Artificial Intelligence (AI) in Fintech Market Size, Share, and COVID-19 Impact Analysis by Component, Deployment Mode, Application, Regions, Company Market Share, and Regional Forecast, 2022-2030

Publish Date: Mar 2024
Report ID: ICT-1683
Base Year: 2023
Report Format: PDF, Excel
Report Pages: 197
Region: Global

According to the Regional Research Reports, the Global Artificial Intelligence (AI) in Fintech market is anticipated to reach USD 38.50 billion by 2030 from USD 8.23 billion in 2021. The global Artificial Intelligence (AI) in the Fintech market is projected to grow at a CAGR of 18.7% from 2022 to 2030. The Improvement in customer services with the help of chatbots, virtual helpers, artificial intelligence interfaces, and fraud detection drive the growth of the global AI in the fintech market. However, strict laws restrain the market growth. Contrarily, fintech companies are increasingly harnessing the power of AI for fintech crypto to automate workflows, improve decision-making, and add value. Therefore, this is a major factor expected to provide lucrative opportunities in the coming years.

Global Artificial Intelligence (AI) in Fintech Market Segmentation

Regional Research Reports has segmented the global Artificial Intelligence (AI) in Fintech market based on component, deployment mode, and application at a regional and global level. Geographically, the research report has considered the five regions: North America, Europe, Asia Pacific, South America, and the Middle East & Africa. Moreover, the research study focuses on the market analysis of the tier-1 countries, such as the USA, China, Germany, India, the UK, Japan, France, Italy, Spain, Russia, South Korea, and other territories.

Global Artificial Intelligence (AI) in Fintech Market Analysis by Component

  • Solution
  • Services

Global Artificial Intelligence (AI) in Fintech Market Analysis by Deployment Mode

  • On-premise
  • Cloud

Global Artificial Intelligence (AI) in Fintech Market Analysis by Application

  • Virtual Assistants (Chatbots)
  • Business Analytics and Reporting
  • Customer Behavioral Analytics
  • Others

Global Artificial Intelligence (AI) in Fintech Market Growth, by Region and Country, 2018-2021, 2022-2030 (US$ Millions)

Global Artificial Intelligence (AI) in Fintech Market Analysis by Region and Country

  • North America (US, Canada, Mexico)
  • Europe (Germany, UK, France, Italy, Spain, Russia, Switzerland, Poland, Belgium, the Netherlands, Norway, Sweden, Czech Republic, Slovakia, Slovenia, Rest of Europe)
  • Asia Pacific (China, India, Japan, South Korea, Indonesia, Thailand, Malaysia, Vietnam, Singapore, Australia & New Zealand, Rest of Asia Pacific)
  • South America (Brazil, Argentina, Peru, Colombia, Rest of South America)
  • The Middle East & Africa (UAE, Saudi Arabia, South Africa, Egypt, Qatar, Northern Africa, Rest of MEA)

Global Artificial Intelligence (AI) in Fintech Market Competitive: Key Players

The report includes a comprehensive analysis of leading market players, such as:

  • Key companies Artificial Intelligence (AI) in Fintech revenues in the global market, 2018-2021 (Estimated), (US$ Millions)
  • Key companies Artificial Intelligence (AI) in Fintech revenues market share in global market, 2021 (%)
  • Key companies Artificial Intelligence (AI) in Fintech sold in the global market, 2018-2021 (Estimated)

Leading Artificial Intelligence (AI) in Fintech Manufacturers –

  • Amazon Web Services, Inc.
  • Cisco Systems, Inc.
  • ComplyAdvantage
  • Cognizant
  • Capgemini
  • FICO
  • Google
  • Hewlett Packard Enterprise Development LP
  • HCL Technologies Limited
  • IBM
  • Intel Corporation
  • Inbenta Holdings Inc.
  • Microsoft
  • Oracle
  • Saleforce, Inc.
  • SAP SE
  • TIBCO Software, Inc.

(Note: The list of the key market players can be updated with the latest market scenario and trends)

Artificial Intelligence (AI) in Fintech Market Report Covers Comprehensive Analysis On:

  • Market Segmentation & Regional Analysis
  • Market Size of 10 years
  • Pricing Analysis
  • Supply & Demand Analysis
  • Component Life Cycle Analysis
  • Porter's Five Forces & Value/Supply Chain Analysis
  • Developed & Emerging Economies Analysis
  • PESTEL Analysis
  • Market and Forecast Factor Analysis
  • Market Opportunities, Risks, & Trends
  • Conclusion & Recommendation
  • Regulatory Landscape
  • Patent Analysis
  • Competition Landscape
  • 15+ Company Profiles

Artificial Intelligence (AI) in Fintech Market Research Methodology

The report is based on analysis through extensive secondary research and primary Interviews.

The secondary data sources include the company website, annual reports, investor presentations, press releases, white papers, journals, certified publications, government websites, and articles from the industry.

Similarly following is the list of a few paid secondary sources/databases,

  • Factiva
  • Statista
  • D&B Hoovers
  • Owler
  • Enlyft
  • HG Insights
  • Bloomberg
  • Crunchbase

The primary sources include CXOs, VPs, directors, component & innovation directors, component managers, and related executives from key organizations from both the supply and demand sides. Similarly, we have also interviewed various vehicle-type organizations. We cannot reveal the end-user organizations due to non-disclosure agreements.

For instance, the region forecast is based on extensive secondary research and primary Interviews. We have conducted primary interviews across the regions to get more region-specific insights. Additionally, primary interviews were conducted with independent consultants and subject matter experts in respective regions. These experts were interviewed to obtain qualitative and quantitative information related to the market and validate the research findings and estimations. The primary and secondary data inputs referred for triangulation and forecast for the region segment are as follows,

  • Top Player's historic revenues and Year on Year Growth
  • Top Players' regional presence and revenue patterns
  • Recent Developments and strategies of vendors and applications (E.g., Mergers & Acquisitions, Partnerships, New Component launches, and others)
  • R&D Investments & Innovation Landscape
  • Start-up Ecosystem and Funding Initiatives
  • Regulatory Environment and Implications (Country or region Specific)

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