查看购物车
  • Traditional Chinese
  • English
  • Japanese
  • Korean
封面
市场调查报告书
商品编码
1503364

2030 年金融科技市场人工智慧 (AI) 预测：按组件、部署模式、应用程式、最终用户和地区进行的全球分析

Artificial Intelligence (AI) in Fintech Market Forecasts to 2030 - Global Analysis By Component (Solution, Services and Other Component), Deployment Mode, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3个工作天内

价格

根据 Stratistics MRC 的数据，2024 年全球金融科技人工智慧 (AI) 市场规模将达到 440 亿美元，预计到 2030 年将达到 586 亿美元，在预测期内复合年增长率为 4.9%。

人工智慧 (AI) 透过提高各种金融服务的效率、个人化和安全性，正在彻底改变金融科技产业。人工智慧驱动的演算法可以快速分析大量资料，从而实现更好的风险评估、诈骗侦测和信用评分流程。在客户服务方面，人工智慧聊天机器人和虚拟助理提供 24/7 全天候支持，改善用户体验并降低金融机构的营运成本。人工智慧演算法还透过识别市场资料的模式和趋势来优化交易策略，以增强投资决策和投资组合管理。

根据认证诈欺审查员协会 (ACFE) 和分析先驱 SAS 进行的一项新民意调查，去年国际上使用人工智慧 (AI) 和机器学习 (ML) 进行诈欺检测的情况有所增加。

更深入的客户洞察和个性化

人工智慧可以分析大量客户资料并了解客户的财务行为、偏好和风险状况。这使得金融科技机构能够个人化金融产品和服务，提供有针对性的提案，并提高客户满意度。想像一下，收到根据您的风险接受度和贷款选择量身定制的投资建议，并考虑到您独特的财务状况。

演算法决策偏差

人工智慧演算法可以使它们所训练的资料中存在的偏见永久化。这可能导致歧视性贷款做法、不公平的风险评估或将某些群体排除在金融服务之外。仔细的资料选择、偏差检测技术和持续监控对于减少人工智慧主导的决策中阻碍市场成长的偏差至关重要。

提高效率和盈利

人工智慧可以自动执行传统上由人类员工处理的繁琐任务，例如贷款处理、诈欺侦测和客户服务查询。这简化了业务，减少了人为错误，并释放人力资本以专注于更具策略性的措施。效率的提高意味着金融科技公司成本的降低和利润潜力的增加。这使得金融科技公司能够即时侦测非法贸易，防止财务损失，并做出更明智的信用评估。

缺乏可解释性和透明度

金融机构依赖人工智慧做出关键决策，例如信用评分、投资策略和诈欺检测。然而，人工智慧模型固有的复杂性通常会导致黑盒流程，决策背后的基本原则不容易被相关人员（包括客户、监管机构，甚至审核）理解或解释。这种不透明性可能会导致一些负面影响。

COVID-19 的影响

由于许多零售商继续面临问题，COVID-19 的爆发影响了市场成长。许多商家推出了销售点融资替代方案以实现潜在成长。商家像银行帐户一样使用当前资料进行承保。这些公司还使用基于人工智慧的模型来了解基于交易和产品购买的消费行为。

在预测期内，服务业预计将是最大的。

託管服务预计将快速成长，因为它们有助于管理金融科技中支援人工智慧的应用程序，并有望成为预测期内最大的服务类别。金融科技新兴企业正在利用人工智慧提供专业服务，预计将推动该产业的发展。糟糕的客户服务或不正确的建议可能会导致客户流失。虚拟助理和聊天机器人可以即时存取消费者的帐户，提出个人化提案，并帮助他们管理储蓄。专业服务可能有助于金融科技公司提供为消费者量身定制的 24/7 支持，同时减少误导性建议、错误和糟糕客户服务的可能性。

风险管理领域预计在预测期内复合年增长率最高。

由于人工智慧演算法处理敏感的财务资料并自动化决策流程，有效的风险管理实践对于减轻潜在风险和确保监管合规性至关重要。此外，围绕人工智慧在金融领域使用的法规审查需要遵守资料隐私法（例如 GDPR）和金融法规（例如巴塞尔协议 III），以及高度透明的人工智慧演算法和风险管理框架，以确保课责。

