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Global Artificial Intelligence In Fintech Market Size, Share & Industry Trends Analysis Report By Component (Solutions and Services), By Deployment (On-premise and Cloud), By Application, By Regional Outlook and Forecast, 2022-2028

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    Report

  • 250 Pages
  • June 2022
  • Region: Global
  • Marqual IT Solutions Pvt. Ltd (KBV Research)
  • ID: 5636658
The Global Artificial Intelligence In Fintech Market size is expected to reach $25.8 billion by 2028, rising at a market growth of 16.8% CAGR during the forecast period.

Insurance executives and future banking agents is expected to ask the proper questions to robots rather than human experts as a result of data-driven management decisions at a reduced cost. Machines is expected to then analyze the data and provide recommendations that will aid leaders and subordinates in making better decisions. Users can employ automated financial assistants and planners to help them make financial decisions. These include events tracking, stock and bond price trends based on the user's financial goals and personal portfolio, that can aid in the recommendation of bonds and stocks to buy or sell. These systems, dubbed 'Robo-Advisors', are highly being provided by both traditional financial firms and Fintech startups.



Bright well Payments, a financial services firm that offers financial solutions to transport money safely anywhere in the world, announced the launching of ARDEN in May 2022. This risk-detection engine powered by AI helps fintech companies protect their cardholders and financial assets. Globally, banks are implementing AI-enabled solutions to enhance safety, and AI provides banks the advantage of digitization. Additionally, it enables them engage with other fintech businesses. Apps that necessitate UPI, a fingerprint, or facial recognition are available from financial institutions.

UPI is one of the most widely used digital payment systems in India, and the system was created to enable payments to be executed in seconds. To generate critical insights, financial firms utilize AI to handle and assess data from a variety of sources. Banks might use such inventive solutions to solve challenges they have when providing services like payment processing and loan management. Many banking apps offer personalized financial advice to assist users in achieving their financial goals, tracking their income & expenditures, and performing other financial chores. AI-powered finance advances are primarily responsible for this customization.

COVID-19 Impact Analysis

The latest coronavirus outbreak has been beneficial to the market. Due to the coronavirus pandemic, business activity has been halted, resulting in disruptions in border restrictions, supply chains, and travel restrictions imposed by government bodies. As a result, banks and fintech companies are adopting a work-from-home attitude. Moreover, banks and financial institutions are implementing AI technologies to extract information and insights from unstructured documents and automate the laborious procedure that banks have traditionally completed in shorter period of time. For example, Temenos, a banking software business, announced the introduction of eight propositions in April 2020, utilizing breakthrough Explainable AI (XAI) and cloud technologies to assist banks and financial institutions in responding to the COVID-19 situation.



The leading players in the market are competing with diverse innovative offerings to remain competitive in the market. The below illustration shows the percentage of revenue shared by some of the leading companies in the market. The leading players of the market are adopting various strategies in order to cater demand coming from the different industries. The key developmental strategies in the market are Partnerships & Collaborations.

Market Growth Factors


Reduction in cost and better efficiency along with enhanced wealth management

Artificial intelligence in fintech is enabling businesses to minimize costs, automate processes, and lessen the risk of human mistake. Companies utilize AI Chatbots as customer assistants for a variety of tasks, including sales, customer service (over the phone), and online chat. AI is enabling small finance organizations since it is cost-effective and has a minimal risk of error. Furthermore, the end user is gaining momentum for the insightful facts regarding cash flow, income, and expense, as this is expected to assist organizations cut their expenses. Lesser net worth market groups are provided digital and wealth management advice services, leading to low fee-based commissions.

Various technological enhancements is expected to increase the popularity of AI in fintech

Credit card fraud is one of the most common types of cybercrime. As a result, firms are developing the next-generation of algorithms called Convolutional Neural Networks, which are based on the visual cortex, a small portion of cells in the human body that is sensitive to particular regions of the visual field. They can extract basic visual elements such as aligned edges, end-points, and corners in this way. This system can analyze an individual's funding data and establish whether they made the most recent credit card transaction or if their credit card data was used by someone else based on that data.

