세계의 금융 AI 시장 : 제품별, 기술별, 용도별, 최종 사용자별, 지역별 예측(-2030년)
AI in Finance Market by Product (Algorithmic Trading, Virtual Assistants, Robo-Advisors, GRC, IDP, Underwriting Tools), Technology, Application (Fraud Detection, Risk Management, Trend Analysis, Financial Planning, Forecasting) - Global Forecast to 2030
상품코드:1594716
리서치사:MarketsandMarkets
발행일:2024년 10월
페이지 정보:영문 393 Pages
라이선스 & 가격 (부가세 별도)
ㅁ Add-on 가능: 고객의 요청에 따라 일정한 범위 내에서 Customization이 가능합니다. 자세한 사항은 문의해 주시기 바랍니다.
한글목차
금융 AI 시장 규모는 2024년 383억 6,000만 달러에서 2030년에는 1,903억 3,000만 달러로 성장하며, 예측 기간 동안 CAGR은 30.6%가 될 것으로 예측됩니다.
채팅봇과 가상 어시스턴트는 고객 서비스의 자동화, 사용자 경험 향상, 운영 비용 절감이 가능하기 때문에 AI를 활용한 금융 시장에서 수요가 높아지고 있습니다. 리스크의 식별과 경감을 강화하고, 보다 안전한 금융 관행을 육성하고, 금융에 있어서 AI 시장을 형성하고 있습니다.
조사 범위
조사 대상년도
2019-2030년
기준년
2023년
예측 기간
2024-2030년
검토 단위
달러(10억 달러)
부문
제품별, 기술별, 용도별, 최종 사용자별, 지역별
대상 지역
북미, 유럽, 아시아태평양, 중동, 아프리카, 라틴아메리카
핀테크 기업은 금융 서비스의 자동화, 고객 경험의 향상, 업무 효율의 향상을 위해 AI를 활용하도록 되어 왔습니다. 효과적인 위험 관리에 필수적입니다. 소비자가 더 빠르고 효율적인 서비스를 요구합니다 핀텍 기업은 부정 감지, 신용 스코어링, 채팅봇을 통한 고객 참여 등의 작업에 AI를 활용하고 있습니다. 이 분야를 향후 수년간 크게 성장시킬 것으로 자리잡고 있습니다.
경제 전체의 급속한 디지털 전환과 핀테크 스타트업의 대두가 아시아태평양의 AI 솔루션을 견인하고 있습니다. 기술에 상당한 투자를 하고 있습니다. 싱가포르 금융관리국(MAS)과 중국 사이버공간관리국(CAC) 등의 규제기관은 혁신을 촉진하고 시장의 성장을 더욱 뒷받침합니다. 리스크 관리 솔루션의 필요성은 금융에 AI의 급속한 도입에 기여하고 있으며 아시아태평양을 이 분야의 리더로 자리매김하고 있습니다.
본 보고서에서는 세계 금융의 AI 시장에 대해 조사했으며, 제품별, 기술별, 용도별, 최종 사용자별, 지역별 동향 및 시장 진출기업 프로파일 등을 정리했습니다.
목차
제1장 서론
제2장 조사 방법
제3장 주요 요약
제4장 중요 인사이트
제5장 시장 개요와 업계 동향
소개
시장 역학
금융에 있어서의 AI 시장의 진화
공급망 분석
생태계 분석
사례 연구 분석
기술 분석
2024-2025년의 주된 회의와 이벤트
투자와 자금조달 시나리오
규제 상황
특허 분석
가격 분석
Porter's Five Forces 분석
고객사업에 영향을 주는 동향/혼란
주요 이해관계자와 구매 기준
금융에 있어서의 AI 시장에 대한 생성형 AI의 영향
제6장 금융에 있어서의 AI 시장(제품별)
소개
유형
전개 모드
제7장 금융에 있어서의 AI 시장(기술별)
소개
생성형 AI
기타
제8장 금융에 있어서의 AI 시장(용도별)
소개
비즈니스 운영으로서의 금융
비즈니스 기능으로서의 금융
제9장 금융에 있어서의 AI 시장(최종사용자별)
소개
최종 사용자
비즈니스 운영으로서의 금융
제10장 금융에 있어서의 AI 시장(지역별)
소개
북미
유럽
아시아태평양
중동 및 아프리카
라틴아메리카
제11장 경쟁 구도
개요
주요 참가 기업의 전략/비책, 2020-2024년
수익 분석, 2019-2023년
시장 점유율 분석, 2023년
제품 비교
주요 벤더의 기업 평가 및 재무 지표
기업평가 매트릭스: 주요 진입기업, 2023년
기업평가 매트릭스: 스타트업/중소기업, 2023년
경쟁 시나리오
제12장 기업 프로파일
소개
주요 진출기업
FIS
FISERV
GOOGLE
MICROSOFT
ZOHO
IBM
SOCURE
WORKIVA
PLAID
C3 AI
HIGHRADIUS
SAP
AWS
HPE
ORACLE
SALESFORCE
INTEL
NVIDIA
NETAPP
DATAROBOT
ENOVA INTERNATIONAL
ALPHASENSE
OCROLUS
VECTRA AI
TERADATA
PEGA
VENA SOLUTIONS
AFFIRM
SYMPHONYAI
ENVESTNET|YODLEE
스타트업/중소기업
ADDEPTO
DEEPER INSIGHTS
H2O.AI
APP0
UNDERWRITE.AI
DEEPGRAM
EMAGIA
INDATA LABS
ZEST AI
SCIENAPTIC AI
GRADIENT AI
KASISTO
TRUMID
DATAVISOR
KAVOUT
WEALTHBLOCK
제13장 인접 시장과 관련 시장
제14장 부록
JHS
영문 목차
영문목차
The AI in Finance market is projected to grow from USD 38.36 billion in 2024 to USD 190.33 billion by 2030, at a compound annual growth rate (CAGR) of 30.6% during the forecast period. Chatbots and virtual assistants are in demand in the AI-driven finance market due to the ability to automate customer service, enhance user experience, and reduce operational costs. The rising demand of AI-powered algorithms enhance risk identification and mitigation, fostering safer financial practices is shaping the AI in Finance market.
Scope of the Report
Years Considered for the Study
2019-2030
Base Year
2023
Forecast Period
2024-2030
Units Considered
USD (Billion)
Segments
Product type, Technology, Application, End user, and Region
Regions covered
North America, Europe, Asia Pacific, Middle East & Africa, Latin America
"By end user as business operation, Fintech segment registers the highest CAGR during the forecast period."
Fintech companies are increasingly leveraging AI to automate financial services, enhance customer experiences, and improve operational efficiency. This technology enables real-time data analysis, which is crucial for personalized financial solutions and effective risk management. As consumers demand faster and more efficient services, fintech firms are utilizing AI for tasks such as fraud detection, credit scoring, and customer engagement through chatbots. The continuous innovation and competitive landscape in fintech drive the need for sophisticated AI solutions, positioning this segment for substantial growth in the coming years.