比最大的地区

由于着名的人工智慧软体和系统供应商、金融机构对人工智慧计划的联合投资以及人工智慧在金融科技解决方案中的高度采用，预计北美在预测期内将占据最大的市场占有率。预计该地区在未来几年该行业将出现显着增长。此外，北美已成为许多人工智慧金融科技公司的业务中心，Sidetrade等公司选择将北美业务设在卡加利，推动市场成长。

复合年增长率最高的地区：

由于政府的支持措施和国内企业的快速扩张为金融科技业务的人工智慧发展创造了许多机会，预计亚太地区在预测期内将保持最高的复合年增长率。此外，作为其业务策略的一部分，主要企业正在投资该地区的新市场，从而刺激该地区的市场成长。

免费客製化服务

订阅此报告的客户可以存取以下免费自订选项之一：

  • 公司简介
    • 其他市场参与者的综合分析（最多 3 家公司）
    • 主要企业SWOT分析（最多3家企业）
  • 区域分割
    • 根据客户兴趣对主要国家的市场估计、预测和复合年增长率（註：基于可行性检查）
  • 竞争基准化分析
    • 根据产品系列、地理分布和策略联盟对主要企业基准化分析

目录

第一章执行摘要

第二章 前言

  • 概述
  • 相关利益者
  • 调查范围
  • 调查方法
    • 资料探勘
    • 资料分析
    • 资料检验
    • 研究途径
  • 研究资讯来源
    • 主要研究资讯来源
    • 二次研究资讯来源
    • 先决条件

第三章市场趋势分析

  • 促进因素
  • 抑制因素
  • 机会
  • 威胁
  • 应用分析
  • 最终用户分析
  • 新兴市场
  • COVID-19 的影响

第4章波特五力分析

  • 供应商的议价能力
  • 买方议价能力
  • 替代品的威胁
  • 新进入者的威胁
  • 竞争公司之间的敌对关係

第五章 全球金融科技人工智慧 (AI) 市场：按组成部分

  • 解决方案
    • 聊天机器人和虚拟助理
    • 诈欺检测与预防
    • 信用评分和融资
    • 演算法交易
    • 个人化银行业务
  • 服务
    • 管理服务
    • 支援与维护
    • 专业服务
    • 指南针咨询
    • 实施和培训
  • 其他组件

第六章 全球金融科技人工智慧（AI）市场：依部署模式

  • 云
  • 本地

第七章 全球金融科技人工智慧 (AI) 市场：按应用分类

  • 危机管理
  • 付款及汇款
  • 客户服务
  • 保险服务
  • 资产管理
  • 其他用途

第八章 全球金融科技人工智慧 (AI) 市场：按最终用户分类

  • 银行和金融机构
  • 保险公司
  • 投资公司
  • 金融科技Start-Ups
  • 其他最终用户

第九章 全球金融科技人工智慧（AI）市场：按地区

  • 北美洲
    • 美国
    • 加拿大
    • 墨西哥
  • 欧洲
    • 德国
    • 英国
    • 义大利
    • 法国
    • 西班牙
    • 其他欧洲国家
  • 亚太地区
    • 日本
    • 中国
    • 印度
    • 澳洲
    • 纽西兰
    • 韩国
    • 其他亚太地区
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 南美洲其他地区
  • 中东/非洲
    • 沙乌地阿拉伯
    • 阿拉伯聯合大公国
    • 卡达
    • 南非
    • 其他中东和非洲

第10章 主要进展

  • 合约、伙伴关係、协作和合资企业
  • 收购和合併
  • 新产品发布
  • 业务扩展
  • 其他关键策略

第十一章 公司概况

  • Active.Ai
  • Amazon Web Services Inc.
  • Betterment Holdings
  • ComplyAdvantage.com
  • Data Minr Inc.
  • IBM Corporation
  • Intel Corporation
  • IPsoft Inc.
  • Microsoft Corporation
  • Narrative Science
  • Next IT Corporation
  • Onfido
  • Pefin Holdings LLC
  • Ripple Labs Inc.
  • Sift Science Inc.
  • TIBCO Software
  • Trifacta Software Inc.
  • WealthFront Inc.
  • Zeitgold
Product Code: SMRC26531

