fraud detection systems to combat evolving cyber threats. The mature market demonstrates consistent adoption of machine learning and behavioral analytics solutions. Strong presence of major technology vendors and financial service providers accelerates innovation and deployment. Regional focus on data security and consumer protection standards continues to fuel market expansion.
US
CanadaEurope represents a significant market for AI fraud detection, characterized by stringent regulatory frameworks including PSD2, GDPR, and strong consumer protection standards. Financial institutions across the region invest in advanced detection systems to comply with regulatory requirements and combat sophisticated fraud schemes. The market benefits from mature banking infrastructure, high digital payment adoption, and cross-border transaction complexity. European banks prioritize data privacy and security alongside fraud prevention capabilities. Regional focus on open banking and fintech integration drives innovation in fraud detection solutions. Strong emphasis on customer authentication and transaction monitoring accelerates market growth.
UK
Germany
FranceAsia-Pacific emerges as the fastest-growing regional market for AI fraud detection, driven by rapid digital payment adoption, expanding e-commerce ecosystems, and increasing fraud sophistication. The region experiences explosive growth in mobile payments, fintech innovation, and financial inclusion initiatives. Emerging economies invest heavily in fraud prevention infrastructure to support digital transformation. Rising fraud losses and regulatory pressures from central banks accelerate adoption of AI-powered detection systems. The region benefits from large populations transitioning to digital financial services and growing cross-border transaction volumes. Strong government support for fintech development and cybersecurity initiatives fuels market expansion.
China
India
Japan
South KoreaLatin America experiences accelerating growth in AI fraud detection adoption, driven by expanding digital payment infrastructure, rising fraud incidents, and increasing regulatory focus. The region benefits from growing middle-class populations adopting digital financial services and e-commerce expansion. Financial institutions invest in fraud prevention systems to combat rising cybercrime and payment fraud. Regulatory pressures from central banks and financial authorities drive adoption of advanced detection technologies. The market shows strong potential as digital payment penetration increases and fintech ecosystems mature. Regional focus on financial inclusion and digital transformation supports sustained market expansion.
Brazil
ArgentinaMiddle East & Africa exhibits expanding demand tied to national AI strategies, government digitalization, and sovereign infrastructure investment. Enterprise opportunities center around public sector programs, financial institutions, and commercial enterprises across the UAE, Saudi Arabia, South Africa, and regional digital hubs, where technology investments are increasingly project-led and infrastructure-driven. The region is valued at $0.8B in 2025 and is projected to achieve $7.0B by 2035, marking a 24.2% CAGR. Expansion is facilitated through government procurement frameworks, regional cloud partnerships, and enterprise tech integrators, with infrastructure readiness outside tier-1 technology corridors determining deployment velocity.
UAE
Saudi Arabia| Dimension | Description |
|---|---|
| Market Concentration | The AI fraud detection market exhibits moderate concentration with established financial services and data analytics firms holding significant market share alongside emerging specialized vendors. |
| Product Differentiation | Competitors differentiate through machine learning algorithms, real-time processing capabilities, multi-channel fraud detection, and integration depth with existing payment and banking infrastructure. |
| Geographic Reach | North American and European companies maintain strong positions, with growing competition from Asia-Pacific vendors addressing regional regulatory requirements and localized fraud patterns. |
| Innovation Focus | Key innovation areas include behavioral analytics, graph-based fraud detection, explainable AI models, and cross-channel transaction monitoring to combat evolving fraud methodologies. |
| M&A Activity | Consolidation continues as larger financial services platforms acquire specialized AI fraud detection vendors to enhance capabilities and expand market coverage. |
Source: Banking Industry Insights Analysis, 2026
The AI fraud detection market comprises 20 major corporate entities spanning financial services infrastructure providers, specialized fraud detection vendors, and payment networks. Established players like Fiserv, FIS Global, and TransUnion leverage extensive customer bases and data assets, while specialized firms such as NICE Actimize and Feedzai compete through advanced machine learning capabilities. Payment networks including Visa and Mastercard integrate fraud detection into core platforms. Competition intensifies as regulatory requirements and sophisticated fraud schemes drive demand for AI-powered solutions across banking, e-commerce, and fintech sectors.
