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FintechにおけるAI市場レポート：タイプ、展開モデル、用途、地域別、2024年～2032年

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 2024-2032

出版日
発行
IMARC
ページ情報
英文 145 Pages
納期
2～3営業日
カスタマイズ可能
価格
価格表記: USDを日本円(税抜)に換算
本日の銀行送金レート: 1USD=143.57円
FintechにおけるAI市場レポート：タイプ、展開モデル、用途、地域別、2024年～2032年
出版日: 2024年09月10日
発行: IMARC
ページ情報: 英文 145 Pages
納期: 2～3営業日
GIIご利用のメリット
  • 全表示
  • 概要
  • 図表
  • 目次
概要

世界のFintechにおけるAI市場の市場規模は2023年に146億米ドルに達しました。今後、IMARC Groupは、2024年から2032年にかけて20.9%の成長率（CAGR）を示し、2032年までに877億米ドルに達すると予測しています。急速な技術進歩、規制遵守に対する需要の高まり、パーソナライズされたサービスに対する需要の高まり、金融リスクを軽減するためのFintechにおけるAIの広範な採用、サイバー詐欺の発生率の増加、金融プロセスを自動化するためのFintechにおけるAIの活用の高まりは、FintechにおけるAI市場の成長を促進する主な要因の一部です。

FintechにおけるAI市場の分析：

  • 市場の成長と規模：自動化ニーズの高まりに加え、リスク管理強化の必要性が高まっていることから、市場は堅調な成長を遂げています。
  • 技術の進歩：機械学習（ML）アルゴリズム、自然言語処理（NLP）、予測分析などの先進技術の統合により、市場の見通しは明るいです。
  • 産業への応用：AIは、銀行、保険、資産管理、トレーディングなど、金融業界のさまざまな分野で応用されています。
  • 地域別動向：北米は、大手ハイテク企業の存在により市場をリードしています。しかし、アジア太平洋地域はAI技術への投資が増加しており、急成長市場として浮上しています。
  • 競合情勢：伝統的な金融機関とテクノロジー企業の提携が市場成長を後押ししています。
  • 課題と機会：同市場は、データ・プライバシーに関する懸念などの課題に直面する一方で、不正検知への注目の高まりにより機会にも遭遇しています。
  • 将来の展望：AIを搭載したチャットボットの拡大により、FintechにおけるAI市場の将来性は有望視されています。また、倫理的なAIフレームワークの開発への注目が高まることで、市場の成長が見込まれます。

FintechにおけるAI市場の動向：

急速な技術進歩

FintechにおけるAIの統合は、現在進行中の技術進歩の影響を大きく受けています。これに伴い、機械学習（ML）アルゴリズムの統合により、ビッグデータ分析が洗練され、金融分野での潜在的な用途が拡大し、市場成長を後押ししています。さらに、こうした技術革新により、膨大な量のデータを高速で正確に処理・解釈することが可能になり、リアルタイムの洞察と自動化機能が提供されます。さらに、複雑な金融モデリングに必要な計算能力をさらに高める量子コンピューティングやクラウド技術の市場開拓が、市場の成長を後押ししています。このほか、フィンテック企業はこうした先端技術を活用して、パーソナライズされたバンキング体験や自動取引を実現し、かつてない精度でリスクを管理しています。さらに、技術の進歩は効率化を促進するだけでなく、まったく新しい商品やサービスへの扉を開くことにもなっています。

規制遵守への要求の高まり

金融業界は、法域によって異なる複雑な規制の下で運営されています。これらの規制を遵守することは必須であるだけでなく、消費者の信頼と金融システム全体の整合性を維持するためにも不可欠です。これに伴い、FintechにおけるAIは、規制遵守を確保し、何百万もの取引を自動的に監視・分析し、異常や関連法への不遵守を検知する上で重要な役割を果たしています。これとともに、自然言語処理（NLP）を統合して刻々と変化する規制の文章を解釈し、金融機関が常に最新の要件に対応できるようにすることが、市場の成長にプラスの影響を与えています。さらに、コンプライアンス・プロセスの自動化により、人為的ミスの可能性が低減し、規制変更に対するより迅速で適応性の高いアプローチが可能になります。

