세계의 금융 서비스용 머신러닝 시장 보고서(2025년)
Machine Learning In The Financial Services Global Market Report 2025
상품코드 : 1822991
리서치사 : The Business Research Company
발행일 : On Demand Report
페이지 정보 : 영문 250 Pages
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한글목차

금융 서비스용 머신러닝 시장 규모는 향후 수년간 비약적인 성장이 예상됩니다. 2029년 연평균 복합 성장률(CAGR)은 35.8%를 나타내 178억 3,000만 달러로 성장할 전망입니다. 예측 기간에는 클라우드 기반 솔루션에 대한 선호도 증가, 금융 예측 분석 이용 증가, 실시간 고객 인사이트력에 대한 수요 증가, 로보 어드바이저의 광범위한 채용, 자동화를 통한 규제 준수에 대한 주력 강화 등이 성장으로 이어질 것으로 예측됩니다. 향후 예상되는 주요 동향으로는 설명 가능한 인공지능 모델의 진보, 신용 스코어링에 있어서의 머신러닝의 응용 강화, 자율형 파이낸셜 어드바이저의 출현, 부정 검지 알고리즘의 혁신, 리얼타임 리스크 관리 시스템의 진보 등을 들 수 있습니다.

클라우드 기반 솔루션에 대한 선호도 증가는 금융 서비스용 머신러닝 시장 확대를 촉진할 것으로 예측됩니다. 클라우드 기반 솔루션은 인터넷에서 제공되는 서비스와 도구로, 로컬로 설치 및 관리할 필요가 없습니다. 클라우드 기반 솔루션의 채택이 증가하고 있는 이유는 원격 액세스에 대한 수요가 커서 개인이나 기업이 필요한 도구와 데이터에 어디서나 액세스할 수 있도록 하기 때문입니다. 금융 서비스를 사용하면 클라우드 기반 솔루션이 유연하고 확장 가능한 인프라를 제공함으로써 금융 기관은 방대한 양의 데이터를 실시간으로 처리하고 머신러닝 모델을 보다 신속하게 배포하고 의사결정 및 위험 관리를 개선하기 위해 분석을 업무에 원활하게 통합할 수 있습니다. 예를 들어, 룩셈부르크에 본사를 둔 정부 통계기관 유로스타트는 2023년 12월 EU 기업의 42.5%가 클라우드 컴퓨팅 서비스를 주로 이메일, 파일 스토리지, 오피스 소프트웨어에 이용했으며, 2021년부터 4.2% 증가했다고 보고했습니다. 이 추세는 금융 서비스 분야에서 머신러닝 애플리케이션의 성장에 박차를 가하고 있습니다.

금융 서비스용 머신러닝 분야의 기업은 기술력을 강화하고 시장에서의 존재감을 높이기 위해 전략적 파트너십을 연결하는 경우가 늘고 있습니다. 이러한 파트너십은 상호 성장을 위해 자원과 전문 지식을 모아 활용하는 조직 간의 협력을 수반합니다. 예를 들어 2022년 12월 독일을 거점으로 하는 투자은행 회사인 독일은행 AG는 미국을 거점으로 하는 기술기업의 엔비디아 코퍼레이션과 제휴하여 금융 서비스용 인공지능(AI)과 머신러닝(ML)의 이용을 확대했습니다. 이 제휴는 업무 효율성 개선, 리스크 관리 강화, 규제 요건을 준수하는 AI 기반 애플리케이션 개발에 중점을 둡니다. 또한 독일 은행의 클라우드 기반 인프라로의 전환을 지원하고, 가상 아바타 및 금융 언어 모델 등의 이니셔티브를 통해 혁신을 촉진하고, 보다 스마트하고 신속하며 개인화된 뱅킹 서비스 제공을 목표로 합니다.

목차

제1장 주요 요약

제2장 시장 특징

제3장 시장 동향과 전략

제4장 시장 : 금리, 인플레이션, 지정학, 무역전쟁과 관세, 그리고 코로나 및 회복이 시장에 미치는 영향을 포함한 거시경제 시나리오

제5장 세계의 성장 분석과 전략 분석 프레임워크

제6장 시장 세분화

제7장 지역별/국가별 분석

제8장 아시아태평양 시장

제9장 중국 시장

제10장 인도 시장

제11장 일본 시장

제12장 호주 시장

제13장 인도네시아 시장

제14장 한국 시장

제15장 서유럽 시장

제16장 영국 시장

제17장 독일 시장

제18장 프랑스 시장

제19장 이탈리아 시장

제20장 스페인 시장

제21장 동유럽 시장

제22장 러시아 시장

제23장 북미 시장

제24장 미국 시장

제25장 캐나다 시장

제26장 남미 시장

제27장 브라질 시장

제28장 중동 시장

제29장 아프리카 시장

제30장 경쟁 구도와 기업 프로파일

제31장 기타 주요 기업 및 혁신 기업

제32장 세계 시장 경쟁 벤치마킹과 대시보드

제33장 주요 인수합병(M&A)

제34장 최근 시장 동향

제35장 시장의 잠재력이 높은 국가, 부문, 전략

제36장 부록

KTH
영문 목차

영문목차

Machine learning in financial services involves the application of advanced algorithms and statistical models that allow systems to learn from historical data and make predictions or decisions without explicit programming. It enables financial institutions to enhance efficiency, accuracy, and decision-making by detecting patterns, automating tasks, and delivering personalized services.

