查看购物车
  • Traditional Chinese
  • English
  • Japanese
  • Korean
封面
市场调查报告书
商品编码
1390666

金融科技市场中的人工智慧报告，按类型（解决方案、服务）、部署模型（基于云端、本地）、应用程式（虚拟助理（聊天机器人）、信用评分、定量和资产管理、诈欺检测等）和区域2023-2028

AI in Fintech Market Report by Type (Solutions, Services), Deployment Model (Cloud-based, On-premises), Application (Virtual Assistant (Chatbots), Credit Scoring, Quantitative and Asset Management, Fraud Detection, and Others), and Region 2023-2028
出版日期: | 出版商: IMARC | 英文 141 Pages | 商品交期: 2-3个工作天内

价格

抽象的

2022年，全球人工智慧金融科技市场规模达到117亿美元。展望未来， IMARC Group预计到2028年市场规模将达到436亿美元，2022-2028年复合年增长率（CAGR）为24.51%。科技的快速进步、对监管合规性的需求不断增长、对个人化服务的需求不断增长、金融科技中广泛采用人工智慧来降低金融风险、网路诈欺发生率的增加以及金融科技中人工智慧的使用不断增加以实现财务流程自动化是其中一些主要因素。推动市场的因素。

金融科技中的人工智慧是指将人工智慧（AI）技术融入金融服务领域，以增强营运和客户体验。它包括机器人流程自动化 (RPA)、机器学习 (ML) 和自然语言处理 (NLP)。金融科技中的人工智慧广泛应用于诈欺侦测、信用评分、聊天机器人客户服务、演算法交易、风险管理、个人化行销、投资分析、监管合规监控、财富管理和处理最佳化。它有助于提高效率、降低成本、提高准确性、防止诈欺、个人化服务并提供无缝的客户体验。

人工智慧在金融科技中的广泛采用，透过资料分析和预测模型来预测和减轻各种金融风险，正在推动市场成长。此外，网路诈骗事件的增加也促进了金融科技领域对人工智慧的需求，以即时识别诈骗活动并增强安全措施。除此之外，广泛采用人工智慧来实现财务流程自动化、减少人为错误、提高效率并确保一致性正在对市场成长产生正面影响。此外，由于金融服务的快速全球化，越来越多地利用人工智慧来实现无缝跨境交易和支持，这也促进了市场的成长。此外，人工智慧在金融科技中的广泛应用，从大量金融资料中获得深刻的见解，正在加强市场的成长。此外，金融机构越来越多地采用人工智慧来降低营运成本并最大限度地减少体力劳动，这也支持了市场的成长。

金融科技市场趋势/驱动因素中的人工智慧：

科技的快速进步

人工智慧在金融科技中的整合很大程度上受到持续技术进步的影响。与此一致的是，整合机器学习（ML）演算法来完善巨量资料分析并扩大其在金融领域的潜在应用正在推动市场成长。此外，这些创新能够高速且准确地处理和解释大量资料，提供即时洞察和自动化功能。此外，量子运算和云端技术的发展进一步增强了复杂金融建模所需的运算能力，正在推动市场成长。除此之外，金融科技公司正在利用这些先进技术来创造个人化银行体验、自动化交易，并以前所未有的精确度管理风险。此外，技术进步不仅提高了效率，也为全新产品和服务打开了大门。

监理合规需求不断成长

金融业的运作遵循一套复杂的法规，各个司法管辖区的法规各不相同。遵守这些法规不仅是强制性的，而且对于维护消费者信任和金融体系的整体完整性也至关重要。据此，金融科技中的人工智慧在确保监管合规性以及自动监控和分析数百万笔交易以检测异常或不遵守相关法律方面发挥着至关重要的作用。除此之外，整合自然语言处理（NLP）来解释不断变化的监管文本，确保金融机构始终了解最新要求，并对市场成长产生正面影响。此外，合规流程的自动化减少了人为错误的可能性，并实现了对监管变化更加敏感和适应性更强的方法。

对个人化服务的需求不断增长

消费者对包括金融在内的所有服务业的个人化体验日益增长的期望正在推动市场成长。人工智慧透过分析大量客户资料并识别个人偏好、消费习惯和财务需求，在满足这项需求方面发挥着至关重要的作用。此外，这些资讯也用于为每位客户量身定制金融产品、优惠和建议。此外，人工智慧使金融机构能够透过以前无法实现的客製化等级提供个人化投资策略或个人化贷款优惠。除此之外，人工智慧的广泛使用有助于提高客户忠诚度、增加参与度和提高整体满意度。因此，采用人工智慧创建量身定制的金融解决方案不仅是一种趋势，而且是金融服务提供方式的根本性转变。