Marketing Restraining Factor:


Data security and privacy concerns of the users

Most fintech businesses are dealing with the sensitive topic of data privacy and security that is the largest hurdle with AI. Because any data breach or security failure might be disastrous, the fintech sector is overseen by tight adherence to standards and governance. Since businesses nourish more and more user and provider information into advanced, AI-fueled algorithms, innovative bits of personal data are created without the knowledge of the way it affected clients and employees, which ultimately leads to the rising privacy concerns. This is especially true in the retail banking industry, in which the collection of consumer data is at the forefront of big data challenges.



Component Outlook

Based on Component, the market is segmented into Solutions and Services. The solution segment procured the highest revenue share in the Artificial Intelligence In Fintech Market in 2021. The high proportion can be due to software tools, which help banks adopt AI-enabled solutions that extract correct and comprehensive data from large amounts of data in a timely manner. Some firms' solutions help them accomplish things like develop their retail banking company with next-best-action software, identify and battle financial fraud, and improve client relationships with multichannel user experience solutions.

Deployment Outlook

Based on Deployment, the market is segmented into On-premise and Cloud. The cloud segment garnered a substantial revenue share in the Artificial Intelligence In Fintech Market in 2021. From 2022 to 2030, the cloud segment will grow at the quickest rate. AI-based algorithms that learn from historical data in a public cloud, detect current norms, and make recommendations are credited with the increase. In data handling and authenticity, the cloud and AI may boost efficiency, and digital security, and this automated technique removes human errors throughout data processing.

Application Outlook

Based on Application, the market is segmented into Business Analytics & Reporting, Customer Behavioral Analytics, Fraud Detection, Virtual Assistant (Chatbots), Quantitative & Asset Management and Others. Business Analytics and Reporting segment witnessed the maximum revenue share in the Artificial Intelligence In Fintech Market in 2021. Regulatory and compliance management, as well as customer behaviour monitoring, benefit from business analytics and reporting. More efficiency, more educated decision, and higher revenues are all elements that have contributed to the segment's growth.

Regional Outlook

Based on Regions, the market is segmented into North America, Europe, Asia Pacific, and Latin America, Middle East & Africa. North America emerged as a leading region in the Artificial Intelligence In Fintech Market with the largest revenue share in 2021. It is due to the industrialized economies of the United States and Canada placing a major focus on R&D-derived technologies. In fintech, this region has the most competitive and rapidly developing AI technology. Many startups and rising firms that provide AI services to the finance sector are also fueling the trend.

Cardinal Matrix-Artificial Intelligence In Fintech Market Competition Analysis




The major strategies followed by the market participants are Partnerships. Based on the Analysis presented in the Cardinal matrix; Microsoft Corporation and Google LLC are the forerunners in the Artificial Intelligence In Fintech Market. Companies such as Oracle Corporation, Intel Corporation and IBM Corporation are some of the key innovators in the Market.

The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include IBM Corporation, Oracle Corporation, Microsoft Corporation, Google LLC, Intel Corporation, Salesforce.com, Inc., Amazon Web Services, Inc., ComplyAdvantage, Amelia US LLC, and Inbenta Technologies, Inc.

Recent Strategies deployed in Artificial Intelligence In Fintech Market


Partnerships, Collaborations and Agreements:

  • Jun-2022: Amazon Web Services (AWS) teamed up with Hong Kong Science and Technology Parks Corporation (HKSTP). This collaboration aimed to boost a robust Innovation and Technology (I&T) ecosystem in Hong Kong. Through this collaboration, AWS and HKSTP is expected to introduce a series of programs under four key pillars to accelerate the innovation of IT companies, startups, and researchers across their whole growth cycle.
  • May-2022: Amazon Web Services (AWS) joined hands with RBL Bank and Amazon Pay. This collaboration aimed to introduce UPI payments, along with offering peer-to-peer and peer-to-merchant transactions. Through this integration, Amazon Pay is expected to issue NPCI’s allocated UPI ID with the manage @rapl, to RBL Bank.
  • May-2022: Oracle PartnerNetwork (OPN) collaborated with Temenos, the cloud banking platform. The collaboration aimed to allow Oracle’s global customers like financial services organizations across the world, to implement its robust Explainable AI and machine learning capabilities through Oracle Cloud Marketplace.
  • May-2022: Salesforce came into a partnership with Upstart, a leading artificial intelligence (AI) lending platform. This partnership aimed to bring AI-enabled lending to the financial services industry, which can assist financial institutions to modernize lending, stay competitive, and delivering better customer service to users.
  • Apr-2022: ComplyAdvantage came into a partnership with Xapien, a deep-technology company. This partnership aimed to provide a ground-breaking due diligence solution to the market, wherein there is a huge requirement for a deep understanding of sanctioned parties or PEPs.
  • Apr-2022: IBM formed a partnership with Skyscend, a fintech start-up with headquarters in Atlanta, GA. Under this partnership, IBM's Embedded Solution Agreement (ESA) is expected to enable Skyscend to integrate IBM's cutting-edge technologies with its Skyscend Pay B2B SaaS fintech platform to service the global marketplace.
  • Mar-2022: Google Cloud came into a partnership with Mizuho Financial Group (MFG), a Japanese bank holding company. This partnership aimed to show the firm modernize its systems, develop a new digital marketing platform on Google Cloud, and release a new digital financial service portfolio like Banking-as-a-Service (BaaS).
  • Feb-2022: Google Cloud entered into a partnership with KeyBank, and Deloitte. This partnership aimed to boost KeyBank’s commitment to a cloud-first approach to banking. In this partnership, KeyBank is expected to become the largest regional banks in the United States to manage its primary platforms and applications on Google Cloud infrastructure, enabling the financial institution to shift the way it creates, operationalizes, and provides digital experiences to customers, partners, and teammates with security at its core.
  • Feb-2022: Microsoft came into partnership with U.S. Bank as part of a significant investment by US bank in its technology infrastructure. This partnership aimed to use Artificial intelligence (AI) and machine learning (ML) in order to support the bank’s applications and infrastructure along with augmenting customer privacy and the security of data and financial assets.
  • Oct-2021: Oracle NetSuite teamed up with HSBC, a British multinational universal bank and financial services holding company. This collaboration aimed to introduce a Banking as a Service (BaaS) offering, which is expected to allow customers to provide business banking services via their own platforms.
  • Feb-2021: Google Cloud formed a partnership with BBVA, a customer-centric global financial services group. This partnership aimed to transform the bank’s security strategy by enhancing and optimizing its security infrastructure. Under this partnership, BBVA is expected to collaborate with Google Cloud in the development of the new artificial intelligence (AI) and machine learning (ML) models to forecast and prevent cyberattacks against its banking infrastructure, offering a more secure experience for the bank and its customers.
  • Dec-2020: Google Cloud formed a partnership with Deutsche Bank, one of the world's leading financial service providers. This partnership aimed to boost the transformation of the bank to the cloud. For Deutsche Bank’s customers, the agreement is expected to reshape the way products and services are developed and delivered.
  • Jul-2020: Microsoft signed a multi-year cloud agreement with Finastra, a financial software company. This agreement aimed to assist the digital transformation of financial services. Together, the companies is expected to support banks, credit unions, and other firms in the sector to utilize Power Platform, Azure, and Microsoft 365.

Product Launches and Product Expansions:

  • Apr-2022: Salesforce released CRM Analytics, AI-based insights for sales, marketing, and service teams in every industry. These technologies is expected to assist sales leaders, service leaders, and employees across any industry like financial services, consumer goods, manufacturing, and communications, put data at the center of each customer relationship, and eventually provide more customized experiences.
  • Apr-2022: IBM introduced IBM z16, Real-Time AI for Transaction Processing. This technology is expected to bring AI inferencing, through its IBM Telum Processor, with highly protected and reliable high-volume transaction processing.
  • Jan-2022: Google introduced a Google Cloud digital assets team. This team is expected to support customers' requirements in building, transacting, storing value, and deploying new products on blockchain-based platforms.
  • May-2021: IBM introduced new advances in artificial intelligence (AI), hybrid cloud, and quantum computing. These advanced is expected to assist IBM's customers and partners boost their digital transformations, returning to work smarter, and developing strategic ecosystems that is expected to generate better business results.
  • Apr-2021: ComplyAdvantage released a new early-stage anti-money laundering (AML) program. The program is expected to offer qualified startups free access to the company’s leading AML and Know Your Customer (KYC) tools and resources required to uncover and decrease the threat of money-laundering activities.
  • Nov-2020: Google Cloud unveiled the new Document AI (DocAI) platform, a unified console for document processing. Through this latest DocAI platform, customers can rapidly access all parsers, tools, and solutions with a unified API, allowing an end-to-end document solution from evaluation to deployment.