パーソナライズされたサービスへの需要の高まり

金融を含むあらゆるサービス分野で、パーソナライズされた体験に対する消費者の期待が高まっていることが、市場の成長を後押ししています。AIは、膨大な顧客データを分析し、個人の嗜好、消費習慣、金融ニーズを特定することで、この需要に応える上で重要な役割を果たしています。さらに、この情報は、金融商品、オファー、アドバイスを各顧客に合わせて調整するために使用されます。加えて、AIによって金融機関は、以前は実現不可能だったレベルのカスタマイズを通じて、個別化された投資戦略や個別化されたローン提案を提供できるようになります。これとは別に、AIの広範な活用は、顧客ロイヤルティの強化、エンゲージメントの向上、総合的な満足度の向上に役立っています。その結果、オーダーメイドの金融ソリューションの構築におけるAIの採用は、単なる動向ではなく、金融サービスの提供方法における根本的な転換となっています。

目次

第1章 序文

第2章 調査範囲と調査手法

  • 調査の目的
  • ステークホルダー
  • データソース
    • 一次情報
    • 二次情報
  • 市場推定
    • ボトムアップアプローチ
    • トップダウンアプローチ
  • 調査手法

第3章 エグゼクティブサマリー

第4章 イントロダクション

  • 概要
  • 主要業界動向

第5章 世界のFintechにおけるAI市場

  • 市場概要
  • 市場実績
  • COVID-19の影響
  • 市場予測

第6章 市場内訳：タイプ別

  • ソリューション
    • 市場動向
    • 市場予測
  • サービス
    • 市場動向
    • 市場予測

第7章 市場内訳：展開モデル別

  • クラウドベース
    • 市場動向
    • 市場予測
  • オンプレミス
    • 市場動向
    • 市場予測

第8章 市場内訳：用途別

  • バーチャルアシスタント（チャットボット）
    • 市場動向
    • 市場予測
  • 信用スコアリング
    • 市場動向
    • 市場予測
  • 定量分析と資産管理
    • 市場動向
    • 市場予測
  • 不正行為検出
    • 市場動向
    • 市場予測
  • その他
    • 市場動向
    • 市場予測

第9章 市場内訳：地域別

  • 北米
    • 米国
    • カナダ
  • アジア太平洋地域
    • 中国
    • 日本
    • インド
    • 韓国
    • オーストラリア
    • インドネシア
    • その他
  • 欧州
    • ドイツ
    • フランス
    • 英国
    • イタリア
    • スペイン
    • ロシア
    • その他
  • ラテンアメリカ
    • ブラジル
    • メキシコ
    • その他
  • 中東・アフリカ
    • 市場動向
    • 市場内訳：国別
    • 市場予測

第10章 SWOT分析

  • 概要
  • 強み
  • 弱み
  • 機会
  • 脅威

第11章 バリューチェーン分析

第12章 ポーターのファイブフォース分析

  • 概要
  • 買い手の交渉力
  • 供給企業の交渉力
  • 競合の程度
  • 新規参入業者の脅威
  • 代替品の脅威

第13章 価格分析

第14章 競合情勢

  • 市場構造
  • 主要企業
  • 主要企業のプロファイル
    • 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.
図表

