封面
市場調查報告書
商品編碼
1390666

金融科技市場中的人工智慧報告,按類型(解決方案、服務)、部署模型(基於雲端、本地)、應用程式(虛擬助理(聊天機器人)、信用評分、定量和資產管理、詐欺檢測等)和區域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個工作天內

價格

概要

2022年,全球人工智慧金融科技市場規模達到117億美元。展望未來, IMARC Group預計到2028年市場規模將達到436億美元,2022-2028年複合年成長率(CAGR)為24.51%。科技的快速進步、對監管合規性的需求不斷成長、對個人化服務的需求不斷成長、金融科技中廣泛採用人工智慧來降低金融風險、網路詐欺發生率的增加以及金融科技中人工智慧的使用不斷增加以實現財務流程自動化是其中一些主要因素。推動市場的因素。

金融科技中的人工智慧是指將人工智慧(AI)技術融入金融服務領域,以增強營運和客戶體驗。它包括機器人流程自動化 (RPA)、機器學習 (ML) 和自然語言處理 (NLP)。金融科技中的人工智慧廣泛應用於詐欺偵測、信用評分、聊天機器人客戶服務、演算法交易、風險管理、個人化行銷、投資分析、監管合規監控、財富管理和處理最佳化。它有助於提高效率、降低成本、提高準確性、防止詐欺、個人化服務並提供無縫的客戶體驗。

人工智慧在金融科技中的廣泛採用,透過資料分析和預測模型來預測和減輕各種金融風險,正在推動市場成長。此外,網路詐騙事件的增加也促進了金融科技領域對人工智慧的需求,以即時識別詐騙活動並增強安全措施。除此之外,廣泛採用人工智慧來實現財務流程自動化、減少人為錯誤、提高效率並確保一致性正在對市場成長產生正面影響。此外,由於金融服務的快速全球化,擴大利用人工智慧來實現無縫跨境交易和支持,這也促進了市場的成長。此外,人工智慧在金融科技中的廣泛應用,從大量金融資料中獲得深刻的見解,正在加強市場的成長。此外,金融機構擴大採用人工智慧來降低營運成本並最大限度地減少體力勞動,這也支持了市場的成長。

金融科技市場趨勢/促進因素中的人工智慧:

科技的快速進步

人工智慧在金融科技中的整合很大程度上受到持續技術進步的影響。與此一致的是,整合機器學習(ML)演算法來完善巨量資料分析並擴大其在金融領域的潛在應用正在推動市場成長。此外,這些創新能夠高速且準確地處理和解釋大量資料,提供即時洞察和自動化功能。此外,量子運算和雲端技術的發展進一步增強了複雜金融建模所需的運算能力,正在推動市場成長。除此之外,金融科技公司正在利用這些先進技術來創造個人化銀行體驗、自動化交易,並以前所未有的精確度管理風險。此外,技術進步不僅提高了效率,也為全新產品和服務打開了大門。

監理合規需求不斷成長

金融業的運作遵循一套複雜的法規,各個司法管轄區的法規各不相同。遵守這些法規不僅是強制性的,而且對於維護消費者信任和金融體系的整體完整性也至關重要。據此,金融科技中的人工智慧在確保監管合規性以及自動監控和分析數百萬筆交易以檢測異常或不遵守相關法律方面發揮著至關重要的作用。除此之外,整合自然語言處理(NLP)來解釋不斷變化的監管文本,確保金融機構始終了解最新要求,並對市場成長產生正面影響。此外,合規流程的自動化減少了人為錯誤的可能性,並實現了對監管變化更加敏感和適應性更強的方法。

對個人化服務的需求不斷成長

消費者對包括金融在內的所有服務業的個人化體驗日益成長的期望正在推動市場成長。人工智慧透過分析大量客戶資料並識別個人偏好、消費習慣和財務需求,在滿足這項需求方面發揮著至關重要的作用。此外,這些資訊也用於為每位客戶量身定做金融產品、優惠和建議。此外,人工智慧使金融機構能夠透過以前無法實現的客製化等級提供個人化投資策略或個人化貸款優惠。除此之外,人工智慧的廣泛使用有助於提高客戶忠誠度、增加參與度和提高整體滿意度。因此,採用人工智慧創建量身定做的金融解決方案不僅是一種趨勢,而且是金融服務提供方式的根本性轉變。

人工智慧在金融科技產業細分:

IMARC Group提供了全球人工智慧金融科技市場報告各細分市場主要趨勢的分析,以及 2023 年至 2028 年全球、區域和國家層面的預測。我們的報告根據類型、部署模型和應用程式對市場進行了分類。

按類型分類:

解決方案

服務

解決方案主導市場

該報告根據類型提供了詳細的市場細分和分析。這包括解決方案和服務。根據該報告,解決方案代表了最大的部分。

人工智慧解決方案正在主導市場,因為它們旨在應對金融業的特定挑戰,例如詐欺偵測、風險管理和客戶服務。此外,他們還提供個人化服務,從而提高客戶參與度和滿意度。他們還幫助了解客戶行為並預測他們的需求,從而促進客製化產品和服務。除此之外,人工智慧解決方案旨在與現有金融系統無縫整合,這使得組織無需進行重大改革即可採用人工智慧,從而減少阻力並鼓勵採用。此外,它們可以根據業務需求和市場動態進行擴展,使公司能夠發展和適應,而無需在技術上進行大量額外投資。此外,人工智慧解決方案透過自動化日常任務和最佳化營運工作流程來節省成本。