Acquisitions and Mergers:

  • Mar-2022: Microsoft took over Nuance Communications, artificial intelligence (AI), and speech technology firm. This acquisition aimed to bring together Nuance’s best-in-class conversational AI and ambient intelligence with Microsoft’s safe and trusted industry cloud portfolio.
  • Jan-2022: Oracle took over Federos, a provider of unified service management solutions for service providers. This acquisition aimed to expand Oracle Communications’ application portfolio by introducing AI-optimized assurance, analytics, and automation solutions to maintain the accessibility and performance of crucial networks and systems.
  • Dec-2020: IBM took over Expertus Technologies, a Montreal-based fintech company. This acquisition aimed to strengthen IBM's portfolio as an end-to-end digital payments solution provider and improve IBM's hybrid cloud and AI strategy.
  • Oct-2020: Intel completed the acquisition of SigOpt, a startup out of San Francisco. Through this acquisition, Intel is expected to double down on building chips and related architecture for the next generation of computing, which is expected to boost Intel's expertise in the area of future technology: artificial intelligence.

Scope of the Study


Market Segments Covered in the Report:


By Component
  • Solutions
  • Services
By Deployment
  • On-premise
  • Cloud
By Application
  • Business Analytics & Reporting
  • Customer Behavioral Analytics
  • Fraud Detection
  • Virtual Assistant (Chatbots)
  • Quantitative & Asset Management
  • Others
By Geography
  • North America
  • US
  • Canada
  • Mexico
  • Rest of North America
  • Europe
  • Germany
  • UK
  • France
  • Russia
  • Spain
  • Italy
  • Rest of Europe
  • Asia Pacific
  • China
  • Japan
  • India
  • South Korea
  • Singapore
  • Malaysia
  • Rest of Asia Pacific
  • LAMEA
  • Brazil
  • Argentina
  • UAE
  • Saudi Arabia
  • South Africa
  • Nigeria
  • Rest of LAMEA

Key Market Players


List of Companies Profiled in the Report:

  • IBM Corporation
  • Oracle Corporation
  • Microsoft Corporation
  • Google LLC
  • Intel Corporation
  • Salesforce.com, Inc.
  • Amazon Web Services, Inc.
  • ComplyAdvantage
  • Amelia US LLC
  • Inbenta Technologies, Inc.