人工智慧在金融科技产业细分：

IMARC Group提供了全球人工智慧金融科技市场报告各细分市场主要趋势的分析，以及 2023 年至 2028 年全球、区域和国家层面的预测。我们的报告根据类型、部署模型和应用程式对市场进行了分类。

按类型划分：

解决方案

服务

解决方案主导市场

该报告根据类型提供了详细的市场细分和分析。这包括解决方案和服务。根据该报告，解决方案代表了最大的部分。

人工智慧解决方案正在主导市场，因为它们旨在应对金融业的特定挑战，例如诈欺侦测、风险管理和客户服务。此外，他们还提供个人化服务，从而提高客户参与度和满意度。他们还帮助了解客户行为并预测他们的需求，从而促进客製化产品和服务。除此之外，人工智慧解决方案旨在与现有金融系统无缝集成，这使得组织无需进行重大改革即可采用人工智慧，从而减少阻力并鼓励采用。此外，它们可以根据业务需求和市场动态进行扩展，使公司能够发展和适应，而无需在技术上进行大量额外投资。此外，人工智慧解决方案透过自动化日常任务和优化营运工作流程来节省成本。

按部署模型划分：

基于云端

本地

基于云端的主导市场

该报告根据部署模型对市场进行了详细的细分和分析。这包括基于云端的和本地的。根据该报告，基于云端的占据了最大的部分。

基于云端的模型提供了一种经济高效的解决方案，因为它们减少了对实体基础设施的需求，促进了向营运支出模式的转变。此外，它们还允许金融机构根据需求轻鬆扩展其人工智慧应用。此外，基于云端的人工智慧解决方案提供从任何有网路连接的地方的访问，这为员工提供了更灵活的工作环境，并允许即时的全球协作。除此之外，它们还允许快速实施和迭代，使金融机构能够在快速发展的行业中保持领先地位。此外，云端供应商拥有强大的安全措施，可以协助满足合规性要求。此外，基于云端的人工智慧解决方案可以更顺畅地与现有系统和其他云端服务集成，从而使金融组织能够创建一个有凝聚力的技术生态系统，而无需面临重大的定製或相容性挑战。

按应用划分：

虚拟助理（聊天机器人）

信用评分

量化与资产管理

诈欺识别

其他的

该报告根据应用程式提供了详细的市场细分和分析。这包括虚拟协助（聊天机器人）、信用评分、定量和资产管理、诈欺检测等。

由人工智慧支援的虚拟助理可以透过提供持续的客户服务、处理查询和即时解决问题来满足各种客户期望。此外，他们还可以透过同时处理大量查询来大幅降低与客户支援相关的劳动力成本，从而释放人力资源以专注于更复杂的任务。此外，虚拟助理可以根据用户个人资料和过去的互动提供个人化回应。这种程度的个人化可带来更具吸引力和满意度的客户体验。

人工智慧在信用评分过程中发挥着至关重要的作用，因为它可以分析大量资料，包括历史信用资讯、交易历史和社交媒体行为，从而可以更全面、更准确地评估个人或企业的信用度。此外，人工智慧驱动的信用评分可在几秒钟内提供结果，从而加快贷款审批速度并提高客户满意度。除此之外，它还可以根据各个金融机构的具体要求和风险偏好进行客製化。

按地区划分：

北美洲

美国

加拿大

亚太

中国

日本

印度

韩国

澳洲

印尼

其他的

欧洲

德国

法国

英国

义大利

西班牙

俄罗斯

其他的

拉丁美洲

巴西

墨西哥

其他的

中东和非洲

北美在市场上表现出明显的主导地位，在金融科技领域占据最大的人工智慧市场份额

该报告还对所有主要区域市场进行了全面分析，其中包括北美（美国和加拿大）；亚太地区（中国、日本、印度、韩国、澳洲、印尼等）；欧洲（德国、法国、英国、义大利、西班牙等）；拉丁美洲（巴西、墨西哥等）；以及中东和非洲。报告称，北美是最大的细分市场。

