February 6, 2023

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.
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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Insurance executives and future banking agents would ask the proper questions to robots rather than human experts as a result of data-driven management decisions at a reduced cost. Machines would 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
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.
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 would 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 would 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.
Market Restraining Factors
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.
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.
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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 would 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 would 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) would 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 would 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 would 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 would 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 would 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 would 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 would 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 would 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 would 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 would assist IBM’s customers and partners boost their digital transformations, returning to work smarter, and developing strategic ecosystems that would generate better business results.
Apr-2021: ComplyAdvantage released a new early-stage anti-money laundering (AML) program. The program would 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 would double down on building chips and related architecture for the next generation of computing, which would boost Intel’s expertise in the area of future technology: artificial intelligence.
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Scope of the Study
Market Segments covered in the Report:
By Component
By Deployment
By Application
Business Analytics & Reporting
Customer Behavioral Analytics
Fraud Detection
Virtual Assistant (Chatbots)
Quantitative & Asset Management
By Geography
North America
Rest of North America
Rest of Europe
Asia Pacific
South Korea
Rest of Asia Pacific
Saudi Arabia
South Africa
Rest of LAMEA
Companies Profiled
IBM Corporation
Oracle Corporation
Microsoft Corporation
Google LLC
Intel Corporation
Salesforce.com, Inc.
Amazon Web Services, Inc.
Amelia US LLC
Inbenta Technologies, Inc.
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