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Table of Contents

Chapter 1. Market Scope & Methodology
1.1 Market Definition
1.2 Objectives
1.3 Market Scope
1.4 Segmentation
1.4.1 Global Artificial Intelligence In Fintech Market, by Component
1.4.2 Global Artificial Intelligence In Fintech Market, by Deployment
1.4.3 Global Artificial Intelligence In Fintech Market, by Application
1.4.4 Global Artificial Intelligence In Fintech Market, by Geography
1.5 Methodology for the research
Chapter 2. Market Overview
2.1 Introduction
2.1.1 Overview
2.1.1.1 Market Composition and Scenario
2.2 Key Factors Impacting the Market
2.2.1 Market Drivers
2.2.2 Market Restraints
Chapter 3. Competition Analysis - Global
3.1 Cardinal Matrix
3.2 Recent Industry Wide Strategic Developments
3.2.1 Partnerships, Collaborations and Agreements
3.2.2 Product Launches and Product Expansions
3.2.3 Acquisition and Mergers
3.3 Market Share Analysis, 2021
3.4 Top Winning Strategies
3.4.1 Key Leading Strategies Percentage Distribution (2018-2022)
3.4.2 Key Strategic Move (Partnerships, Collaborations and Agreements 2018, Nov - 2022, Jun) Leading Players
Chapter 4. Global Artificial Intelligence In Fintech Market by Component
4.1 Global Solutions Market by Region
4.2 Global Services Market by Region
Chapter 5. Global Artificial Intelligence In Fintech Market by Deployment
5.1 Global On-premise Market by Region
5.2 Global Cloud Market by Region
Chapter 6. Global Artificial Intelligence In Fintech Market by Application
6.1 Global Business Analytics & Reporting Market by Region
6.2 Global Customer Behavioural Analytics Market by Region
6.3 Global Fraud Detection Market by Region
6.4 Global Virtual Assistant (Chatbots) Market by Region
6.5 Global Quantitative & Asset Management Market by Region
6.6 Global Others Market by Region
Chapter 7. Global Artificial Intelligence In Fintech Market by Region
7.1 North America Artificial Intelligence In Fintech Market
7.1.1 North America Artificial Intelligence In Fintech Market by Component
7.1.1.1 North America Solutions Market by Country
7.1.1.2 North America Services Market by Country
7.1.2 North America Artificial Intelligence In Fintech Market by Deployment
7.1.2.1 North America On-premise Market by Country
7.1.2.2 North America Cloud Market by Country
7.1.3 North America Artificial Intelligence In Fintech Market by Application
7.1.3.1 North America Business Analytics & Reporting Market by Country
7.1.3.2 North America Customer Behavioral Analytics Market by Country
7.1.3.3 North America Fraud Detection Market by Country
7.1.3.4 North America Virtual Assistant (Chatbots) Market by Country
7.1.3.5 North America Quantitative & Asset Management Market by Country
7.1.3.6 North America Others Market by Country
7.1.4 North America Artificial Intelligence In Fintech Market by Country
7.1.4.1 US Artificial Intelligence In Fintech Market
7.1.4.1.1 US Artificial Intelligence In Fintech Market by Component
7.1.4.1.2 US Artificial Intelligence In Fintech Market by Deployment
7.1.4.1.3 US Artificial Intelligence In Fintech Market by Application
7.1.4.2 Canada Artificial Intelligence In Fintech Market
7.1.4.2.1 Canada Artificial Intelligence In Fintech Market by Component
7.1.4.2.2 Canada Artificial Intelligence In Fintech Market by Deployment
7.1.4.2.3 Canada Artificial Intelligence In Fintech Market by Application
7.1.4.3 Mexico Artificial Intelligence In Fintech Market
7.1.4.3.1 Mexico Artificial Intelligence In Fintech Market by Component
7.1.4.3.2 Mexico Artificial Intelligence In Fintech Market by Deployment
7.1.4.3.3 Mexico Artificial Intelligence In Fintech Market by Application
7.1.4.4 Rest of North America Artificial Intelligence In Fintech Market
7.1.4.4.1 Rest of North America Artificial Intelligence In Fintech Market by Component