北美拥有许多技术创新中心，培育创新和创业文化，进而促进尖端人工智慧技术的发展。此外，该地区私营和公共部门对研发（R&D）措施进行了大量投资，以推动金融科技领域的技术进步和人工智慧商业化。除此之外，北美成熟的金融业为人工智慧的整合提供了肥沃的土壤，对市场的成长产生了正面的影响。除此之外，地方政府实施的支持性政策和法规，鼓励负责任地使用人工智慧，正在推动市场成长。此外，容易获得具有人工智慧、机器学习和资料科学专业知识的熟练专业人员，进一步推动了市场成长。

竞争格局：

顶尖公司正在探索新的演算法、方法和技术，以提高金融服务的效率、安全性和个人化。他们正在与金融科技新创公司和科技公司建立策略合作伙伴关係，以开发尖端解决方案并促进创新。此外，一些关键参与者正在实施预测分析和机器学习 (ML) 模型，以提供对客户行为、市场趋势和风险管理的见解。此外，顶级市场公司正在根据个人需求和偏好打造个人化服务和产品，包括个人化银行业务、投资建议和客製化行销策略。除此之外，领先公司正积极致力于开发透明且公正的人工智慧模型，强调道德的人工智慧实践。此外，他们正在利用人工智慧为服务不足的人群提供金融服务，使用演算法以不同的方式评估信用度或透过人工智慧驱动的工具提供金融知识。

该报告对市场竞争格局进行了全面分析。也提供了所有主要公司的详细资料。市场上的一些主要参与者包括：

亚马逊网路服务公司（Amazon.com Inc）

谷歌有限责任公司（Alphabet Inc.）

因本塔技术公司

英特尔公司

国际商业机器公司

微软公司

Salesforce.com 公司

三星电子有限公司

TIBCO 软体公司

特里法塔

Verint 系统公司

最近的发展：

2023 年 6 月，亚马逊网路服务公司 (Amazon.com Inc.) 与 NVIDIA 合作推出「全球金融科技加速器」计划，以利用人工智慧推动早期金融科技新创公司的发展。

2023年6月，Google有限责任公司（Alphabet Inc.）推出反洗钱人工智慧（AML AI），帮助全球金融机构更有效、更有效率地侦测洗钱行为。

2023年1月，Inbenta Technologies Inc.获得4,000万美元融资，用于开发一个综合平台，为金融服务、旅游、电子商务、保险等产业客製化人工智慧驱动的解决方案。

本报告回答的关键问题

  • 全球人工智慧金融科技市场有多大
  • 2023-2028年全球人工智慧在金融科技市场的预期成长率是多少
  • 推动全球人工智慧金融科技市场发展的关键因素是什么
  • COVID-19 对全球人工智慧金融科技市场有何影响
  • 全球人工智慧金融科技市场按类型划分是怎样的
  • 基于部署模型，全球人工智慧在金融科技市场的细分是什么
  • 全球人工智慧金融科技市场重点区域有哪些
  • 全球人工智慧金融科技市场的主要参与者/公司有哪些

本报告回答的关键问题

  • 全球人工智慧金融科技市场有多大？
  • 2023-2028年全球人工智慧在金融科技市场的预期成长率是多少？
  • 推动全球人工智慧金融科技市场发展的关键因素是什么？
  • COVID-19 对全球金融科技市场人工智慧有何影响？
  • 全球人工智慧金融科技市场按类型划分是怎样的？
  • 从部署模式来看，全球人工智慧在金融科技市场的细分情况如何？
  • 全球人工智慧金融科技市场的重点区域有哪些？
  • 全球人工智慧金融科技市场的主要参与者/公司有哪些？

目录

第一章：前言

第 2 章：范围与方法

  • 研究目的
  • 利害关係人
  • 资料来源
    • 主要资源
    • 二手资料
  • 市场预测
    • 自下而上的方法
    • 自上而下的方法
  • 预测方法

第 3 章：执行摘要

第 4 章：简介

  • 概述
  • 主要行业趋势

第 5 章：金融科技市场中的全球人工智慧

  • 市场概况
  • 市场业绩
  • COVID-19 的影响
  • 市场预测

第 6 章：按类型分類的市场细分

  • 解决方案
    • 市场走向
    • 市场预测
  • 服务
    • 市场走向
    • 市场预测

第 7 章：按部署模式分類的市场

  • 基于云端
    • 市场走向
    • 市场预测
  • 本地
    • 市场走向
    • 市场预测

第 8 章：按应用分類的市场区隔

  • 虚拟助理（聊天机器人）
    • 市场走向
    • 市场预测
  • 信用评分
    • 市场走向
    • 市场预测
  • 量化与资产管理
    • 市场走向
    • 市场预测
  • 诈欺识别
    • 市场走向
    • 市场预测
  • 其他的
    • 市场走向
    • 市场预测