According to Stratistics MRC, the Global Artificial Intelligence (AI) in Fintech Market is accounted for $44.0 billion in 2024 and is expected to reach $58.6 billion by 2030 growing at a CAGR of 4.9% during the forecast period. Artificial Intelligence (AI) is revolutionizing the Fintech industry by enhancing efficiency, personalization, and security across various financial services. AI-powered algorithms analyze vast amounts of data swiftly, enabling better risk assessment, fraud detection, and credit scoring processes. In customer service, AI-driven chatbots and virtual assistant's offer 24/7 support, improving user experience and reducing operational costs for financial institutions. AI algorithms also optimize trading strategies by identifying patterns and trends in market data, thereby enhancing investment decisions and portfolio management.

According to a new poll conducted by Certified Fraud Examiners (ACFE) and analytics pioneer SAS, the use of Artificial Intelligence (AI) and Machine Learning (ML) for fraud detection increased internationally last year.

Market Dynamics:

Driver:

Deeper customer insights and personalization

AI can analyze vast amounts of customer data to understand their financial behavior, preferences, and risk profiles. This enables Fintech institutions to personalize financial products and services, offer targeted recommendations, and improve customer satisfaction. Imagine receiving investment advice tailored to your risk tolerance or loan options that consider your unique financial situation.

Restraint:

Bias in algorithmic decisions

AI algorithms can perpetuate biases present in the data they are trained on. This can lead to discriminatory lending practices, unfair risk assessments, or exclusion of certain demographics from financial services. Careful data selection, bias detection techniques, and ongoing monitoring are essential to mitigate bias in AI-driven decisions hampering the growth of the market.

Opportunity:

Enhanced efficiency and profitability

AI automates tedious tasks traditionally handled by human employees, such as loan processing, fraud detection, and customer service inquiries. This streamlines operations, reduces manual errors, and frees up human capital to focus on more strategic initiatives. Improved efficiency translates to cost savings and potentially higher profits for Fintech companies. This empowers Fintech companies to detect fraudulent transactions in real-time, prevent financial losses, and make more informed creditworthiness assessments.

Threat:

Lack of explainability and transparency

Financial institutions rely on AI for critical decisions such as credit scoring, investment strategies, and fraud detection. However, the inherent complexity of AI models often results in black-box processes where the rationale behind decisions is not easily understandable or explainable to stakeholders, including customers, regulators, and even internal auditors. This opacity can lead to several adverse effects.

Covid-19 Impact

The outbreak of COVID 19 affected the market growth as many retailers continue to face problems. Many merchants implemented point of sale financing alternatives for potential growth. Merchants are using current data like a bank account for underwriting. Still, these players are also using AI-based models to access consumer behavior based on the transaction made or by their product purchase.

The services segment is expected to be the largest during the forecast period

The services is expected to be the largest during the forecast period as the managed service is likely to grow quickly owing to its help in administering AI-enabled apps in fintech. Fintech startups are using AI to provide professional services expected to drive the development of the segment. Poor customer service or incorrect advice might result in customer loss. Virtual assistants and chatbots can access consumers' accounts in real-time, provide personalized recommendations, and aid them in managing their savings. Professional services would assist fintech in providing tailored 24/7 support to their consumers while decreasing the likelihood of incorrect advice, errors, or bad customer service.

The risk management segment is expected to have the highest CAGR during the forecast period

The risk management segment is expected to have the highest CAGR during the forecast period as AI algorithms handle sensitive financial data and automate decision-making processes, effective risk management practices are essential to mitigate potential risks and ensure regulatory compliance. Moreover, regulatory scrutiny around AI usage in finance requires adherence to data privacy laws (like GDPR) and financial regulations (like Basel III), necessitating transparent AI algorithms and accountable risk management frameworks which encourage the growth of the market.

