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市场调查报告书
商品编码
1778327
BFSI的诈欺侦测·防止的全球市场:报价环,诈欺类别,各部署模式,各最终用途,各地区,机会,预测,2018年~2032年Global Fraud Detection and Prevention in BFSI Market Assessment, By Offerings, By Fraud Type, By Deployment Mode, By End-use, By Region, Opportunities and Forecast, 2018-2032F |
全球BFSI(银行、金融服务和保险)诈欺侦测与预防市场预计将从2024年的375.8亿美元成长到2032年的1627.1亿美元,2025年至2032年的复合年增长率为20.11%。受金融服务快速数位化、网路诈骗事件增加以及保护敏感客户资料需求日益增长的推动,BFSI(银行、金融服务和保险)诈欺侦测与预防 (FDP) 市场正呈现强劲成长势头。
全球BFSI(银行、金融服务和保险)诈欺侦测与预防 (FDP) 市场预计将继续保持快速成长,这主要归因于跨数位管道的数位诈欺日益复杂且频繁发生。随着数位银行、线上保险理赔和即时支付系统的加速发展,企业面临网路诈欺、身分盗窃、支付诈欺、帐户盗用和资料外洩的风险也日益增加。
为了应对快速发展且技术日益复杂的诈欺情势,金融机构正在转向 FDP 解决方案,该解决方案结合了人工智慧 (AI)、机器学习 (ML)、大数据分析和行为生物识别技术,以实现即时诈欺检测、基于风险的身份验证和预测分析,从而减少金融犯罪。此外,全球监管结构要求金融机构遵守 "了解你的客户" (KYC)、反洗钱 (AML) 和 "一般资料保护规范" (GDPR) 等合规框架,并投资于诈欺防制基础设施,这进一步推动了 FDP 市场的成长。
此外,基于云端的诈欺侦测平台的普及率不断提高,这些平台提供了可扩展、经济高效的解决方案和 API 友善功能,这推动了对诈欺检测的需求,尤其是对基于云端的帐户的诈欺检测。随着各机构努力维护客户信任并遵守 "了解你的客户" (KYC) 法规,尤其是在疫情期间,对下一代诈欺侦测系统的需求预计将持续成长。
例如,2025 年 3 月 11 日,阿拉伯国家银行 (ANB) 与 IBM Corporation 和 EJADA 合作部署了 IBM Safer Payments,采用跨通路诈欺预防功能来保护客户,并方便客户获得现代、安全和创新的银行体验。
本报告研究了全球 BFSI 诈欺侦测和预防市场,提供了市场概况、按产品细分、诈欺类型、部署模式、最终用途和区域趋势,以及市场参与者的概况。
Global fraud detection and prevention in BFSI market is projected to witness a CAGR of 20.11% during the forecast period 2025-2032, growing from USD 37.58 billion in 2024 to USD 162.71 billion in 2032. The fraud detection and prevention (FDP) in BFSI (Banking, Financial Services, and Insurance) market is experiencing a strong growth trajectory due to the rapid digitization of financial services, the increasing number of cyber fraud incidents, and the growing need to secure sensitive customer data.
The global fraud detection and prevention (FDP) in Banking, Financial Services, and Insurance (BFSI) market is on the path to continued rapid growth, primarily driven by the increased complexity and frequency of digital fraud across digital channels. With the acceleration towards digital banking, online insurance claims, real-time payment systems, organizations are facing increased exposure to cyber fraud, identity theft, payment fraud, account takeovers, and data leaks.
To adapt to the rapidly evolving, technologically advanced landscape of fraud, financial institutions are moving toward FDP solutions using a combination of artificial intelligence (AI), machine learning (ML), big data analytics, and behavioral biometrics that allow for real-time fraud detection, risk-based authentication, and predictive analytics to reduce financial crimes. Additionally, global regulatory structures require financial institutions to comply with and invest in fraud prevention infrastructure to meet compliance frameworks, such as Know Your Customer (KYC), Anti-Money Laundering (AML), and the General Data Protection Regulation (GDPR), which has led to increased growth in the FDP market.
Moreover, the increased adoption of cloud-based fraud detection platforms that can scale, offer cost-effective solutions, and provide easier APIs has created a growing demand for fraud detection, particularly against cloud-based accounts. As organizations strive to protect customer trust and comply with KYC legislation (especially during the pandemic), the rising demand for next-generation fraud detection systems is expected to persist.