第 9 章：按地区分類的市场区隔

  • 北美洲
    • 美国
      • 市场走向
      • 市场预测
    • 加拿大
      • 市场走向
      • 市场预测
  • 亚太
    • 中国
      • 市场走向
      • 市场预测
    • 日本
      • 市场走向
      • 市场预测
    • 印度
      • 市场走向
      • 市场预测
    • 韩国
      • 市场走向
      • 市场预测
    • 澳洲
      • 市场走向
      • 市场预测
    • 印尼
      • 市场走向
      • 市场预测
    • 其他的
      • 市场走向
      • 市场预测
  • 欧洲
    • 德国
      • 市场走向
      • 市场预测
    • 法国
      • 市场走向
      • 市场预测
    • 英国
      • 市场走向
      • 市场预测
    • 义大利
      • 市场走向
      • 市场预测
    • 西班牙
      • 市场走向
      • 市场预测
    • 俄罗斯
      • 市场走向
      • 市场预测
    • 其他的
      • 市场走向
      • 市场预测
  • 拉丁美洲
    • 巴西
      • 市场走向
      • 市场预测
    • 墨西哥
      • 市场走向
      • 市场预测
    • 其他的
      • 市场走向
      • 市场预测
  • 中东和非洲
    • 市场走向
    • 按国家/地区分類的市场细分
    • 市场预测

第 10 章：SWOT 分析

  • 概述
  • 优势
  • 弱点
  • 机会
  • 威胁

第 11 章：价值链分析

第 12 章：波特五力分析

  • 概述
  • 买家的议价能力
  • 供应商的议价能力
  • 竞争程度
  • 新进入者的威胁
  • 替代品的威胁

第 13 章：价格分析

第14章：竞争格局

  • 市场结构
  • 关键参与者
  • 关键参与者简介
    • 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.
Product Code: SR112023A4483

Abstract

The global AI in fintech market size reached US$ 11.7 Billion in 2022. Looking forward, IMARC Group expects the market to reach US$ 43.6 Billion by 2028, exhibiting a growth rate (CAGR) of 24.51% during 2022-2028. 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 market.

AI in fintech refers to the integration of artificial intelligence (AI) technologies within the financial services sector to enhance operations and customer experiences. It includes robotic process automation (RPA), machine learning (ML), and natural language processing (NLP). AI in fintech is widely used for fraud detection, credit scoring, customer service through chatbots, algorithmic trading, risk management, personalized marketing, investment analysis, regulatory compliance monitoring, wealth management, and processing optimization. It aids in improving efficiency, reducing cost, enhancing accuracy, preventing fraud, personalizing services, and providing a seamless customer experience.

The widespread adoption of AI in fintech to predict and mitigate various financial risks through data analysis and predictive modeling is propelling the market growth. Furthermore, the increasing incidence of cyber fraud is facilitating the demand for AI in fintech to identify fraudulent activities in real time and enhance security measures. Apart from this, the widespread adoption of AI to automate financial processes, reduce human errors, enhance efficiency, and ensure consistency is positively influencing the market growth. Additionally, the increasing utilization of AI to enable seamless cross-border transactions and supports, owing to the rapid globalization of financial services, is contributing to the market growth. Moreover, the widespread application of AI in fintech to derive deep insights from vast amounts of financial data is strengthening the market growth. In addition, the rising adoption of AI in financial institutions to reduce operational costs and minimize manual labor is supporting the market growth.