Region with largest share:

North America is projected to hold the largest market share during the forecast period due to prominent AI software and systems suppliers, combined investment by financial institutions into AI projects, and the adoption of most AI in Fintech solutions. The region is expected to experience significant growth in this area in the coming years. Additionally, North America serves as the business hub for many AI Fintech firms, with companies like Sidetrade choosing to locate their North American operations in Calgary which drives the market growth.

Region with highest CAGR:

Asia Pacific is projected to hold the highest CAGR over the forecast period owing the quick expansion of domestic firms with supportive government measures creates numerous opportunities for the advancement of AI in the fintech business. Furthermore, prominent players invest in the region's new markets as part of their business strategy, adding to regional market growth.

Key players in the market

Some of the key players in Artificial Intelligence (AI) in Fintech market include Active.Ai, Amazon Web Services Inc., Betterment Holdings, ComplyAdvantage.com, Data Minr Inc., IBM Corporation, Intel Corporation, IPsoft Inc., Microsoft Corporation, Narrative Science, Next IT Corporation, Onfido, Pefin Holdings LLC, Ripple Labs Inc., Sift Science Inc., TIBCO Software, Trifacta Software Inc., WealthFront Inc. and Zeitgold

Key Developments:

In June 2024, Intel Gaudi Enables a Lower Cost Alternative for AI Compute and GenAI. Community-based software simplifies generative AI (GenAI) development and industry-standard Ethernet networking enables flexible scaling of AI systems.

In February 2024, Indian startup Sarvam AI collaborates with Microsoft to bring its Indic voice large language model (LLM) to Azure. The collaboration aims to enable Sarvam AI to leverage Azure AI and Azure Infrastructure to build and deploy their voice LLM stack

Components Covered:

  • Solution
  • Services
  • Other Components

Deployment Modes Covered:

  • Cloud
  • On-Premise

Applications Covered:

  • Risk Management
  • Payments & Money Transfer
  • Customer Service
  • Insurance Services
  • Asset Management
  • Other Applications

End Users Covered:

  • Banks & Financial Institutions
  • Insurance Companies
  • Investment Firms
  • Fintech Startups
  • Other End Users

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2022, 2023, 2024, 2026, and 2030
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 Application Analysis
  • 3.7 End User Analysis
  • 3.8 Emerging Markets
  • 3.9 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global Artificial Intelligence (AI) in Fintech Market, By Component

  • 5.1 Introduction
  • 5.2 Solution
    • 5.2.1 Chatbots & Virtual Assistants
    • 5.2.2 Fraud Detection & Prevention
    • 5.2.3 Credit Scoring & Lending
    • 5.2.4 Algorithmic Trading
    • 5.2.5 Personalized Banking
  • 5.3 Services
    • 5.3.1 Managed Services
    • 5.3.3 Support & Maintenance
    • 5.3.5 Professional Services
    • 5.3.7 Encompass Consulting
    • 5.3.9 Implementation & Training
  • 5.4 Other Component

6 Global Artificial Intelligence (AI) in Fintech Market, By Deployment Mode

  • 6.1 Introduction
  • 6.2 Cloud
  • 6.3 On-Premise

7 Global Artificial Intelligence (AI) in Fintech Market, By Application

  • 7.1 Introduction
  • 7.2 Risk Management
  • 7.3 Payments & Money Transfer
  • 7.4 Customer Service
  • 7.5 Insurance Services
  • 7.6 Asset Management
  • 7.7 Other Applications

8 Global Artificial Intelligence (AI) in Fintech Market, By End User

  • 8.1 Introduction
  • 8.2 Banks & Financial Institutions
  • 8.3 Insurance Companies
  • 8.4 Investment Firms
  • 8.5 Fintech Startups
  • 8.6 Other End Users