For instance, on 11 March 2025, Arab National Bank (ANB) partnered with IBM Corporation and EJADA to implement IBM Safer Payments, adopting cross-channel fraud protection capabilities to protect and empower its customers with easier access to the latest secure and innovative banking experiences.
Rapid Digitalization of Financial Services Drives Market Demand
The rapid digital transformation of the banking, financial services, and insurance (BFSI) sector has emerged as a significant contributor to the global fraud detection and prevention (FDP) market. With an increasing number of customers wanting easy access and remote services offered by financial institutions, customers are adopting digital banking functions, mobile payments, online lending and digital insurance to meet those expectations, increasing the amount and pace of financial transactions online. As organizations digitize to improve service and make operations more efficient, this transformation also creates more risk. Financial systems are vulnerable to cyber issues as reliance on digital, internet-based platforms continues to increase. Cyber fraud has increased, with instances of identity theft, phishing, malware, and account takeover. More sophisticated cybercriminals have adopted advanced attacks against vulnerabilities in digital channels. Increasing risk, impact, and sophistication of attacks are becoming more significant for organizations and their customers. As a response, financial organizations are becoming increasingly investment-conscious about using advanced fraud detection and prevention solutions that monitor in real-time, offer behavioral analysis, predictive threat detection, and are even expanding to include authentication and account lifecycle management. Several financial organizations have begun to seek new technology solutions to enhance their fraud management systems by incorporating artificial intelligence (AI), machine learning (ML), and data analytics, aiming to improve accuracy, speed, and the ability to identify and respond to various types of threats.
For example, in December 2024, the Reserve Bank of India (RBI) launched MuleHunter.ai, an AI-powered tool that verifies mule accounts used in digital banking frauds. As digital transactions increased on platforms such as UPI and mobile banking, cyber frauds also skyrocketed. The system employs AI/ML that analyzes real-time transaction patterns and identifies suspicious ones, in part because the rapid financial digitalization means more intelligent fraud prevention strategies are needed.
Rising Incidence of Sophisticated Cyber Threats Drives Market Growth
The rapid frequency and sophistication of cyber threats have become an important growth driver for the global Fraud Detection and Prevention (FDP) market across the BFSI sector. Financial institutions are facing an increasing number of frauds perpetrated by more sophisticated methods like phishing, identity theft, account takeovers, synthetic identity fraud, and ransomware, as well as increasingly sophisticated threats that involve advanced techniques such as deepfake identities, organized crime, social engineering, AI generated scams and coordinated bot actions, thus moving beyond traditional methods. These cybercrimes can bypass traditional security controls, causing financial losses, operational downtime, and ultimately harming the organization by eroding trust with its customers. The increase in digital offerings, as well as third-party integrations, has expanded the attack surface, thereby increasing the likelihood of unauthorized access and fraudulent transactions. To combat advanced fraud schemes, BFSI organizations are increasingly utilizing intelligent FDP, which incorporates artificial intelligence (AI), machine learning (ML), and big data analytics to offer real-time anomaly detection, risk scoring, and adaptive authentication, enabling proactive handling of emerging threats. In addition, legislation worldwide is tightening compliance requirements for control frameworks related to protecting consumer data and prohibiting fraudulent activities. As increased activity continues to change the threat landscape, financial institutions are investing heavily in reducing cyber threats through advanced FDP solutions.
For example, in November 2024, IBM Corporation Security expanded its Trusteer Pinpoint Detect solution to give customers advanced behavioral biometrics capabilities to detect account takeover attempts in real-time. The platform monitors a user's interactions, such as mouse movements and clicks, to build unique behavioral models and detect anomalies, even when they are using valid credentials. This advancement has made it easier for companies to detect more advanced types of threats, such as credential theft and social engineering attempts, demonstrating a trend where fraud prevention tools are increasingly utilizing AI in the banking, financial services, and insurance (BFSI) market.