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$), 2018-2023
  • Figure 3: Global: AI in Fintech Market Forecast: Sales Value (in Billion US$), 2024-2032
  • Figure 4: Global: AI in Fintech Market: Breakup by Type (in %), 2023
  • Figure 5: Global: AI in Fintech Market: Breakup by Deployment Model (in %), 2023
  • Figure 6: Global: AI in Fintech Market: Breakup by Application (in %), 2023
  • Figure 7: Global: AI in Fintech Market: Breakup by Region (in %), 2023
  • Figure 8: Global: AI in Fintech (Solutions) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 9: Global: AI in Fintech (Solutions) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 10: Global: AI in Fintech (Services) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 11: Global: AI in Fintech (Services) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 12: Global: AI in Fintech (Cloud-based) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 13: Global: AI in Fintech (Cloud-based) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 14: Global: AI in Fintech (On-premises) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 15: Global: AI in Fintech (On-premises) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 16: Global: AI in Fintech (Virtual Assistant-Chatbots) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 17: Global: AI in Fintech (Virtual Assistant-Chatbots) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 18: Global: AI in Fintech (Credit Scoring) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 19: Global: AI in Fintech (Credit Scoring) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 20: Global: AI in Fintech (Quantitative and Asset Management) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 21: Global: AI in Fintech (Quantitative and Asset Management) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 22: Global: AI in Fintech (Fraud Detection) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 23: Global: AI in Fintech (Fraud Detection) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 24: Global: AI in Fintech (Other Applications) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 25: Global: AI in Fintech (Other Applications) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 26: North America: AI in Fintech Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 27: North America: AI in Fintech Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 28: United States: AI in Fintech Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 29: United States: AI in Fintech Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 30: Canada: AI in Fintech Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 31: Canada: AI in Fintech Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 32: Asia-Pacific: AI in Fintech Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 33: Asia-Pacific: AI in Fintech Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 34: China: AI in Fintech Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 35: China: AI in Fintech Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 36: Japan: AI in Fintech Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 37: Japan: AI in Fintech Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 38: India: AI in Fintech Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 39: India: AI in Fintech Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 40: South Korea: AI in Fintech Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 41: South Korea: AI in Fintech Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 42: Australia: AI in Fintech Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 43: Australia: AI in Fintech Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 44: Indonesia: AI in Fintech Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 45: Indonesia: AI in Fintech Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 46: Others: AI in Fintech Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 47: Others: AI in Fintech Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 48: Europe: AI in Fintech Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 49: Europe: AI in Fintech Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 50: Germany: AI in Fintech Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 51: Germany: AI in Fintech Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 52: France: AI in Fintech Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 53: France: AI in Fintech Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 54: United Kingdom: AI in Fintech Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 55: United Kingdom: AI in Fintech Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 56: Italy: AI in Fintech Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 57: Italy: AI in Fintech Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 58: Spain: AI in Fintech Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 59: Spain: AI in Fintech Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 60: Russia: AI in Fintech Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 61: Russia: AI in Fintech Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 62: Others: AI in Fintech Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 63: Others: AI in Fintech Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 64: Latin America: AI in Fintech Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 65: Latin America: AI in Fintech Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 66: Brazil: AI in Fintech Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 67: Brazil: AI in Fintech Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 68: Mexico: AI in Fintech Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 69: Mexico: AI in Fintech Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 70: Others: AI in Fintech Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 71: Others: AI in Fintech Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 72: Middle East and Africa: AI in Fintech Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 73: Middle East and Africa: AI in Fintech Market: Breakup by Country (in %), 2023
  • Figure 74: Middle East and Africa: AI in Fintech Market Forecast: Sales Value (in Million US$), 2024-2032
  • 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, 2023 and 2032
  • Table 2: Global: AI in Fintech Market Forecast: Breakup by Type (in Million US$), 2024-2032
  • Table 3: Global: AI in Fintech Market Forecast: Breakup by Deployment Model (in Million US$), 2024-2032
  • Table 4: Global: AI in Fintech Market Forecast: Breakup by Application (in Million US$), 2024-2032
  • Table 5: Global: AI in Fintech Market Forecast: Breakup by Region (in Million US$), 2024-2032
  • Table 6: Global: AI in Fintech Market: Competitive Structure
  • Table 7: Global: AI in Fintech Market: Key Players
目次
Product Code: SR112024A4483

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