세계의 핀테크 AI 시장 보고서 : 유형, 전개 모델, 용도, 지역별(2024-2032년)

The global AI in fintech market size reached US$ 14.6 Billion in 2023. Looking forward, IMARC Group expects the market to reach US$ 87.7 Billion by 2032, exhibiting a growth rate (CAGR) of 20.9% during 2024-2032. The rapid technological advancements, rising demand for regulatory compliances, growing demand for personalized services, widespread adoption of AI in fintech to mitigate financial risks, increasing incidence of cyber fraud, and rising utilization of AI in fintech to automate financial processes are some of the major factors propelling the AI in fintech market growth.

AI in Fintech Market Analysis:

• Market Growth and Size: The market is witnessing robust growth on account of the increasing demand for automation, along with the rising need to improve risk management.
• Technological Advancements: The integration of advanced technologies, such as machine learning (ML) algorithms, natural language processing (NLP), and predictive analytics, is offering a positive market outlook.
• Industry Applications: AI finds applications in various segments of the financial industry, including banking, insurance, wealth management, and trading.
• Geographical Trends: North America leads the market, driven by the presence of major tech companies. However, Asia Pacific is emerging as a fast-growing market due to the increasing investments in AI technology.
• Competitive Landscape: Partnerships between traditional financial institutions and technology companies are propelling the market growth.
• Challenges and Opportunities: While the market faces challenges, such as data privacy concerns, it also encounters opportunities due to the rising focus on fraud detection.
• Future Outlook: The future of the AI in fintech market looks promising, with the expansion of AI-powdered chatbots. Additionally, the increasing focus on developing ethical AI frameworks is expected to propel the market growth.

AI in Fintech Market Trends:

The rapid technological advancements

The integration of AI in fintech is heavily influenced by ongoing technological advancements. In line with this, the integration of machine learning (ML) algorithms to refine big data analytics and expand its potential applications within the financial sector is boosting the market growth. Furthermore, these innovations enable the accurate processing and interpretation of vast amounts of data at high speeds, providing real-time insights and automation capabilities. Moreover, the development of quantum computing and cloud technologies, which further enhance the computational power necessary for complex financial modeling, is fueling the market growth. Besides this, fintech companies are leveraging these advanced technologies to create personalized banking experiences, automated trading, and manage risks with unprecedented precision. In addition, technological advancements are not only driving efficiency but also opening doors to entirely new products and services.

The rising demand for regulatory compliance

The financial industry operates under a complex set of regulations that vary across jurisdictions. Compliance with these regulations is not just mandatory but also critical to maintaining consumer trust and the overall integrity of the financial system. In line with this, AI in fintech plays a vital role in ensuring regulatory compliance and automatically monitoring and analyzing millions of transactions to detect anomalies or non-compliance with relevant laws. Along with this, the integration of natural language processing (NLP) to interpret the ever-changing regulatory texts, ensuring that financial institutions are always up-to-date with the latest requirements, is positively influencing the market growth. Additionally, the automation of compliance processes reduces the potential for human error and enables a more responsive and adaptable approach to regulatory changes.

The growing demand for personalized services

The increasing consumer expectation for personalized experiences across all service sectors, including finance, is propelling the market growth. AI plays a crucial role in meeting this demand by analyzing vast amounts of customer data and identifying individual preferences, spending habits, and financial needs. Furthermore, this information is used to tailor financial products, offers, and advice to each customer. In addition, AI enables financial institutions to provide a personalized investment strategy or individualized loan offers through levels of customization that were previously unattainable. Apart from this, the widespread utilization of AI is aiding in enhancing customer loyalty, increasing engagement, and improving overall satisfaction. As a result, the adoption of AI in creating tailored financial solutions is not merely a trend but a fundamental shift in the way financial services are delivered.

AI in Fintech Industry Segmentation:

IMARC Group provides an analysis of the key trends in each segment of the global AI in fintech market report, along with AI in fintech market forecast at the global, regional and country levels from 2024-2032. Our report has categorized the market based on type, deployment model and application.

Breakup by Type:

• Solutions
• Services

Solutions dominate the market

The report has provided a detailed breakup and analysis of the market based on the type. This includes solutions and services. According to the report, solutions represented the largest segment.