The core components of machine learning in financial services are software and services. Software comprises platforms and tools for building, deploying, and managing machine learning models, available through both cloud-based and on-premises deployment. These solutions support a wide range of applications, such as fraud detection and prevention, risk management, customer analytics, portfolio management, algorithmic trading, regulatory compliance, chatbots and virtual assistants, loan underwriting, and insurance claim processing. The technology serves diverse end users, including banks, insurance providers, investment firms, and others.

Note that the outlook for this market is being affected by rapid changes in trade relations and tariffs globally. The report will be updated prior to delivery to reflect the latest status, including revised forecasts and quantified impact analysis. The report's Recommendations and Conclusions sections will be updated to give strategies for entities dealing with the fast-moving international environment.

The rapid escalation of U.S. tariffs and the resulting trade tensions in spring 2025 are significantly impacting the financial sector, particularly in investment strategies and risk management. Heightened tariffs have fueled market volatility, prompting cautious behavior among institutional investors and increasing demand for hedging instruments. Banks and asset managers are facing higher costs associated with cross-border transactions, as tariffs disrupt global supply chains and dampen corporate earnings, key drivers of equity market performance. Insurance companies, meanwhile, are grappling with increased claims risks tied to supply chain disruptions and trade-related business losses. Additionally, reduced consumer spending and weakened export demand are constraining credit growth and investment appetite. The sector must now prioritize diversification, digital transformation, and robust scenario planning to navigate the heightened economic uncertainty and protect profitability.

The machine learning in the financial services market research report is one of a series of new reports from The Business Research Company that provides machine learning in the financial services market statistics, including machine learning in the financial services industry's global market size, regional shares, competitors with a machine learning in the financial services market share, detailed machine learning in the financial services market segments, market trends and opportunities, and any further data you may need to thrive in the machine learning in the financial services industry. This machine learning in the financial services market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenario of the industry.

The machine learning in the financial services market size has grown exponentially in recent years. It will grow from $3.85 billion in 2024 to $5.24 billion in 2025 at a compound annual growth rate (CAGR) of 36.2%. The growth in the historic period was driven by the rising need for fraud detection, greater adoption of automation in financial operations, growing demand for personalized banking experiences, the expanding volume of financial data, and the increasing use of digital payment platforms.

The machine learning in the financial services market size is expected to see exponential growth in the next few years. It will grow to $17.83 billion in 2029 at a compound annual growth rate (CAGR) of 35.8%. In the forecast period, growth is expected to stem from the growing preference for cloud-based solutions, increased use of predictive analytics in finance, rising demand for real-time customer insights, wider adoption of robo-advisors, and a stronger focus on regulatory compliance through automation. Key trends anticipated include advancements in explainable artificial intelligence models, enhanced application of machine learning in credit scoring, the emergence of autonomous financial advisors, innovations in fraud detection algorithms, and progress in real-time risk management systems.

The growing preference for cloud-based solutions is expected to drive the expansion of machine learning in the financial services market. Cloud-based solutions are internet-delivered services or tools that eliminate the need for local installation or management. Their rising adoption is largely due to the demand for remote access, enabling individuals and businesses to access essential tools and data from any location. In financial services, cloud-based solutions provide flexible and scalable infrastructure, allowing institutions to process vast amounts of data in real time, deploy machine learning models more quickly, and seamlessly integrate analytics into operations for improved decision-making and risk management. For example, in December 2023, Eurostat, a Luxembourg-based governmental statistical agency, reported that 42.5% of EU enterprises used cloud computing services in 2023-primarily for email, file storage, and office software-marking a 4.2% increase from 2021. This trend is fueling the growth of machine learning applications in the financial services sector.

Companies in the machine learning in financial services market are increasingly forming strategic partnerships to strengthen technological capabilities and broaden market presence. Such partnerships involve collaboration between organizations to leverage combined resources and expertise for mutual growth. For instance, in December 2022, Deutsche Bank AG, a Germany-based investment banking company, partnered with Nvidia Corporation, a US-based technology company, to expand the use of artificial intelligence (AI) and machine learning (ML) in financial services. The partnership focuses on improving operational efficiency, enhancing risk management, and developing AI-powered applications that comply with regulatory requirements. It also supports Deutsche Bank's transition to cloud-based infrastructure and fosters innovation through initiatives such as virtual avatars and financial language models, aimed at delivering smarter, faster, and more personalized banking services.