"By region, Asia Pacific to register the highest CAGR market during the forecast period." Rapid digital transformation across economies and the rise of fintech startups are driving AI solutions in Asia Pacific. Countries like China and India are investing heavily in AI technologies to enhance financial services and improve customer experiences. The region's vast consumer base presents major opportunities of customized financial products and services. Regulatory bodies such as Monetary Authority of Singapore (MAS) and Cyberspace Administration of China (CAC) promote innovation and further boost market growth. The increasing focus on data-driven decision-making and the need for efficient risk management solutions also contribute to the rapid adoption of AI in finance, positioning Asia-Pacific as a leader in this sector.
Breakdown of primaries
In-depth interviews were conducted with Chief Executive Officers (CEOs), innovation and technology directors, system integrators, and executives from various key organizations operating in the AI in Finance market.
By Company: Tier I: 35%, Tier II: 45%, and Tier III: 20%
By Designation: C-Level: 35%, Director Level: 25%, and Others: 40%
By Region: North America: 40%, Europe: 25%, Asia Pacific: 20%, Middle East & Africa: 10%, and Latin America: 5%.
FIS (US), Fiserv (US), Google (US), Microsoft (US), Zoho (India), IBM (US), Socure (US), Workiva (US), Plaid (US), SAS (US), C3 AI (US); are some of the key players in the AI in Finance market.
The study includes an in-depth competitive analysis of these key players in the AI in Finance market, including their company profiles, recent developments, and key market strategies.
Research Coverage
This research report categorizes the AI in Finance market by product type (ERP and financial services, chatbots and virtual assistants, automated reconciliation solutions, intelligent document processing, governance, risk and compliance (GRC) software, accounts payable/receivable automation software, robo-advisors, expense management systems, compliance automation platforms, algorithmic trading platforms, underwriting engines/platforms), by deployment mode (cloud and on-premises), by technology (generative AI, NLP and predictive analytics), by application (Business operation (fraud detection and prevention, risk management, customer service & engagement, financial compliance & regulatory reporting, investment & portfolio management) Business function (financial planning & forecasting, automated bookkeeping & reconciliation, procurement & supply chain finance, revenue cycle management), by End user (Enterprise as business function (government & public sectors, retail & ecommerce, real estate, manufacturing, telecom & media, healthcare & pharma, utilities, technology & software) Enterprise as business operation (banking, insurance, investment & asset management, fintech, accounting & auditing firms, capital markets/regtech, payments & cards/payment processing) and by region (North America, Europe, Asia Pacific, Middle East & Africa, and Latin America). The scope of the report covers detailed information regarding the major factors, such as drivers, restraints, challenges, and opportunities, influencing the growth of the AI in Finance market. A detailed analysis of the key industry players has been done to provide insights into their business overview, solutions and services, key strategies, Contracts, partnerships, and agreements. new product & service launches, mergers and acquisitions, and recent developments associated with the AI in Finance market. Competitive analysis of upcoming startups in the AI in Finance market ecosystem is covered in this report.