AI solutions are dominating the market as they are designed to meet specific challenges within the financial industry, such as fraud detection, risk management, and customer service. Furthermore, they provide personalized service offerings, resulting in improved customer engagement and satisfaction. They also assist in understanding customer behavior and predicting their needs, thus facilitating tailored products and services. Apart from this, AI solutions are designed to integrate seamlessly with existing financial systems, which allows organizations to adopt AI without major overhauls, reducing resistance and encouraging adoption. Additionally, they can be scaled according to the business needs and market dynamics, which allows companies to grow and adapt without significant additional investment in technology. Moreover, AI solutions lead to cost savings by automating routine tasks and optimizing operational workflows.

Breakup by Deployment Model:

• Cloud-based
• On-premises

Cloud-based dominates the market

The report has provided a detailed breakup and analysis of the market based on the deployment model. This includes cloud-based and on-premises. According to the report, cloud-based represented the largest segment.

Cloud-based models offer a cost-effective solution as they reduce the need for physical infrastructure, facilitating the shift towards an operational expenditure model. Furthermore, they allow financial institutions to easily scale their AI applications according to demand. Additionally, cloud-based AI solutions provide access from anywhere with an internet connection, which enables a more flexible working environment for employees and allows for real-time global collaboration. Apart from this, they allow rapid implementation and iteration, enabling financial institutions to stay ahead in a fast-moving industry. Moreover, cloud providers have robust security measures and can assist with compliance requirements. In addition, cloud-based AI solutions offer smoother integration with existing systems and other cloud services, which enables financial organizations to create a cohesive technology ecosystem without significant customization or compatibility challenges.

Breakup by Application:

• Virtual Assistant (Chatbots)
• Credit Scoring
• Quantitative and Asset Management
• Fraud Detection
• Others

The report has provided a detailed breakup and analysis of the market based on the application. This includes virtual assistant (chatbots), credit scoring, quantitative and asset management, fraud detection, and others.

Virtual assistants powered by AI can meet various customer expectations by providing constant customer service, handling inquiries, and resolving issues in real time. In addition, they can significantly reduce the labor costs associated with customer support by handling a high volume of queries simultaneously, thus freeing human resources to focus on more complex tasks. Furthermore, virtual assistants can provide personalized responses based on user profiles and past interactions. This level of personalization fosters a more engaging and satisfying customer experience.

AI plays a crucial role in the credit scoring process as it can analyze vast amounts of data, including historical credit information, transaction history, and social media behavior, allowing for a more comprehensive and accurate assessment of an individual's or business's creditworthiness. Furthermore, AI-driven credit scoring provides results in a matter of seconds, thus enabling faster loan approvals and enhancing customer satisfaction. Besides this, it can be tailored to suit the specific requirements and risk appetites of individual financial institutions.

Breakup by Region:

• North America
  • United States
  • Canada
• Asia-Pacific
  • China
  • Japan
  • India
  • South Korea
  • Australia
  • Indonesia
  • Others
• Europe
  • Germany
  • France
  • United Kingdom
  • Italy
  • Spain
  • Russia
  • Others
• Latin America
  • Brazil
  • Mexico
  • Others
• Middle East and Africa

North America exhibits a clear dominance in the market, accounting for the largest AI in fintech market share

The report has also provided a comprehensive analysis of all the major regional markets, which includes North America (the United States and Canada); Asia Pacific (China, Japan, India, South Korea, Australia, Indonesia, and others); Europe (Germany, France, the United Kingdom, Italy, Spain, and others); Latin America (Brazil, Mexico, and others); and the Middle East and Africa. According to the report, North America represented the largest market segment.

North America hosts numerous technological innovation centers that foster a culture of innovation and entrepreneurship, leading to the development of cutting-edge AI technologies. In addition, the region has witnessed significant investment in research and development (R&D) initiatives from both private and public sectors to drive technological advancements and the commercialization of AI within fintech. Apart from this, North America's well-established financial industry, which provides a fertile ground for integrating AI, is positively influencing the market growth. Besides this, the imposition of supportive policies and regulations by regional governments, encouraging the responsible use of AI, is boosting the market growth. Moreover, the easy availability of skilled professionals with expertise in AI, ML, and data science is further bolstering the market growth.

Competitive Landscape:

Top firms are exploring new algorithms, methodologies, and technologies that can drive efficiency, security, and personalization in financial services. They are engaging in strategic partnerships with fintech startups and tech companies to develop cutting-edge solutions and foster innovation. Furthermore, several key players are implementing predictive analytics and machine learning (ML) models to provide insights into customer behavior, market trends, and risk management. In addition, top market companies are creating personalized services and products tailored to individual needs and preferences, including personalized banking, investment advice, and customized marketing strategies. Apart from this, leading firms are actively working to develop transparent and unbiased AI models, emphasizing ethical AI practices. Moreover, they are leveraging AI to provide financial services to underserved populations, using algorithms to assess creditworthiness differently or provide financial literacy through AI-driven tools.

