세계 핀테크(Fintech)용 AI 시장 : 시장 점유율 분석, 업계 동향과 통계, 성장 예측(2024-2029년)

The AI in Fintech Market size is estimated at USD 44.08 billion in 2024, and is expected to reach USD 50.87 billion by 2029, growing at a CAGR of 2.91% during the forecast period (2024-2029).

The COVID-19 pandemic outbreak has been accelerating the change in the way how people interact with financial services. Payment- and wealth-focused fintech companies have focused on bolstering their existing infrastructure by investing in new resources or expanding capacity to withstand the stress to their systems from higher transaction volumes. Though it seemed challenging for fintech companies, such actions have provided a significant need for AI solutions as these companies depend on transaction volumes for revenue. Such factors are expected to spearhead the demand for AI solutions in the fintech market.

Key Highlights

• Financial firms have been the early adopters of the mainframe computer and relational database. They eagerly waited for the next level of computational power. Artificial Intelligence (AI) improves results by applying methods derived from the aspects of human intelligence at a broader scale. The computational arms race for past years has revolutionized fintech companies. Technologies, such as machine learning, AI, neural networks, Big Data Analytics, evolutionary algorithms, and much more, have allowed computers to crunch huge, varied, diverse, and deep datasets than ever before.
• Moreover, AI and machine learning have benefited banks and fintech as they can process vast amounts of information about customers. This data and information are then compared to obtain results about timely services/products that customers want, which has aided, essentially, in developing customer relations.
• Additionally, machine learning is being adopted at unprecedented rates, specifically to create propensity models. Banks and insurance companies are introducing machine learning-based solutions for web and mobile applications. This has further enhanced the real-time target marketing by predicting the product propensity of the customers based on behavioral data in real-time.
• Several market incumbents are establishing a niche by explicitly offering solutions, like AI Chatbots for banking. For instance, in June 2021, Talisma and Active.Ai has partnered to enable improved customer experience in BFSI using conversation AI enabled Chatbot.
• Moreover, several credit card companies implement predictive analytics into their existing fraud detection workflows to reduce false positives. The studied market further gains traction with several players offering AI-based Anti-money Laundering (AML) and Fraud detection solutions for credit card companies and other financial institutions.
• For instance, in June 2022, Lucinity, a developer of AI-driven anti-money laundering (AML) software has partnered with fraud management company SEON to include real time fraud prevention capabilities in AML compliance software. SEON's fraud prevention solution will be available through Lucinity's platform, providing customers with compliance risk services from transaction monitoring to real-time fraud detection and prevention.
• Further, AI-ready infrastructure should be capable of efficient data management, have enough processing power, be agile, flexible, and scalable, and have the capacity to accommodate different volumes of data. Therefore, it would be more challenging for fintech small businesses to assemble the necessary hardware and software elements to support AI. Moreover, as the democratization of AI and deep learning applications expands, not only for tech giants but is now viable for small and medium-sized businesses. The demand for AI professionals to do the work has ballooned as well, and the scarcity of trained resources is the major challenge for AI in fintech.