AI in Fintech Market Trends/Drivers:

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 forecasts at the global, regional and country levels from 2023-2028. 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 assistance (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 2023-2028?
  • 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

List of Figures

  • Figure 1: Global: AI in Fintech Market: Major Drivers and Challenges
  • Figure 2: Global: AI in Fintech Market: Sales Value (in Billion US$), 2017-2022
  • Figure 3: Global: AI in Fintech Market Forecast: Sales Value (in Billion US$), 2023-2028
  • Figure 4: Global: AI in Fintech Market: Breakup by Type (in %), 2022
  • Figure 5: Global: AI in Fintech Market: Breakup by Deployment Model (in %), 2022
  • Figure 6: Global: AI in Fintech Market: Breakup by Application (in %), 2022
  • Figure 7: Global: AI in Fintech Market: Breakup by Region (in %), 2022
  • Figure 8: Global: AI in Fintech (Solutions) Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 9: Global: AI in Fintech (Solutions) Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 10: Global: AI in Fintech (Services) Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 11: Global: AI in Fintech (Services) Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 12: Global: AI in Fintech (Cloud-based) Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 13: Global: AI in Fintech (Cloud-based) Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 14: Global: AI in Fintech (On-premises) Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 15: Global: AI in Fintech (On-premises) Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 16: Global: AI in Fintech (Virtual Assistant-Chatbots) Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 17: Global: AI in Fintech (Virtual Assistant-Chatbots) Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 18: Global: AI in Fintech (Credit Scoring) Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 19: Global: AI in Fintech (Credit Scoring) Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 20: Global: AI in Fintech (Quantitative and Asset Management) Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 21: Global: AI in Fintech (Quantitative and Asset Management) Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 22: Global: AI in Fintech (Fraud Detection) Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 23: Global: AI in Fintech (Fraud Detection) Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 24: Global: AI in Fintech (Other Applications) Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 25: Global: AI in Fintech (Other Applications) Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 26: North America: AI in Fintech Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 27: North America: AI in Fintech Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 28: United States: AI in Fintech Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 29: United States: AI in Fintech Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 30: Canada: AI in Fintech Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 31: Canada: AI in Fintech Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 32: Asia-Pacific: AI in Fintech Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 33: Asia-Pacific: AI in Fintech Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 34: China: AI in Fintech Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 35: China: AI in Fintech Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 36: Japan: AI in Fintech Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 37: Japan: AI in Fintech Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 38: India: AI in Fintech Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 39: India: AI in Fintech Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 40: South Korea: AI in Fintech Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 41: South Korea: AI in Fintech Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 42: Australia: AI in Fintech Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 43: Australia: AI in Fintech Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 44: Indonesia: AI in Fintech Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 45: Indonesia: AI in Fintech Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 46: Others: AI in Fintech Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 47: Others: AI in Fintech Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 48: Europe: AI in Fintech Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 49: Europe: AI in Fintech Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 50: Germany: AI in Fintech Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 51: Germany: AI in Fintech Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 52: France: AI in Fintech Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 53: France: AI in Fintech Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 54: United Kingdom: AI in Fintech Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 55: United Kingdom: AI in Fintech Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 56: Italy: AI in Fintech Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 57: Italy: AI in Fintech Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 58: Spain: AI in Fintech Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 59: Spain: AI in Fintech Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 60: Russia: AI in Fintech Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 61: Russia: AI in Fintech Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 62: Others: AI in Fintech Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 63: Others: AI in Fintech Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 64: Latin America: AI in Fintech Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 65: Latin America: AI in Fintech Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 66: Brazil: AI in Fintech Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 67: Brazil: AI in Fintech Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 68: Mexico: AI in Fintech Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 69: Mexico: AI in Fintech Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 70: Others: AI in Fintech Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 71: Others: AI in Fintech Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 72: Middle East and Africa: AI in Fintech Market: Sales Value (in Million US$), 2017 & 2022
  • Figure 73: Middle East and Africa: AI in Fintech Market: Breakup by Country (in %), 2022
  • Figure 74: Middle East and Africa: AI in Fintech Market Forecast: Sales Value (in Million US$), 2023-2028
  • Figure 75: Global: AI in Fintech Industry: SWOT Analysis
  • Figure 76: Global: AI in Fintech Industry: Value Chain Analysis
  • Figure 77: Global: AI in Fintech Industry: Porter's Five Forces Analysis

List of Tables

  • Table 1: Global: AI in Fintech Market: Key Industry Highlights, 2022 and 2028
  • Table 2: Global: AI in Fintech Market Forecast: Breakup by Type (in Million US$), 2023-2028
  • Table 3: Global: AI in Fintech Market Forecast: Breakup by Deployment Model (in Million US$), 2023-2028
  • Table 4: Global: AI in Fintech Market Forecast: Breakup by Application (in Million US$), 2023-2028
  • Table 5: Global: AI in Fintech Market Forecast: Breakup by Region (in Million US$), 2023-2028
  • Table 6: Global: AI in Fintech Market: Competitive Structure
  • Table 7: Global: AI in Fintech Market: Key Players