In December 2024, Mastercard Inc., a US-based credit card company, acquired Recorded Future for an undisclosed amount. This acquisition seeks to strengthen Mastercard's cybersecurity and fraud detection capabilities by incorporating Recorded Future's machine learning-powered threat intelligence platform. The integration enables financial institutions and digital businesses to proactively detect, evaluate, and address cyber threats, thereby enhancing trust and security across Mastercard's global payment ecosystem. Recorded Future Inc., based in the US, specializes in cybersecurity and threat intelligence solutions designed for the financial services industry.

Major players in the machine learning in the financial services market are 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., Palantir Technologies Inc., Fair Isaac Corporation, HighRadius Corporation, Upstart Holdings Inc., DataRobot Inc., Ocrolus Inc., Feedzai Inc., H2O.ai Inc., ZestFinance Inc., and Overbond Ltd.

North America was the largest region in the machine learning in the financial services market in 2024. The regions covered in machine learning in the financial services report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East and Africa.

The countries covered in the machine learning in the financial services market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

The machine learning in the financial services market consists of revenues earned by entities by providing services such as financial forecasting, regulatory compliance support, portfolio optimization, and transaction monitoring. Values in this market are 'factory gate' values, that is the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.

Machine Learning In The Financial Services Global Market Report 2025 from The Business Research Company provides strategists, marketers and senior management with the critical information they need to assess the market.

This report focuses on machine learning in the financial services market which is experiencing strong growth. The report gives a guide to the trends which will be shaping the market over the next ten years and beyond.

Reasons to Purchase

Where is the largest and fastest growing market for machine learning in the financial services ? How does the market relate to the overall economy, demography and other similar markets? What forces will shape the market going forward, including technological disruption, regulatory shifts, and changing consumer preferences? The machine learning in the financial services market global report from the Business Research Company answers all these questions and many more.

The report covers market characteristics, size and growth, segmentation, regional and country breakdowns, competitive landscape, market shares, trends and strategies for this market. It traces the market's historic and forecast market growth by geography.

The forecasts are made after considering the major factors currently impacting the market. These include the technological advancements such as AI and automation, Russia-Ukraine war, trade tariffs (government-imposed import/export duties), elevated inflation and interest rates.

Scope

Table of Contents

1. Executive Summary

2. Machine Learning In The Financial Services Market Characteristics

3. Machine Learning In The Financial Services Market Trends And Strategies

4. Machine Learning In The Financial Services Market - Macro Economic Scenario Including The Impact Of Interest Rates, Inflation, Geopolitics, Trade Wars and Tariffs, And Covid And Recovery On The Market

5. Global Machine Learning In The Financial Services Growth Analysis And Strategic Analysis Framework

6. Machine Learning In The Financial Services Market Segmentation

7. Machine Learning In The Financial Services Market Regional And Country Analysis

8. Asia-Pacific Machine Learning In The Financial Services Market

9. China Machine Learning In The Financial Services Market

10. India Machine Learning In The Financial Services Market

11. Japan Machine Learning In The Financial Services Market

12. Australia Machine Learning In The Financial Services Market

13. Indonesia Machine Learning In The Financial Services Market

14. South Korea Machine Learning In The Financial Services Market

15. Western Europe Machine Learning In The Financial Services Market

16. UK Machine Learning In The Financial Services Market

17. Germany Machine Learning In The Financial Services Market

18. France Machine Learning In The Financial Services Market

19. Italy Machine Learning In The Financial Services Market

20. Spain Machine Learning In The Financial Services Market

21. Eastern Europe Machine Learning In The Financial Services Market

22. Russia Machine Learning In The Financial Services Market

23. North America Machine Learning In The Financial Services Market

24. USA Machine Learning In The Financial Services Market

25. Canada Machine Learning In The Financial Services Market

26. South America Machine Learning In The Financial Services Market

27. Brazil Machine Learning In The Financial Services Market

28. Middle East Machine Learning In The Financial Services Market

29. Africa Machine Learning In The Financial Services Market

30. Machine Learning In The Financial Services Market Competitive Landscape And Company Profiles

31. Machine Learning In The Financial Services Market Other Major And Innovative Companies

32. Global Machine Learning In The Financial Services Market Competitive Benchmarking And Dashboard

33. Key Mergers And Acquisitions In The Machine Learning In The Financial Services Market

34. Recent Developments In The Machine Learning In The Financial Services Market

35. Machine Learning In The Financial Services Market High Potential Countries, Segments and Strategies

36. Appendix

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