AI in Fintech Market Trends

Fraud Detection is Expected to Witness Significant Growth

• Artificial intelligence can assist in identifying rapid and effective ways to detect financial fraud and malpractice. They allow machines to process enormous datasets accurately, which people sometimes struggle with. Using artificial intelligence for fraud detection has various advantages. The ability to compute quickly is a well-known benefit of AI and machine learning. It creates a grasp of a user's app usage habits, such as transaction methods, payments, and so on, allowing it to spot anomalies in real-time. It reduces false positives and allows specialists to focus on more complex issues because it is more efficient than manual techniques.
• According to a new poll conducted by Certified Fraud Examiners (ACFE) and analytics pioneer SAS, the use of Artificial Intelligence (AI) and Machine Learning (ML) for fraud detection increased internationally last year. According to the poll, 13% of organizations employ artificial intelligence (AI) and machine learning to detect and deter fraud, with another 25% planning to do so in the next year or two, representing roughly 200% growth. According to the poll, fraud examiners identified this and other anti-fraud tech developments in a cross-industry that are extensively spreading.
• Further, the Reserve Bank of India (RBI) reported around 9,103 bank fraud incidents across India in fiscal year 2022. This increased over the previous year, reversing the last decade's trend. The total value of bank scams fell from INR 1.38 trillion to INR 604 billion. Such high rise in the bank fraud cases would allow the AI market players to develop new solutions or tools to cater wide range of needs of the customer.
• The players in the market are collobarting to provide better service to its customer. For instance, in february 2023, Mastercard partnered with Network International, the Middle East and Africa's premier provider of digital commerce, to address fraud, declines, and chargebacks to minimise costs and risk for acquirers. Through the collaboration, Network will roll out Mastercard's Brighterion Artificial Intelligence (AI) technology across the region, providing acquirers and businesses with transaction fraud screening and merchant monitoring.
• Further, in March 2022, Shift Technology, a provider of AI-driven decision automation and optimisation solutions for the global insurance industry, and Duck Creek Technologies, a global provider of technology solutions to the P&C insurance industry, have announced a solution partnership to bring AI-enabled fraud detection capabilities to market in 2022. Once fully integrated, Duck Creek Claims users will receive real-time fraud alerts directly into their claims management software system.

North America Accounts For the Largest Market Share

• North America is expected to dominate the AI in Fintech market due to prominent AI software and systems suppliers, combined investment by financial institutions into AI projects, and the adoption of most AI in Fintech solutions. The region is expected to experience significant growth in this area in the coming years. Additionally, North America serves as the business hub for many AI Fintech firms, with companies like Sidetrade choosing to locate their North American operations in Calgary.
• Government initiatives and investments towards AI. would drive the market for instance. In fiscal year 2022, the U.S. government spent USD 3.3 billion on artificial intelligence (A.I.) contracts, according to data from a recent Stanford University study. Spending by federal government agencies on technology climbed by over USD 600 million annually, from USD 2.7 billion in 2021, with the decision science, computer vision, and autonomous segments receiving the majority of investment. Since 2017, when the U.S. government spent USD 1.3 billion on artificial technology, total spending on A.I. contracts has climbed by over 2.5 times.
• The players in the market are collobarting to provide better service to the customer in the region. For instance, in august 2022, Zest AI, the recipient of NACUSO's CUSO of the Year Award and a player in improving credit access through better scoring announced a partnership with Equifax, Inc., a worldwide data, analytics, and technology firm. The collaboration will allow credit unions that use Zest AI's underwriting technology to analyze more of the data sourced by Equifax to accept more applications with better speed, particularly those who have traditionally been underbanked. This is Zest AI's first big distribution relationship with a National Consumer Reporting Agency.
• Some companies' solutions help businesses grow retail banking with next-best-action software, detect and combat financial fraud, and improve client relationships with multichannel customer experience solutions. For insatnce, in April 2022, Versapay, a player in Collaborative Accounts Receivable, said today that it has finalised its acquisition of DadeSystems, a fintech startup based in the United States. Versapay's array of accounts receivable (AR) automation solutions has been expanded, as have its AI and machine learning capabilities, as a result of the acquisition. It also broadens Versapay's enterprise and mid-market footprint while adding critical skills to its growing staff.
• Banks in the region have started using blockchain technology to record data and combat fraud. Blockchain records the details of each transaction, making it easier to detect hacker attempts This technology permits worldwide payments and allows for speedy transactions with low commissions. The Distributed Ledger Technology (DLT) of Blockchain assists in the recording and sharing data across different stores and a distributed network. Furthermore, cryptographic and algorithmic methods synchronize data across the financial network. This is a significant step since transaction data can be stored in different locations. It paves the way for blockchain interoperability and cross-industry data exchange.