7.1.4.4.2 Rest of North America Artificial Intelligence In Fintech Market by Deployment
7.1.4.4.3 Rest of North America Artificial Intelligence In Fintech Market by Application
7.2 Europe Artificial Intelligence In Fintech Market
7.2.1 Europe Artificial Intelligence In Fintech Market by Component
7.2.1.1 Europe Solutions Market by Country
7.2.1.2 Europe Services Market by Country
7.2.2 Europe Artificial Intelligence In Fintech Market by Deployment
7.2.2.1 Europe On-premise Market by Country
7.2.2.2 Europe Cloud Market by Country
7.2.3 Europe Artificial Intelligence In Fintech Market by Application
7.2.3.1 Europe Business Analytics & Reporting Market by Country
7.2.3.2 Europe Customer Behavioural Analytics Market by Country
7.2.3.3 Europe Fraud Detection Market by Country
7.2.3.4 Europe Virtual Assistant (Chatbots) Market by Country
7.2.3.5 Europe Quantitative & Asset Management Market by Country
7.2.3.6 Europe Others Market by Country
7.2.4 Europe Artificial Intelligence In Fintech Market by Country
7.2.4.1 Germany Artificial Intelligence In Fintech Market
7.2.4.1.1 Germany Artificial Intelligence In Fintech Market by Component
7.2.4.1.2 Germany Artificial Intelligence In Fintech Market by Deployment
7.2.4.1.3 Germany Artificial Intelligence In Fintech Market by Application
7.2.4.2 UK Artificial Intelligence In Fintech Market
7.2.4.2.1 UK Artificial Intelligence In Fintech Market by Component
7.2.4.2.2 UK Artificial Intelligence In Fintech Market by Deployment
7.2.4.2.3 UK Artificial Intelligence In Fintech Market by Application
7.2.4.3 France Artificial Intelligence In Fintech Market
7.2.4.3.1 France Artificial Intelligence In Fintech Market by Component
7.2.4.3.2 France Artificial Intelligence In Fintech Market by Deployment
7.2.4.3.3 France Artificial Intelligence In Fintech Market by Application
7.2.4.4 Russia Artificial Intelligence In Fintech Market
7.2.4.4.1 Russia Artificial Intelligence In Fintech Market by Component
7.2.4.4.2 Russia Artificial Intelligence In Fintech Market by Deployment
7.2.4.4.3 Russia Artificial Intelligence In Fintech Market by Application
7.2.4.5 Spain Artificial Intelligence In Fintech Market
7.2.4.5.1 Spain Artificial Intelligence In Fintech Market by Component
7.2.4.5.2 Spain Artificial Intelligence In Fintech Market by Deployment
7.2.4.5.3 Spain Artificial Intelligence In Fintech Market by Application
7.2.4.6 Italy Artificial Intelligence In Fintech Market
7.2.4.6.1 Italy Artificial Intelligence In Fintech Market by Component
7.2.4.6.2 Italy Artificial Intelligence In Fintech Market by Deployment
7.2.4.6.3 Italy Artificial Intelligence In Fintech Market by Application
7.2.4.7 Rest of Europe Artificial Intelligence In Fintech Market
7.2.4.7.1 Rest of Europe Artificial Intelligence In Fintech Market by Component
7.2.4.7.2 Rest of Europe Artificial Intelligence In Fintech Market by Deployment
7.2.4.7.3 Rest of Europe Artificial Intelligence In Fintech Market by Application
7.3 Asia Pacific Artificial Intelligence In Fintech Market
7.3.1 Asia Pacific Artificial Intelligence In Fintech Market by Component
7.3.1.1 Asia Pacific Solutions Market by Country
7.3.1.2 Asia Pacific Services Market by Country
7.3.2 Asia Pacific Artificial Intelligence In Fintech Market by Deployment
7.3.2.1 Asia Pacific On-premise Market by Country
7.3.2.2 Asia Pacific Cloud Market by Country
7.3.3 Asia Pacific Artificial Intelligence In Fintech Market by Application
7.3.3.1 Asia Pacific Business Analytics & Reporting Market by Country
7.3.3.2 Asia Pacific Customer Behavioural Analytics Market by Country
7.3.3.3 Asia Pacific Fraud Detection Market by Country
7.3.3.4 Asia Pacific Virtual Assistant (Chatbots) Market by Country
7.3.3.5 Asia Pacific Quantitative & Asset Management Market by Country
7.3.3.6 Asia Pacific Others Market by Country