Key Benefits of Buying the Report
The report will help the market leaders/new entrants in this market with information on the closest approximations of the revenue numbers for the overall AI in Finance market and the subsegments. This report will help stakeholders understand the competitive landscape and gain more insights to position their businesses better and to plan suitable go-to-market strategies. The report also helps stakeholders understand the pulse of the market and provides them with information on key market drivers, restraints, challenges, and opportunities.
The report provides insights on the following pointers:
Analysis of key drivers (AI-powered algorithms enhance risk identification and mitigation, fostering safer financial practices, AI-driven chatbots and virtual assistants enhance customer service experiences, making financial advice more accessible, machine learning models provide accurate forecasts which help in strategic planning and investment decisions), restraints (the possibility of bias and issues related to the ethical use of data), opportunities (rise in demand for hyper-personalization of financial products and tailoring services to individual customer needs and preferences for long-term engagement), and challenges (Safeguarding data to prevent breaches and regulatory violations) influencing the growth of the AI in Finance market.
Product Development/Innovation: Detailed insights on upcoming technologies, research & development activities, and new product & service launches in the AI in Finance market
Market Development: Comprehensive information about lucrative markets - the report analyses the AI in Finance market across varied regions.
Market Diversification: Exhaustive information about new products & services, untapped geographies, recent developments, and investments in the AI in Finance market
Competitive Assessment: In-depth assessment of market shares, growth strategies and service offerings of leading players FIS (US), Fiserv (US), Google (US), Microsoft (US), Zoho (India), IBM (US), Socure (US), Workiva (US), Plaid (US), SAS (US), C3 AI (US) among others in AI in Finance market.
TABLE OF CONTENTS
1 INTRODUCTION
1.1 STUDY OBJECTIVES
1.2 MARKET DEFINITION
1.2.1 INCLUSIONS AND EXCLUSIONS
1.3 MARKET SCOPE
1.3.1 MARKET SEGMENTATION
1.3.2 YEARS CONSIDERED
1.4 CURRENCY CONSIDERED
1.5 STAKEHOLDERS
2 RESEARCH METHODOLOGY
2.1 RESEARCH DATA
2.1.1 SECONDARY DATA
2.1.2 PRIMARY DATA
2.1.2.1 Breakup of primary profiles
2.1.2.2 Key industry insights
2.2 DATA TRIANGULATION
2.3 MARKET SIZE ESTIMATION
2.3.1 TOP-DOWN APPROACH
2.3.2 BOTTOM-UP APPROACH
2.4 MARKET FORECAST
2.5 RESEARCH ASSUMPTIONS
2.6 RISK ASSESSMENT
2.7 RESEARCH LIMITATIONS
3 EXECUTIVE SUMMARY
4 PREMIUM INSIGHTS
4.1 ATTRACTIVE OPPORTUNITIES FOR PLAYERS IN AI IN FINANCE MARKET
4.2 AI IN FINANCE MARKET: TOP THREE APPLICATIONS
4.3 NORTH AMERICA: AI IN FINANCE MARKET, BY DEPLOYMENT MODE AND END USER
4.4 AI IN FINANCE MARKET, BY REGION
5 MARKET OVERVIEW AND INDUSTRY TRENDS
5.1 INTRODUCTION
5.2 MARKET DYNAMICS
5.2.1 DRIVERS
5.2.1.1 Increasing demand for precise forecasts for strategic planning and investment
5.2.1.2 Growing adoption of AI algorithms to enhance risk detection and mitigation
5.2.1.3 Rising popularity of personalized financial services
5.2.2 RESTRAINTS
5.2.2.1 Concerns regarding bias and ethical data use
5.2.3 OPPORTUNITIES
5.2.3.1 Growing need for hyper-personalized financial products for long-term customer engagement and tailored services
5.2.3.2 Rising demand for accurate credit scoring and better risk management
5.2.4 CHALLENGES
5.2.4.1 Ensuring data security to prevent breaches or violations