按部署模型分類:

基於雲端

本地

基於雲端的主導市場

該報告根據部署模型對市場進行了詳細的細分和分析。這包括基於雲端的和本地的。根據該報告,基於雲端的佔據了最大的部分。

基於雲端的模型提供了一種經濟高效的解決方案,因為它們減少了對實體基礎設施的需求,促進了向營運支出模式的轉變。此外,它們還允許金融機構根據需求輕鬆擴展其人工智慧應用。此外,基於雲端的人工智慧解決方案提供從任何有網路連接的地方的訪問,這為員工提供了更靈活的工作環境,並允許即時的全球協作。除此之外,它們還允許快速實施和迭代,使金融機構能夠在快速發展的行業中保持領先地位。此外,雲端供應商擁有強大的安全措施,可以協助滿足合規性要求。此外,基於雲端的人工智慧解決方案可以更順暢地與現有系統和其他雲端服務整合,從而使金融組織能夠創建一個有凝聚力的技術生態系統,而無需面臨重大的定製或相容性挑戰。

按應用分類:

虛擬助理(聊天機器人)

信用評分

量化與資產管理

詐欺識別

其他

該報告根據應用程式提供了詳細的市場細分和分析。這包括虛擬協助(聊天機器人)、信用評分、定量和資產管理、詐欺檢測等。

由人工智慧支援的虛擬助理可以透過提供持續的客戶服務、處理查詢和即時解決問題來滿足各種客戶期望。此外,他們還可以透過同時處理大量查詢來大幅降低與客戶支援相關的勞動力成本,從而釋放人力資源以專注於更複雜的任務。此外,虛擬助理可以根據用戶個人資料和過去的互動提供個人化回應。這種程度的個人化可帶來更具吸引力和滿意度的客戶體驗。

人工智慧在信用評分過程中發揮著至關重要的作用,因為它可以分析大量資料,包括歷史信用資訊、交易歷史和社交媒體行為,從而可以更全面、更準確地評估個人或企業的信用度。此外,人工智慧驅動的信用評分可在幾秒鐘內提供結果,從而加快貸款核准速度並提高客戶滿意度。除此之外,它還可以根據各個金融機構的具體要求和風險偏好進行客製化。

按地區分類:

北美洲

美國

加拿大

亞太

中國

日本

印度

韓國

澳洲

印尼

其他

歐洲

德國

法國

英國

義大利

西班牙

俄羅斯

其他

拉丁美洲

巴西

墨西哥

其他

中東和非洲

北美在市場上表現出明顯的主導地位,在金融科技領域佔據最大的人工智慧市場佔有率

該報告還對所有主要區域市場進行了全面分析,其中包括北美(美國和加拿大);亞太地區(中國、日本、印度、韓國、澳洲、印尼等);歐洲(德國、法國、英國、義大利、西班牙等);拉丁美洲(巴西、墨西哥等);以及中東和非洲。報告稱,北美是最大的細分市場。

北美擁有許多技術創新中心,培育創新和創業文化,進而促進尖端人工智慧技術的發展。此外,該地區私營和公共部門對研發(R&D)措施進行了大量投資,以推動金融科技領域的技術進步和人工智慧商業化。除此之外,北美成熟的金融業為人工智慧的整合提供了肥沃的土壤,對市場的成長產生了正面的影響。除此之外,地方政府實施的支持性政策和法規,鼓勵負責任地使用人工智慧,正在推動市場成長。此外,容易獲得具有人工智慧、機器學習和資料科學專業知識的熟練專業人員,進一步推動了市場成長。

競爭格局:

頂尖公司正在探索新的演算法、方法和技術,以提高金融服務的效率、安全性和個人化。他們正在與金融科技新創公司和科技公司建立策略合作夥伴關係,以開發尖端解決方案並促進創新。此外,一些關鍵參與者正在實施預測分析和機器學習 (ML) 模型,以提供對客戶行為、市場趨勢和風險管理的見解。此外,頂級市場公司正在根據個人需求和偏好打造個人化服務和產品,包括個人化銀行業務、投資建議和客製化行銷策略。除此之外,領先公司正積極致力於開發透明且公正的人工智慧模型,強調道德的人工智慧實踐。此外,他們正在利用人工智慧為服務不足的人群提供金融服務,使用演算法以不同的方式評估信用度或透過人工智慧驅動的工具提供金融知識。

該報告對市場競爭格局進行了全面分析。也提供了所有主要公司的詳細資料。市場上的一些主要參與者包括:

亞馬遜網路服務公司(Amazon.com Inc)

谷歌有限責任公司(Alphabet Inc.)