9 Global Artificial Intelligence (AI) in Fintech Market, By Geography

  • 9.1 Introduction
  • 9.2 North America
    • 9.2.1 US
    • 9.2.2 Canada
    • 9.2.3 Mexico
  • 9.3 Europe
    • 9.3.1 Germany
    • 9.3.2 UK
    • 9.3.3 Italy
    • 9.3.4 France
    • 9.3.5 Spain
    • 9.3.6 Rest of Europe
  • 9.4 Asia Pacific
    • 9.4.1 Japan
    • 9.4.2 China
    • 9.4.3 India
    • 9.4.4 Australia
    • 9.4.5 New Zealand
    • 9.4.6 South Korea
    • 9.4.7 Rest of Asia Pacific
  • 9.5 South America
    • 9.5.1 Argentina
    • 9.5.2 Brazil
    • 9.5.3 Chile
    • 9.5.4 Rest of South America
  • 9.6 Middle East & Africa
    • 9.6.1 Saudi Arabia
    • 9.6.2 UAE
    • 9.6.3 Qatar
    • 9.6.4 South Africa
    • 9.6.5 Rest of Middle East & Africa

10 Key Developments

  • 10.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 10.2 Acquisitions & Mergers
  • 10.3 New Product Launch
  • 10.4 Expansions
  • 10.5 Other Key Strategies

11 Company Profiling

  • 11.1 Active.Ai
  • 11.2 Amazon Web Services Inc.
  • 11.3 Betterment Holdings
  • 11.4 ComplyAdvantage.com
  • 11.5 Data Minr Inc.
  • 11.6 IBM Corporation
  • 11.7 Intel Corporation
  • 11.8 IPsoft Inc.
  • 11.9 Microsoft Corporation
  • 11.10 Narrative Science
  • 11.11 Next IT Corporation
  • 11.12 Onfido
  • 11.13 Pefin Holdings LLC
  • 11.14 Ripple Labs Inc.
  • 11.15 Sift Science Inc.
  • 11.16 TIBCO Software
  • 11.17 Trifacta Software Inc.
  • 11.18 WealthFront Inc.
  • 11.19 Zeitgold

List of Tables

  • Table 1 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Region (2022-2030) ($MN)
  • Table 2 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Component (2022-2030) ($MN)
  • Table 3 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Solution (2022-2030) ($MN)
  • Table 4 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Chatbots & Virtual Assistants (2022-2030) ($MN)
  • Table 5 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Fraud Detection & Prevention (2022-2030) ($MN)
  • Table 6 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Credit Scoring & Lending (2022-2030) ($MN)
  • Table 7 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Algorithmic Trading (2022-2030) ($MN)
  • Table 8 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Personalized Banking (2022-2030) ($MN)
  • Table 9 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Services (2022-2030) ($MN)
  • Table 10 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Managed Services (2022-2030) ($MN)
  • Table 11 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Support & Maintenance (2022-2030) ($MN)
  • Table 12 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Professional Services (2022-2030) ($MN)
  • Table 13 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Encompass Consulting (2022-2030) ($MN)
  • Table 14 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Implementation & Training (2022-2030) ($MN)
  • Table 15 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Other Component (2022-2030) ($MN)
  • Table 16 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Deployment Mode (2022-2030) ($MN)
  • Table 17 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Cloud (2022-2030) ($MN)
  • Table 18 Global Artificial Intelligence (AI) in Fintech Market Outlook, By On-Premise (2022-2030) ($MN)
  • Table 19 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Application (2022-2030) ($MN)
  • Table 20 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Risk Management (2022-2030) ($MN)
  • Table 21 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Payments & Money Transfer (2022-2030) ($MN)
  • Table 22 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Customer Service (2022-2030) ($MN)
  • Table 23 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Insurance Services (2022-2030) ($MN)
  • Table 24 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Asset Management (2022-2030) ($MN)
  • Table 25 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Other Applications (2022-2030) ($MN)
  • Table 26 Global Artificial Intelligence (AI) in Fintech Market Outlook, By End User (2022-2030) ($MN)
  • Table 27 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Banks & Financial Institutions (2022-2030) ($MN)
  • Table 28 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Insurance Companies (2022-2030) ($MN)
  • Table 29 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Investment Firms (2022-2030) ($MN)
  • Table 30 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Fintech Startups (2022-2030) ($MN)
  • Table 31 Global Artificial Intelligence (AI) in Fintech Market Outlook, By Other End Users (2022-2030) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.