Artificial Intelligence (AI) In Banking Market Size, Share, Opportunities, And Trends By Solution (Hardware, Software, Services), By Application (Customer Service, Robot Advice, General Purpose/Predictive Analysis, Cyber Security, Direct Learning), And By Geography - Forecasts From 2025 To 2030

Artificial intelligence (AI) in the banking market is estimated to grow at a CAGR of 17.96%, attaining US$75.357 billion by 2030, from US$32.988 billion in 2025.

AI integration in banking has transformed the sector. This transformation is leading to a more customer-centric approach and enhanced technological relevance. These systems reduce costs through heightened productivity. The BIS Annual Economic Report, emphasizes that Central banks should embrace artificial intelligence, anticipating its impact on the economy. The widespread adoption will create the importance of data as a cornerstone of the AI revolution and the need for central bank cooperation.

Moreover, intelligent algorithms rapidly detect fraudulent activities, significantly improving security measures within seconds. For example, in August 2024, Zest AI announced its new fraud detection solution, Zest Protect. Zest Protect can identify fraudulent activity during the loan decision process, helping credit unions, banks, and other lenders navigate the rising application frauds. This is a crucial shift in banking services, prioritizing efficiency and security.

Further, the growing number of internet users has created a demand for innovative technology and solutions. The number of internet users reached 5.4 billion in 2023 from 5.1 billion in 2023, according to the ITU (International Telecommunication Union) data. This led organizations like Bank of America to use innovative technology to meet the needs of its clients and employees. The organization has had a 94% increase in artificial intelligence and machine learning (ML) granted patents and pending patent applications since 2022. The company has nearly 1,100 AI and ML patents and pending applications in its portfolio, with more than half having already been granted.

What are the artificial intelligence (AI) in banking growth drivers?

• Increase in the number of digital payments

Nowadays, every bank has a mobile app that works effectively and manages the majority of customer interactions. Digitalization has improved banks’ ability to meet customers’ needs. However, as the number of digital payments and interactions increased spontaneously, this became a challenge for the banks to achieve their goals. Yet the goal is also to increase the proportion of digital interactions.

In India, the number of digital payment transactions has increased at a CAGR of 44% from FY 2017-18 to FY 2023-24. The total digital payment transactions volume increased from 8,839 crore in FY 2021-22 to 13,462 crore in FY 2022-23.

 The growing number of banks and their related transactions would seek a greater return on their investment in digital by using their vast stores of customer data and advanced analytics. These can be achieved through AI capabilities, moving beyond basic demographic segmentation and treating customers as individuals. This will also allow these banks to gain a better understanding of customer’s needs and demands.

What are the key geographical trends shaping artificial intelligence (AI) in the banking market?

The Asia Pacific artificial intelligence (AI) in banking market size is expected to grow significantly during the forecast period. The growth of AI in China's banking sector is a phenomenal development in terms of technology and strategy for the industry. In recent years, Chinese banks have been increasing their role to adopt AI technologies aimed at enhancing efficiency in operations, better customer experience, and new income sources. A survey was conducted with 1,6000 decision-makers in industries worldwide by U.S. AI and analytics software company SAS and Coleman Parkes Research, which showed that China is leading the world in terms of their adoption of generative AI. 83% of Chinese respondents said that they use generative AI, which was higher than the global average survey of 54% consisting of 16 other countries and regions involved in the survey, including the United States, where only 65% have adopted AI.

One of the main reasons Chinese banks are embracing AI is the need to diversify income sources. Experts estimate that AI will increase fee-based income for banks from about 30% to 40% of total revenues, allowing them to reduce their dependence on net interest income, which is highly sensitive to central bank policies. The integration of AI means that banks can automate most of their processes, from customer service to fraud detection, saving on operational costs and becoming more productive. For example, major banks in China now make an average of 400 million decisions daily by applying machine learning models to position themselves miles ahead of their competitors elsewhere in Asia, such as in Singapore and India.

Artificial Intelligence (AI) in Banking Market Products Offered by Key Companies:

• International Business Machines Corp. (IBM) offers consulting services, global hybrid cloud, and artificial intelligence solutions. The company provides infrastructure, hosting, and consulting services in addition to developing system hardware and software. Analytics, AI, automation, blockchain, cloud computing, IT infrastructure, IT management, cybersecurity, and software development are some of IBM's core competencies. In addition, the organization provides technology consulting, cloud, networking, security, application, and business resilience services, as well as technology support. The company’s IBM WatsonX Assistant is an AI-based chatbot designed for Banking. 
• Amazon Web Services or AWS is a subsidiary of Amazon Inc., a US-based technological company. The company offers a wide range of products and solutions for multiple industries, which includes marketing & advertising, aerospace & satellite, automotive, education, financial services, games, and industrial among many others. The products of the company include contact centers, AI, analytics, games, IoT, media services, and quantum technology. In the global AI for the banking market, the company offers generative AI solutions, for financial services, which include multiple features like scalability, enhanced security, and lower-cost infrastructure.

Key developments in artificial intelligence (AI) in the banking market:

• In May 2024, IBM collaborated with Mizuho Financial Group, Inc. to develop a proof of concept (PoC) using Watsonx. The new collaboration demonstrates 98% accuracy in monitoring and responding to error messages during a three-month trial.
• In May 2024, Temenos AG, a global leader in enterprise solutions, announced the launch of its responsible generative AI solution, which is aimed at core banking. The latest solution offers enhanced operational efficiency, cutting-edge technology, and product management. The solution also offers the capability to the institutions to deploy the AI solution faster and in a safer process. The company further stated that the generative AI solution can be applied to customers, and enables the banks to develop and enable products in real-time.