7.3.4 Asia Pacific Artificial Intelligence In Fintech Market by Country
7.3.4.1 China Artificial Intelligence In Fintech Market
7.3.4.1.1 China Artificial Intelligence In Fintech Market by Component
7.3.4.1.2 China Artificial Intelligence In Fintech Market by Deployment
7.3.4.1.3 China Artificial Intelligence In Fintech Market by Application
7.3.4.2 Japan Artificial Intelligence In Fintech Market
7.3.4.2.1 Japan Artificial Intelligence In Fintech Market by Component
7.3.4.2.2 Japan Artificial Intelligence In Fintech Market by Deployment
7.3.4.2.3 Japan Artificial Intelligence In Fintech Market by Application
7.3.4.3 India Artificial Intelligence In Fintech Market
7.3.4.3.1 India Artificial Intelligence In Fintech Market by Component
7.3.4.3.2 India Artificial Intelligence In Fintech Market by Deployment
7.3.4.3.3 India Artificial Intelligence In Fintech Market by Application
7.3.4.4 South Korea Artificial Intelligence In Fintech Market
7.3.4.4.1 South Korea Artificial Intelligence In Fintech Market by Component
7.3.4.4.2 South Korea Artificial Intelligence In Fintech Market by Deployment
7.3.4.4.3 South Korea Artificial Intelligence In Fintech Market by Application
7.3.4.5 Singapore Artificial Intelligence In Fintech Market
7.3.4.5.1 Singapore Artificial Intelligence In Fintech Market by Component
7.3.4.5.2 Singapore Artificial Intelligence In Fintech Market by Deployment
7.3.4.5.3 Singapore Artificial Intelligence In Fintech Market by Application
7.3.4.6 Malaysia Artificial Intelligence In Fintech Market
7.3.4.6.1 Malaysia Artificial Intelligence In Fintech Market by Component
7.3.4.6.2 Malaysia Artificial Intelligence In Fintech Market by Deployment
7.3.4.6.3 Malaysia Artificial Intelligence In Fintech Market by Application
7.3.4.7 Rest of Asia Pacific Artificial Intelligence In Fintech Market
7.3.4.7.1 Rest of Asia Pacific Artificial Intelligence In Fintech Market by Component
7.3.4.7.2 Rest of Asia Pacific Artificial Intelligence In Fintech Market by Deployment
7.3.4.7.3 Rest of Asia Pacific Artificial Intelligence In Fintech Market by Application
7.4 LAMEA Artificial Intelligence In Fintech Market
7.4.1 LAMEA Artificial Intelligence In Fintech Market by Component
7.4.1.1 LAMEA Solutions Market by Country
7.4.1.2 LAMEA Services Market by Country
7.4.2 LAMEA Artificial Intelligence In Fintech Market by Deployment
7.4.2.1 LAMEA On-premise Market by Country
7.4.2.2 LAMEA Cloud Market by Country
7.4.3 LAMEA Artificial Intelligence In Fintech Market by Application
7.4.3.1 LAMEA Business Analytics & Reporting Market by Country
7.4.3.2 LAMEA Customer Behavioural Analytics Market by Country
7.4.3.3 LAMEA Fraud Detection Market by Country
7.4.3.4 LAMEA Virtual Assistant (Chatbots) Market by Country
7.4.3.5 LAMEA Quantitative & Asset Management Market by Country
7.4.3.6 LAMEA Others Market by Country
7.4.4 LAMEA Artificial Intelligence In Fintech Market by Country
7.4.4.1 Brazil Artificial Intelligence In Fintech Market
7.4.4.1.1 Brazil Artificial Intelligence In Fintech Market by Component
7.4.4.1.2 Brazil Artificial Intelligence In Fintech Market by Deployment
7.4.4.1.3 Brazil Artificial Intelligence In Fintech Market by Application
7.4.4.2 Argentina Artificial Intelligence In Fintech Market
7.4.4.2.1 Argentina Artificial Intelligence In Fintech Market by Component
7.4.4.2.2 Argentina Artificial Intelligence In Fintech Market by Deployment
7.4.4.2.3 Argentina Artificial Intelligence In Fintech Market by Application
7.4.4.3 UAE Artificial Intelligence In Fintech Market
7.4.4.3.1 UAE Artificial Intelligence In Fintech Market by Component
7.4.4.3.2 UAE Artificial Intelligence In Fintech Market by Deployment
7.4.4.3.3 UAE Artificial Intelligence In Fintech Market by Application
7.4.4.4 Saudi Arabia Artificial Intelligence In Fintech Market
7.4.4.4.1 Saudi Arabia Artificial Intelligence In Fintech Market by Component