因本塔技術公司

英特爾公司

國際商業機器公司

微軟公司

Salesforce.com 公司

三星電子有限公司

TIBCO 軟體公司

特里法塔

Verint 系統公司

最近的發展:

2023 年 6 月,亞馬遜網路服務公司 (Amazon.com Inc.) 與 NVIDIA 合作推出「全球金融科技加速器」計劃,以利用人工智慧推動早期金融科技新創公司的發展。

2023年6月,Google有限責任公司(Alphabet Inc.)推出反洗錢人工智慧(AML AI),幫助全球金融機構更有效、更有效率地偵測洗錢行為。

2023年1月,Inbenta Technologies Inc.獲得4,000萬美元融資,用於開發一個綜合平台,為金融服務、旅遊、電子商務、保險等產業客製化人工智慧驅動的解決方案。

本報告回答的關鍵問題

  • 全球人工智慧金融科技市場有多大
  • 2023-2028年全球人工智慧在金融科技市場的預期成長率是多少
  • 推動全球人工智慧金融科技市場發展的關鍵因素是什麼
  • COVID-19 對全球人工智慧金融科技市場有何影響
  • 全球人工智慧金融科技市場按類型分類是怎樣的
  • 基於部署模型,全球人工智慧在金融科技市場的細分是什麼
  • 全球人工智慧金融科技市場重點區域有哪些
  • 全球人工智慧金融科技市場的主要參與者/公司有哪些

本報告回答的關鍵問題

  • 全球人工智慧金融科技市場有多大?
  • 2023-2028年全球人工智慧在金融科技市場的預期成長率是多少?
  • 推動全球人工智慧金融科技市場發展的關鍵因素是什麼?
  • COVID-19 對全球金融科技市場人工智慧有何影響?
  • 全球人工智慧金融科技市場按類型分類是怎樣的?
  • 從部署模式來看,全球人工智慧在金融科技市場的詳細情形如何?
  • 全球人工智慧金融科技市場的重點區域有哪些?
  • 全球人工智慧金融科技市場的主要參與者/公司有哪些?

目錄

第 1 章:前言

第 2 章:範圍與方法

  • 研究目的
  • 利害關係人
  • 資料來源
    • 主要資源
    • 二手資料
  • 市場預測
    • 自下而上的方法
    • 自上而下的方法
  • 預測方法

第 3 章:執行摘要

第 4 章:簡介

  • 概述
  • 主要行業趨勢

第 5 章:金融科技市場中的全球人工智慧

  • 市場概況
  • 市場業績
  • COVID-19 的影響
  • 市場預測

第 6 章:按類型分類的市場細分

  • 解決方案
    • 市場走向
    • 市場預測
  • 服務
    • 市場走向
    • 市場預測

第 7 章:按部署模式分類的市場

  • 基於雲端
    • 市場走向
    • 市場預測
  • 本地
    • 市場走向
    • 市場預測

第 8 章:按應用分類的市場區隔

  • 虛擬助理(聊天機器人)
    • 市場走向
    • 市場預測
  • 信用評分
    • 市場走向
    • 市場預測
  • 量化與資產管理
    • 市場走向
    • 市場預測
  • 詐欺識別
    • 市場走向
    • 市場預測
  • 其他
    • 市場走向
    • 市場預測

第 9 章:按地區分類的市場區隔

  • 北美洲
    • 美國
      • 市場走向
      • 市場預測
    • 加拿大
      • 市場走向
      • 市場預測
  • 亞太
    • 中國
      • 市場走向
      • 市場預測
    • 日本
      • 市場走向
      • 市場預測
    • 印度
      • 市場走向
      • 市場預測
    • 韓國
      • 市場走向
      • 市場預測
    • 澳洲
      • 市場走向
      • 市場預測
    • 印尼
      • 市場走向
      • 市場預測
    • 其他
      • 市場走向
      • 市場預測
  • 歐洲
    • 德國
      • 市場走向
      • 市場預測
    • 法國
      • 市場走向
      • 市場預測
    • 英國
      • 市場走向
      • 市場預測
    • 義大利
      • 市場走向
      • 市場預測
    • 西班牙
      • 市場走向
      • 市場預測
    • 俄羅斯
      • 市場走向
      • 市場預測
    • 其他
      • 市場走向
      • 市場預測
  • 拉丁美洲
    • 巴西
      • 市場走向
      • 市場預測
    • 墨西哥
      • 市場走向
      • 市場預測
    • 其他
      • 市場走向
      • 市場預測
  • 中東和非洲
    • 市場走向
    • 按國家/地區分類的市場細分
    • 市場預測

第 10 章:SWOT 分析

  • 概述
  • 優勢
  • 弱點
  • 機會
  • 威脅

第 11 章:價值鏈分析

第 12 章:波特五力分析

  • 概述
  • 買家的議價能力
  • 供應商的議價能力
  • 競爭程度
  • 新進入者的威脅
  • 替代品的威脅

第 13 章:價格分析

第14章:競爭格局

  • 市場結構
  • 關鍵參與者
  • 關鍵參與者簡介
    • 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