Market participants differentiate through proprietary machine learning models, real-time transaction analysis, and behavioral analytics capabilities. SAS Institute and FICO leverage statistical expertise and predictive modeling heritage. Emerging vendors like Feedzai and Sift emphasize cloud-native architectures and explainable AI. Integration depth varies significantly, with payment networks embedding fraud detection natively while specialist vendors offer modular solutions. Companies invest heavily in handling evolving fraud patterns including synthetic identity fraud, account takeover, and organized retail crime through continuous model retraining and cross-institutional data sharing.
Strategic consolidation shapes market dynamics as larger financial services platforms acquire specialized fraud detection capabilities. Major infrastructure providers expand through targeted acquisitions to enhance AI offerings and customer retention. Payment networks strengthen fraud prevention through internal development and partnerships. Geographic expansion focuses on emerging markets with growing digital payment adoption and regulatory mandates for fraud prevention. Partnerships between technology vendors and financial institutions enable co-development of industry-specific solutions, while venture-backed specialists pursue growth through customer acquisition and feature expansion before potential acquisition by larger platforms.
Key companies active in the global AI Fraud Detection include:
Recent developments in AI Fraud Detection focus on advanced document authentication, agentic AI platforms reducing investigation time, and strategic acquisitions enhancing biometric and deepfake detection capabilities. Major players are integrating machine learning, generative AI, and automated risk analysis to combat evolving fraud threats including synthetic identities and AI-generated fraud.
| Date | Summary | Source |
|---|---|---|
| April 1, 2025 | NICE Actimize launched its enhanced X-Sight ActOne platform incorporating agentic AI, machine learning, and generative AI capabilities. The platform reduces fraud investigation time by over 50%, streamlining case management and enabling efficient investigator collaboration through advanced automation. | Official Announcement |
| December 10, 2024 | LexisNexis Risk Solutions acquired IDVerse, an AI-powered document authentication and fraud detection provider. IDVerse verifies over 16,000 identity document types globally using deep neural networks and biometric algorithms, enhancing capabilities against deepfakes and AI-generated fraud with automatic fraud model updates. | Official Announcement |
| August 12, 2024 | Experian's 2025 U.S. Identity and Fraud Report indicates 72% of businesses expect AI fraud to be among top challenges by 2026. The report highlights fraudsters leveraging AI for automated bot attacks, deepfakes, synthetic identities, and personalized phishing, requiring AI-powered detection solutions. | Official Announcement |
Source: Banking Industry Insights Analysis, 2026
Through our market assessment, we gathered perspectives from senior executives active in the ai fraud detection ecosystem.
Rick Trainor's statement underscores the market's fundamental shift toward AI-versus-AI fraud mitigation strategies. His emphasis on integrating advanced technologies reflects industry consensus that traditional rule-based systems are insufficient against sophisticated AI-driven fraud. This perspective validates the market's trajectory toward more complex, adaptive detection platforms and justifies continued investment in agentic AI and machine learning solutions across the fraud detection ecosystem.
Investors benefit from the AI Fraud Detection market's projected 17.8% CAGR growth trajectory, expanding from USD 18.5 billion to USD 95.2 billion by 2035. Strategic acquisitions and consolidation activities create exit opportunities, while continuous innovation in agentic AI and biometric technologies attract venture capital. The market's defensive nature—protecting financial institutions from fraud losses—provides stable, recurring revenue streams and resilient investment returns across economic cycles.
Technology vendors including NICE Actimize, Fiserv, and LexisNexis benefit from expanding demand for sophisticated fraud detection platforms. The shift toward agentic AI and machine learning creates opportunities for platform differentiation and premium pricing. Vendors can monetize through licensing, SaaS subscriptions, and managed services. Integration capabilities with existing banking infrastructure and real-time processing performance become key competitive advantages, enabling vendors to capture market share across financial institutions, payment processors, and fintech companies.