The report has provided a comprehensive analysis of the competitive landscape in the market. Detailed profiles of all major companies have also been provided. Some of the key players in the market include:

• Amazon Web Services Inc. (Amazon.com Inc)
• Google LLC (Alphabet Inc.)
• Inbenta Technologies Inc.
• Intel Corporation
• International Business Machines Corporation
• Microsoft Corporation
• Salesforce.com Inc.
• Samsung Electronics Co. Ltd.
• TIBCO Software Inc.
• Trifacta
• Verint Systems Inc.

Recent Developments:

• In June 2023, Amazon Web Services Inc. (Amazon.com Inc) partnered with NVIDIA to launch the "Global FinTech Accelerator" program to jump-start early-stage fintech startups leveraging AI.
• In June 2023, Google LLC (Alphabet Inc.) launched Anti Money Laundering AI (AML AI) to help global financial institutions more effectively and efficiently detect money laundering.
• In January 2023, Inbenta Technologies Inc. secured US$ 40 Million to develop a comprehensive platform that tailors AI-driven solutions across industries, such as financial services, travel, e-commerce, insurance, etc.

Key Questions Answered in This Report

• 1. How big is the global AI in fintech market?
• 2. What is the expected growth rate of the global AI in fintech market during 2024-2032?
• 3. What are the key factors driving the global AI in fintech market?
• 4. What has been the impact of COVID-19 on the global AI in fintech market?
• 5. What is the breakup of the global AI in fintech market based on the type?
• 6. What is the breakup of the global AI in fintech market based on the deployment model?
• 7. What are the key regions in the global AI in fintech market?
• 8. Who are the key players/companies in the global AI in fintech market?

Table of Contents

1 Preface

2 Scope and Methodology

• 2.1 Objectives of the Study
• 2.2 Stakeholders
• 2.3 Data Sources
  • 2.3.1 Primary Sources
  • 2.3.2 Secondary Sources
• 2.4 Market Estimation
  • 2.4.1 Bottom-Up Approach
  • 2.4.2 Top-Down Approach
• 2.5 Forecasting Methodology

3 Executive Summary

4 Introduction

• 4.1 Overview
• 4.2 Key Industry Trends

5 Global AI in Fintech Market

• 5.1 Market Overview
• 5.2 Market Performance
• 5.3 Impact of COVID-19
• 5.4 Market Forecast

6 Market Breakup by Type

• 6.1 Solutions
  • 6.1.1 Market Trends
  • 6.1.2 Market Forecast
• 6.2 Services
  • 6.2.1 Market Trends
  • 6.2.2 Market Forecast

7 Market Breakup by Deployment Model

• 7.1 Cloud-based
  • 7.1.1 Market Trends
  • 7.1.2 Market Forecast
• 7.2 On-premises
  • 7.2.1 Market Trends
  • 7.2.2 Market Forecast

8 Market Breakup by Application

• 8.1 Virtual Assistant (Chatbots)
  • 8.1.1 Market Trends
  • 8.1.2 Market Forecast
• 8.2 Credit Scoring
  • 8.2.1 Market Trends
  • 8.2.2 Market Forecast
• 8.3 Quantitative and Asset Management
  • 8.3.1 Market Trends
  • 8.3.2 Market Forecast
• 8.4 Fraud Detection
  • 8.4.1 Market Trends
  • 8.4.2 Market Forecast
• 8.5 Others
  • 8.5.1 Market Trends
  • 8.5.2 Market Forecast