Cloud Deployment Segment Dominates Market Growth
The cloud deployment segment is projected to be a high-growth segment of the global Fraud Detection and Prevention (FDP) market, with a steady growth trend observed in the broader BFSI segment of FDP. With financial institutions actively pursuing their digital transformation programs, there is a significant shift toward cloud deployment, offering the benefits of scalability, cost efficiency, and the ability to support real-time fraud detection and monitoring. Cloud FDP systems enable banks, insurance companies, and fintechs to implement more sophisticated analytics, AI, and ML capabilities without incurring significant infrastructure investments. They also allow faster response to fraud trends, automatic upgrades, and integration with third-party systems and mobile banking feeds. As banks, payments, and insurance companies continue to adopt a more digital business model, the rise in remote transactions, mobile payments, and online banking offerings has fueled the demand for more flexible and agile fraud prevention methods. Cloud deployment also encourages centralized threat intelligence, encourages inter-location or inter-department collaboration, and can provide a well-rounded posture to improve the overall security stance of banks, insurance companies, and fintechs that operate under. While financial institutions continue to pursue real-time processing of data in compliance with regulatory requirements, with risk management aiding in effective strategy and business models, cloud deployment is poised for rapid adoption across the BFSI sector.
For instance, in August 2024, Rippleshot, Inc. announced a partnership with CPI Card Group to integrate its cloud-based, AI-enabled fraud detection platform into CPI's payment card services. The collaboration aims to enhance security, reduce the cost of fraud, and naturally increase customer retention, while highlighting the growing adoption of scalable, cloud-native fraud detection platforms (FDPs) within the payments and card ecosystem.
North America Dominates the Global Fraud Detection and Prevention in BFSI Market Size
North America occupies the top position in terms of share in the world's fraud detection and prevention (FDP) market share in the Banking, Financial Services and Insurance (BFSI) sector driven by key factors such as high uses of digital banking, consolidated financial infrastructure and the first adopters of new and innovative methods including artificial intelligence (AI), machine learning (ML) and cloud-based fraud detection system. The region also suffers from a high rate of difficult-to-detect cyber threats, including the everyday online and mobile banking activity, phishing, account takeover, identity theft and synthetic fraud, and, as a result, financial institutions in the U.S. and Canada have invested heavily into real-time fraud detection tools and multiple security mechanisms to protect customer data and the integrity of an effective transactions.
In addition to high use of digital banking accounts and the high internet use through all channels of the customer experience, different and applicable regulations such as the Gramm-Leach-Bliley Act (GLBA) and Payment Card Industry Data Security Standard (PCI DSS), laws around data protection and regulations through the Federal Reserve and other institutions such as FINRA, have not only prompted BFSI type organizations to strengthen their fraud systems - they have advanced and accelerated their use of sophisticated fraud prevention technology.
For instance, in April 2025, JPMorgan Chase & Co. launched NeuroShield, an AI-driven fraud detection service using behavioral biometrics and real-time analytics to combat digital banking fraud. It was reported that NeuroShield reduced fraud losses by 40% through the pilot project. The announcement highlights North America's significant lead in the adoption of advanced fraud detection and prevention (FDP) solutions, driven by high volumes of digital transactions, stringent regulatory requirements, and substantial capital investments.
Key Players Landscape and Outlook
The Fraud Detection and Prevention (FDP) industry, particularly in the banking, financial services, and insurance (BFSI) sector, strikes a good balance between innovation and competition. This has prompted companies to innovate and invest a significant amount of money in new and emerging technologies to combat complex fraud threats proactively. Companies in this space include major players such as IBM, FICO, SAS, BAE Systems, NICE Actimize, Oracle, SAP, and ACI Worldwide, which have developed AI- and machine learning-based fraud management solutions specifically designed to address the needs of banking and insurance organizations. Solutions are being developed that focus on real-time risk scoring, behavioral biometrics, cloud-native capabilities, and end-to-end fraud analytics. The outlook remains positive; demand for intelligent, scalable, and regulatory-compliant FDP systems continues to grow, especially in the larger regions of North America, Europe and Asia-Pacific. Over the next five years, the competitive landscape will be influenced by several factors, including new strategic alliances, cloud adoption, and AI-enabled solutions, as well as the increasing demand for FDP from fintechs, neobanks, and mid-tier BFSI organisations.
For instance, in June 2025, NICE Ltd. announced that KeyBank, a central US bank-based financial institution, is further enhancing its financial crime operations by implementing its X-Sight AI Enterprise Platform. The X-Sight AI Enterprise Platform is a cutting-edge solution that leverages analytics and AI to address critical issues in fraud detection, compliance, and risk management. The implementation complemented KeyBank's modernization efforts in crime prevention infrastructure. The move reflects a broader trend among large financial institutions to invest in intelligent, scalable fraud prevention technologies.
All segments will be provided for all regions and countries covered
Companies mentioned above DO NOT hold any order as per market share and can be changed as per information available during research work.