Artificial Intelligence (AI) In Banking Market Scope:

Report Metric	Details
AI in Banking Market Size in 2025	US$32.988 billion
AI in Banking Market Size in 2030	US$75.357 billion
Growth Rate	CAGR of 17.96%
Study Period	2020 to 2030
Historical Data	2020 to 2023
Base Year	2024
Forecast Period	2025 – 2030
Forecast Unit (Value)	USD Billion
Segmentation	Solution Application Geography
Geographical Segmentation	North America, South America, Europe, Middle East and Africa, Asia Pacific
List of Major Companies in AI in Banking Market	Zest AI IBM Data Robot Inc. Accenture Personetics Technologies
Customization Scope	Free report customization with purchase

The Artificial Intelligence (AI) in Banking Market is analyzed into the following segments:

• By Solution
  • Hardware
  • Software
  • Services
• By Application
  • Customer Service
  • Robot Advice
  • General Purpose/Predictive Analysis
  • Cyber Security
  • Direct Learning
• By Geography
  • North America
    • USA
    • Canada
    • Mexico
  • South America
    • Brazil
    • Argentina
    • Others
  • Europe
    • Germany
    • France
    • United Kingdom
    • Italy
    • Spain
    • Others
  • Middle East and Africa
    • Saudi Arabia
    • UAE
    • Israel
    • Others
  • Asia Pacific Region
    • China
    • Japan
    • India
    • Australia
    • South Korea
    • Others

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1. INTRODUCTION

1.1. Market Overview

1.2. Market Definition

1.3. Scope of the Study

1.4. Market Segmentation

1.5. Currency

1.6. Assumptions

1.7. Base and Forecast Years Timeline

1.8. Key benefits for the stakeholders

2. RESEARCH METHODOLOGY  

2.1. Research Design

2.2. Research Process

3. EXECUTIVE SUMMARY

3.1. Key Findings

4. MARKET DYNAMICS

4.1. Market Drivers

4.2. Market Restraints

4.3. Porter’s Five Forces Analysis

4.3.1. Bargaining Power of Suppliers

4.3.2. Bargaining Power of Buyers

4.3.3. The Threat of New Entrants

4.3.4. Threat of Substitutes

4.3.5. Competitive Rivalry in the Industry

4.4. Industry Value Chain Analysis

4.5. Analyst View

5. ARTIFICIAL INTELLIGENCE (AI) IN THE BANKING MARKET BY SOLUTION

5.1. Introduction

5.2. Hardware

5.3. Software

5.4. Services

6. ARTIFICIAL INTELLIGENCE (AI) IN THE BANKING MARKET BY APPLICATION

6.1. Introduction

6.2. Customer Service

6.3. Robot Advice

6.4. General Purpose/Predictive Analysis

6.5. Cyber Security

6.6. Direct Learning

7. ARTIFICIAL INTELLIGENCE (AI) IN THE BANKING MARKET BY GEOGRAPHY

7.1. Introduction

7.2. North America

7.2.1. By Solution

7.2.2. By Application

7.2.3. By Country

7.2.3.1. United States

7.2.3.2. Canada

7.2.3.3. Mexico

7.3. South America

7.3.1. By Solution

7.3.2. By Application

7.3.3. By Country

7.3.3.1. Brazil

7.3.3.2. Argentina

7.3.3.3. Others

7.4. Europe

7.4.1. By Solution

7.4.2. By Application

7.4.3. By Country

7.4.3.1. Germany 

7.4.3.2. France

7.4.3.3. United Kingdom 

7.4.3.4. Italy

7.4.3.5. Spain

7.4.3.6. Others

7.5. Middle East and Africa

7.5.1. By Solution

7.5.2. By Application

7.5.3. By Country

7.5.3.1. Saudi Arabia

7.5.3.2. UAE

7.5.3.3. Israel

7.5.3.4. Others

7.6. Asia Pacific

7.6.1. By Solution

7.6.2. By Application

7.6.3. By Country

7.6.3.1. China

7.6.3.2. Japan

7.6.3.3. India

7.6.3.4. Australia

7.6.3.5. South Korea

7.6.3.6. Others

8. COMPETITIVE ENVIRONMENT AND ANALYSIS

8.1. Major Players and Strategy Analysis

8.2. Market Share Analysis

8.3. Mergers, Acquisitions, Agreements, and Collaborations

8.4. Competitive Dashboard

9. COMPANY PROFILES

9.1. Zest AI

9.2. IBM

9.3. Data Robot Inc.

9.4. Accenture

9.5. Personetics Technologies

9.6. Wipro

9.7. Intel Corporation

9.8. SAP

9.9. Temenos

9.10. SAS

9.11. Abe AI (Yodlee)

9.12. OSP Labs

9.13. Amazon Web Services, Inc

9.14. ACE Software Solutions Inc

9.15. Adesso SE

Zest AI

IBM

Data Robot Inc.

Accenture

Personetics Technologies

Wipro

Intel Corporation

SAP

Temenos

SAS

Abe AI (Yodlee)

OSP Labs

Amazon Web Services, Inc

ACE Software Solutions Inc

Adesso SE