9 Market Breakup by Region

• 9.1 North America
  • 9.1.1 United States
    • 9.1.1.1 Market Trends
    • 9.1.1.2 Market Forecast
  • 9.1.2 Canada
    • 9.1.2.1 Market Trends
    • 9.1.2.2 Market Forecast
• 9.2 Asia-Pacific
  • 9.2.1 China
    • 9.2.1.1 Market Trends
    • 9.2.1.2 Market Forecast
  • 9.2.2 Japan
    • 9.2.2.1 Market Trends
    • 9.2.2.2 Market Forecast
  • 9.2.3 India
    • 9.2.3.1 Market Trends
    • 9.2.3.2 Market Forecast
  • 9.2.4 South Korea
    • 9.2.4.1 Market Trends
    • 9.2.4.2 Market Forecast
  • 9.2.5 Australia
    • 9.2.5.1 Market Trends
    • 9.2.5.2 Market Forecast
  • 9.2.6 Indonesia
    • 9.2.6.1 Market Trends
    • 9.2.6.2 Market Forecast
  • 9.2.7 Others
    • 9.2.7.1 Market Trends
    • 9.2.7.2 Market Forecast
• 9.3 Europe
  • 9.3.1 Germany
    • 9.3.1.1 Market Trends
    • 9.3.1.2 Market Forecast
  • 9.3.2 France
    • 9.3.2.1 Market Trends
    • 9.3.2.2 Market Forecast
  • 9.3.3 United Kingdom
    • 9.3.3.1 Market Trends
    • 9.3.3.2 Market Forecast
  • 9.3.4 Italy
    • 9.3.4.1 Market Trends
    • 9.3.4.2 Market Forecast
  • 9.3.5 Spain
    • 9.3.5.1 Market Trends
    • 9.3.5.2 Market Forecast
  • 9.3.6 Russia
    • 9.3.6.1 Market Trends
    • 9.3.6.2 Market Forecast
  • 9.3.7 Others
    • 9.3.7.1 Market Trends
    • 9.3.7.2 Market Forecast
• 9.4 Latin America
  • 9.4.1 Brazil
    • 9.4.1.1 Market Trends
    • 9.4.1.2 Market Forecast
  • 9.4.2 Mexico
    • 9.4.2.1 Market Trends
    • 9.4.2.2 Market Forecast
  • 9.4.3 Others
    • 9.4.3.1 Market Trends
    • 9.4.3.2 Market Forecast
• 9.5 Middle East and Africa
  • 9.5.1 Market Trends
  • 9.5.2 Market Breakup by Country
  • 9.5.3 Market Forecast

10 SWOT Analysis

• 10.1 Overview
• 10.2 Strengths
• 10.3 Weaknesses
• 10.4 Opportunities
• 10.5 Threats

11 Value Chain Analysis

12 Porters Five Forces Analysis

• 12.1 Overview
• 12.2 Bargaining Power of Buyers
• 12.3 Bargaining Power of Suppliers
• 12.4 Degree of Competition
• 12.5 Threat of New Entrants
• 12.6 Threat of Substitutes

13 Price Analysis

14 Competitive Landscape

• 14.1 Market Structure
• 14.2 Key Players
• 14.3 Profiles of Key Players
  • 14.3.1 Amazon Web Services Inc. (Amazon.com Inc)
    • 14.3.1.1 Company Overview
    • 14.3.1.2 Product Portfolio
    • 14.3.1.3 SWOT Analysis
  • 14.3.2 Google LLC (Alphabet Inc.)
    • 14.3.2.1 Company Overview
    • 14.3.2.2 Product Portfolio
  • 14.3.3 Inbenta Technologies Inc.
    • 14.3.3.1 Company Overview
    • 14.3.3.2 Product Portfolio
    • 14.3.3.3 SWOT Analysis
  • 14.3.4 Intel Corporation
    • 14.3.4.1 Company Overview
    • 14.3.4.2 Product Portfolio
  • 14.3.5 International Business Machines Corporation
    • 14.3.5.1 Company Overview
    • 14.3.5.2 Product Portfolio
    • 14.3.5.3 Financials
    • 14.3.5.4 SWOT Analysis
  • 14.3.6 Microsoft Corporation
    • 14.3.6.1 Company Overview
    • 14.3.6.2 Product Portfolio
    • 14.3.6.3 Financials
    • 14.3.6.4 SWOT Analysis
  • 14.3.7 Salesforce.com Inc.
    • 14.3.7.1 Company Overview
    • 14.3.7.2 Product Portfolio
    • 14.3.7.3 Financials
    • 14.3.7.4 SWOT Analysis
  • 14.3.8 Samsung Electronics Co. Ltd.
    • 14.3.8.1 Company Overview
    • 14.3.8.2 Product Portfolio
    • 14.3.8.3 Financials
    • 14.3.8.4 SWOT Analysis
  • 14.3.9 TIBCO Software Inc.
    • 14.3.9.1 Company Overview
    • 14.3.9.2 Product Portfolio
    • 14.3.9.3 Financials
    • 14.3.9.4 SWOT Analysis
  • 14.3.10 Trifacta
    • 14.3.10.1 Company Overview
    • 14.3.10.2 Product Portfolio
    • 14.3.10.3 SWOT Analysis
  • 14.3.11 Verint Systems Inc.
    • 14.3.11.1 Company Overview
    • 14.3.11.2 Product Portfolio