Machine Learning in Financial Services Market to Hit $17.82 Bn by 2029 at 35.8% CAGR | The Business Research Company

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The Business Research Company’s Machine Learning in Financial Services Global Market Report 2025 - Market Size, Trends, And Global Forecast 2025-2034

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What Is The Forecast For The Machine Learning In The Financial Services Market From 2024 To 2029?
Over the past few years, the market size of machine learning in financial services has seen rapid expansion. This market is projected to boost from $3.85 billion in 2024 to $5.24 billion in 2025, flourishing at a compound annual growth rate (CAGR) of 36.2%. The substantial growth in the past can be accredited to escalating demands for fraud detection, augmented embracement of automation in financial procedures, growing requirement for customized banking experiences, increased quantity of financial data, and a surge in the utility of digital payment platforms.

The market size of machine learning applied in financial services is projected to experience a rapid increase in the upcoming years. Expected to reach $17.83 billion by 2029, the compound annual growth rate (CAGR) is estimated to be 35.8%. The predicted upturn during this period is due to the growing preference for cloud-based solutions, heightened use of predictive analytics within financial sectors, increasing demand for instantaneous customer insights, expanded use of robo-advisors, and a heightened emphasis on regulatory compliance through automation. Key trends to observe during this period include improvements in explainable artificial intelligence models, the advanced application of machine learning in credit scoring, the creation of autonomous financial advisors, innovation in fraud detection algorithms, and advancements in real-time risk management systems.

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What Are The Core Growth Drivers Shaping The Future Of The Machine Learning In The Financial Services Market?
The shift towards cloud-based solutions is anticipated to boost the advancement of machine learning in the financial services sector. Cloud-based solutions refer to services or tools that can be accessed via the internet, eradicating the need for personal installation or management. The demand for these solutions is on an upswing due to the appeal of remote access; individuals and businesses can utilize vital tools and data from any location, unrestricted by physical boundaries. The adoption of cloud-based solutions bolsters machine learning in financial services by providing an adaptable and scalable framework that enables financial institutions to process large batches of data immediately, launch machine learning models more swiftly, and seamlessly incorporate analytics into their operations to enhance decision-making and risk management processes. For example, Eurostat, a governmental statistical agency based in Luxembourg, disclosed in December 2023 that 42.5% of businesses in the EU utilized cloud computing services, mostly for tasks such as email, file storage, and office software, marking a 4.2% increase from 2021. Consequently, the shift towards cloud-based solutions is contributing to the expansion of machine learning within the financial services sector.

Which Companies Are Currently Leading In The Machine Learning In The Financial Services Market?
Major players in the Machine Learning In The Financial Services Global Market Report 2025 include:
• Amazon Web Services Inc.
• Microsoft Corporation
• Intel Corporation
• Accenture Public Limited Company
• International Business Machines Corporation
• Oracle Corporation
• SAP Societas Europaea
• Salesforce Inc.
• NVIDIA Corporation
• SAS Institute Inc.

What Are The Top Trends In The Machine Learning In The Financial Services Industry?
Leading enterprises in the financial services market utilizing machine learning are adopting cooperative partnership strategies to increase technological capabilities and widen their presence. These strategic alliances are joint agreements between two or more entities to utilize each other's skills and assets to achieve common objectives or growth. For example, in December 2022, Nvidia Corporation, a technology firm based in the US, joined forces with Deutsche Bank AG, an investment banking firm based in Germany. The purpose of this alliance is to accelerate the application of artificial intelligence (AI) and machine learning (ML) within financial services. It aims to enhance operational productivity, fortify risk management, and formulate AI-enabled applications conforming to regulatory norms. This partnership also endorses Deutsche Bank's transition to a cloud-central infrastructure and it fosters innovation through initiatives like virtual avatars and finance-focused language models, with the ultimate goal of delivering faster, smarter, and more customized banking facilities.

Comparative Analysis Of Leading Machine Learning In The Financial Services Market Segments
The machine learning in the financial services market covered in this report is segmented –

1) By Component: Software, Services
2) By Deployment Mode: Cloud, On-Premises
3) By Application: Fraud Detection And Prevention, Risk Management, Customer Analytics, Portfolio Management, Algorithmic Trading, Regulatory Compliance, Chatbots And Virtual Assistants, Loan Underwriting, Insurance Claim Processing
4) By End-User: Banking, Insurance Companies, Investment Firms, Other End-Users

Subsegments:
1) By Software: Fraud Detection Software, Risk Management Software, Algorithmic Trading Software, Customer Analytics Software, Compliance Monitoring Software, Credit Scoring Software
2) By Services: Managed Services, Professional Services, Consulting Services, Training And Support Services, Integration And Implementation Services

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Which Regions Are Dominating The Machine Learning In The Financial Services Market Landscape?
In the 2025 Global Market Report for Machine Learning in the Financial Services, North America leads as the region with the largest market. It is also projected to experience significant growth. The report includes comprehensive coverage of various regions which include Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, and Africa.

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