7.4.4.4.2 Saudi Arabia Artificial Intelligence In Fintech Market by Deployment
7.4.4.4.3 Saudi Arabia Artificial Intelligence In Fintech Market by Application
7.4.4.5 South Africa Artificial Intelligence In Fintech Market
7.4.4.5.1 South Africa Artificial Intelligence In Fintech Market by Component
7.4.4.5.2 South Africa Artificial Intelligence In Fintech Market by Deployment
7.4.4.5.3 South Africa Artificial Intelligence In Fintech Market by Application
7.4.4.6 Nigeria Artificial Intelligence In Fintech Market
7.4.4.6.1 Nigeria Artificial Intelligence In Fintech Market by Component
7.4.4.6.2 Nigeria Artificial Intelligence In Fintech Market by Deployment
7.4.4.6.3 Nigeria Artificial Intelligence In Fintech Market by Application
7.4.4.7 Rest of LAMEA Artificial Intelligence In Fintech Market
7.4.4.7.1 Rest of LAMEA Artificial Intelligence In Fintech Market by Component
7.4.4.7.2 Rest of LAMEA Artificial Intelligence In Fintech Market by Deployment
7.4.4.7.3 Rest of LAMEA Artificial Intelligence In Fintech Market by Application
Chapter 8. Company Profiles
8.1 IBM Corporation
8.1.1 Company Overview
8.1.2 Financial Analysis
8.1.3 Regional & Segmental Analysis
8.1.4 Research & Development Expenses
8.1.5 Recent strategies and developments
8.1.5.1 Partnerships, Collaborations, and Agreements
8.1.5.2 Product Launches and Product Expansions
8.1.5.3 Acquisition and Mergers
8.1.6 SWOT Analysis
8.2 Oracle Corporation
8.2.1 Company Overview
8.2.2 Financial Analysis
8.2.3 Segmental and Regional Analysis
8.2.4 Research & Development Expense
8.2.5 Recent strategies and developments
8.2.5.1 Partnerships, Collaborations, and Agreements
8.2.5.2 Acquisition and Mergers
8.2.6 SWOT Analysis
8.3 Microsoft Corporation
8.3.1 Company Overview
8.3.2 Financial Analysis
8.3.3 Segmental and Regional Analysis
8.3.4 Research & Development Expenses
8.3.5 Recent strategies and developments
8.3.5.1 Partnerships, Collaborations, and Agreements
8.3.5.2 Acquisition and Mergers
8.3.6 SWOT Analysis
8.4 Google LLC
8.4.1 Company Overview
8.4.2 Financial Analysis
8.4.3 Segmental and Regional Analysis
8.4.4 Research & Development Expense
8.4.5 Recent strategies and developments
8.4.5.1 Partnerships, Collaborations, and Agreements
8.4.5.2 Product Launches and Product Expansions
8.4.6 SWOT Analysis
8.5 Intel Corporation
8.5.1 Company Overview
8.5.2 Financial Analysis
8.5.3 Segmental and Regional Analysis
8.5.4 Research & Development Expenses
8.5.5 Recent strategies and developments
8.5.5.1 Partnerships, Collaborations, and Agreements
8.5.5.2 Acquisition and Mergers
8.5.6 SWOT Analysis
8.6 Salesforce.com, Inc.
8.6.1 Company Overview
8.6.2 Financial Analysis
8.6.3 Regional Analysis
8.6.4 Research & Development Expense
8.6.5 Recent strategies and developments
8.6.5.1 Partnerships, Collaborations, and Agreements
8.6.5.2 Product Launches and Product Expansions
8.6.6 SWOT Analysis
8.7 Amazon Web Services, Inc. (Amazon.com, Inc.)
8.7.1 Company Overview
8.7.2 Financial Analysis
8.7.3 Segmental Analysis
8.7.4 Recent strategies and developments
8.7.4.1 Partnerships, Collaborations, and Agreements
8.8 ComplyAdvantage
8.8.1 Company Overview
8.8.2 Recent strategies and developments
8.8.2.1 Partnerships, Collaborations, and Agreements
8.8.2.2 Product Launches and Product Expansions
8.9 Amelia US LLC (IPSoft)
8.9.1 Company Overview
8.9.2 Recent strategies and developments
8.9.2.1 Product Launches and Product Expansions
8.10. Inbenta technologies, Inc.
8.10.1 Company Overview

Companies Mentioned

  • IBM Corporation
  • Oracle Corporation
  • Microsoft Corporation
  • Google LLC
  • Intel Corporation
  • Salesforce.com, Inc.
  • Amazon Web Services, Inc.
  • ComplyAdvantage
  • Amelia US LLC
  • Inbenta Technologies, Inc.

Methodology

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