Financial institutions and payment networks like Mastercard and Visa benefit from reduced fraud losses, improved customer trust, and operational efficiency. AI-powered detection systems reduce investigation time by over 50%, lowering operational costs while enabling faster legitimate transaction processing. Enhanced fraud prevention protects brand reputation and customer loyalty. Compliance with regulatory requirements becomes easier through automated monitoring and reporting. These institutions gain competitive advantages by offering frictionless, secure payment experiences that build customer confidence and drive transaction volume growth.
Regulatory bodies benefit from improved market stability and reduced systemic fraud risk as AI detection systems identify emerging threats faster. Compliance officers gain automated monitoring and reporting capabilities that simplify regulatory adherence across jurisdictions. Real-time fraud detection enables regulators to identify patterns indicating organized fraud schemes or money laundering activities. Advanced analytics provide data-driven insights for policy development. However, regulators must establish governance frameworks ensuring algorithmic transparency, fairness, and accountability in AI-driven decision-making affecting customer access to financial services.
The AI Fraud Detection market demonstrates robust expansion trajectory, growing from USD 18.5 billion in 2025 to USD 95.2 billion by 2035, representing USD 76.7 billion in absolute value expansion at 17.8% CAGR. North America leads with ~38.4% share (USD 7.10 billion in 2025, reaching USD 28.6 billion by 2035 at 17.8% CAGR), while Asia-Pacific emerges as the fastest-growing region at 17.8% CAGR, driven by digital payment proliferation and fintech ecosystem expansion. Solutions segment dominates at USD 11.5 billion in 2025, projected to reach USD 59.0 billion by 2035. Payment Fraud application represents the largest opportunity at USD 47.0 billion by 2035. Market growth reflects escalating fraud sophistication, regulatory compliance pressures, and enterprise digital transformation initiatives globally.
Stakeholders should prioritize expansion into high-growth regions including Asia-Pacific (20.1% CAGR), Latin America (18.4% CAGR), and Middle East & Africa (24.2% CAGR) to capture emerging market opportunities. Solution providers should develop industry-specific fraud detection platforms addressing Payment Fraud (USD 47.0 billion by 2035) and Identity Fraud (USD 22.8 billion by 2035) segments. Investment in managed services and AI-as-a-Service delivery models aligns with Services segment growth (15.0% CAGR, USD 36.2 billion by 2035). Strategic partnerships with financial institutions, fintech companies, and regulatory bodies enhance market positioning. Organizations should emphasize real-time detection capabilities, cloud-based architectures, and compliance with evolving regulatory frameworks to maintain competitive advantage.
The AI Fraud Detection market presents attractive investment opportunities with consistent 17.8% CAGR growth and USD 76.7 billion absolute value expansion through 2035. North America's mature market (USD 28.6 billion by 2035) offers stable returns, while Asia-Pacific's 20.1% CAGR growth rate provides high-growth potential. Solutions segment dominance (USD 59.0 billion by 2035) indicates strong enterprise demand for technology investments. Risk factors include regulatory compliance complexity, data privacy concerns, integration challenges with legacy systems, and talent shortage in AI expertise. Market consolidation potential exists as larger vendors acquire specialized fraud detection providers. Investment in emerging technologies including advanced machine learning, behavioral analytics, and real-time processing capabilities positions investors favorably for sustained market expansion.
Key growth pathways include geographic expansion into Asia-Pacific (USD 32.5 billion by 2035) and Middle East & Africa (USD 7.0 billion by 2035) regions experiencing accelerated digital transformation. Vertical integration opportunities exist through acquisition of specialized fraud detection providers and complementary cybersecurity solutions. Product innovation pathways focus on Payment Fraud detection (USD 47.0 billion by 2035), Identity Fraud prevention (USD 22.8 billion by 2035), and Account Takeover protection (USD 13.7 billion by 2035). Services expansion through managed detection services, consulting, and system integration addresses Services segment growth (USD 36.2 billion by 2035). Strategic partnerships with financial institutions, regulatory bodies, and technology platforms enable market penetration. Investment in emerging technologies including AI, machine learning, and cloud infrastructure supports sustained competitive advantage and market share expansion.
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