AI in Fintech Industry Overview

AI in the Fintech market is moving towards fragmented due to many global players. Various acquisitions and collaborations of large companies are expected to occur shortly, focusing on innovation. Some major players in the market include IBM Corporation, Intel Corporation, Narrative Science, and Microsoft Corporation.

In February 2023, Baiduri Bank in Brunei chose Singapore-based Software-as-a-Service (SaaS) fintech Finbots.ai to modernize its credit risk management with artificial intelligence (AI). According to Finbots.ai, its AI credit modeling solution, creditX, will allow Baiduri Bank to design and deploy high-quality credit scorecards in a fraction of the time and cost. This will minimize credit risk, increase efficiency and agility for retail and small and medium-sized organizations (SMEs), as well as expedite the bank's financial inclusion campaign for the underserved credit market.

In February 2023, Scotiabank introduced a new tool, Scotia Smart Investor, to give customers greater asset control. The Canadian lender introduced the new device via assistance+, combining AI-powered recommendations with real-time personalized assistance. Scotia Smart Investor was created by Scotia Securities, Scotiabank's linked mutual fund dealer. The tool, which includes an AI-powered advice engine, will assist users in designing, planning, monitoring, and updating financial goals.

Additional Benefits:

• The market estimate (ME) sheet in Excel format
• 3 months of analyst support

TABLE OF CONTENTS

1 INTRODUCTION

• 1.1 Study Assumptions and Market Definition
• 1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET INSIGHTS

• 4.1 Market Overview
• 4.2 Industry Attractiveness - Porter's Five Forces Analysis
  • 4.2.1 Bargaining Power of Suppliers
  • 4.2.2 Bargaining Power of Buyers
  • 4.2.3 Threat of New Entrants
  • 4.2.4 Threat of Substitutes
  • 4.2.5 Intensity of Competitive Rivalry
• 4.3 Emerging Uses of AI in Financial Technology
• 4.4 Technology Snapshot
• 4.5 Impact of COVID-19 on the market

5 MARKET DYNAMICS

• 5.1 Market Drivers
  • 5.1.1 Increasing Demand For Process Automation Among Financial Organizations
  • 5.1.2 Increasing Availability of Data Sources
• 5.2 Market Restraints
  • 5.2.1 Need for Skilled Workforce

6 MARKET SEGMENTATION

• 6.1 By Type
  • 6.1.1 Solutions
  • 6.1.2 Services
• 6.2 By Deployment
  • 6.2.1 Cloud
  • 6.2.2 On-premise
• 6.3 By Application
  • 6.3.1 Chatbots
  • 6.3.2 Credit Scoring
  • 6.3.3 Quantitative & Asset Management
  • 6.3.4 Fraud Detection
  • 6.3.5 Other Applications
• 6.4 By Geography
  • 6.4.1 North America
  • 6.4.2 Europe
  • 6.4.3 Asia Pacific
  • 6.4.4 Rest of the World

7 COMPETITIVE LANDSCAPE

• 7.1 Company Profiles
  • 7.1.1 IBM Corporation
  • 7.1.2 Intel Corporation
  • 7.1.3 ComplyAdvantage.com
  • 7.1.4 Narrative Science
  • 7.1.5 Amazon Web Services Inc.
  • 7.1.6 IPsoft Inc.
  • 7.1.7 Next IT Corporation
  • 7.1.8 Microsoft Corporation
  • 7.1.9 Onfido
  • 7.1.10 Ripple Labs Inc.
  • 7.1.11 Active.Ai
  • 7.1.12 TIBCO Software (Alpine Data Labs)
  • 7.1.13 Trifacta Software Inc.
  • 7.1.14 Data Minr Inc.
  • 7.1.15 Zeitgold
  • 7.1.16 Sift Science Inc.
  • 7.1.17 Pefin Holdings LLC
  • 7.1.18 Betterment Holdings
  • 7.1.19 WealthFront Inc.

8 INVESTMENT ANALYSIS

9 FUTURE OF THE MARKET