Artificial intelligence (AI) in the banking market is estimated to grow at a CAGR of 55.53% to attain US$54.635 billion in 2029, increasing from US$17.383 billion in 2024. Artificial intel...
Artificial intelligence (AI) in the banking market is estimated to grow at a CAGR of 55.53% to attain US$54.635 billion in 2029, increasing from US$17.383 billion in 2024.
Artificial intelligence (AI) techniques play a major role in the daily lives of people which has prompted the banks to adopt the use of such technology to satisfy the needs of the users. This includes a rise in the need for mobile and internet banking services that are less complex owing to the availability of diverse software for different purposes. Due to the integration of different coherent AI technologies, banks can integrate digital advantages which will also make them suitable competitors to the FinTech firms. It is envisaged that AI will aid the extensive use of data analytics to enable banks to address issues of unauthorized transactions and meet their KYC regulatory compliance and controls.
The most recent trend being witnessed in the banking sector is the introduction of AI which will majorly fuel the market expansion. This is due to an increase in the need for faster services and ease of use by customers. AI in banking systems is aimed at improving the level of customer satisfaction, improving business processes as well as solving problems related to banking systems. Such technology helps in storing, and analyzing data in huge volumes and helping banks understand useful business information in less time. Moreover, the growth in compliance and a decrease in operational risk will enhance the embrace of AI in the banking sector.
The market is witnessing diverse collaborations and innovative technological advancements, for instance, in June 2024, NatWest launched Cora+, an upgraded version of its virtual Cora a conversational agent developed in partnership with IBM and oriented towards generative AI. The new adaptation was presented during London Tech Week and made the UK bank one of the first to integrate generative AI within a digital assistant. Cora satisfies the needs of the customers on a 24-hour basis and answers any questions relating to banking using common language processing and machine learning skills.
Based on the solution, the AI in banking market is divided into hardware, software, and services. Software is most likely to fuel the growth of AI in the banking market majorly because software is at the core of data processing, machine learning, and forecasting. Software is more flexible and amenable to changes than hardware thus allowing banks to meet their requirements as well as provide interoperability with the existing systems.
Based on the application, the AI in banking market is classified into customer service, robot advice, general purpose/predictive analysis, cyber security, and direct learning. It is expected that the deployment of general purpose/predictive analysis for activities such as intellectual fraud detection and customer risk profiling will enable AI in bank market to grow. Predictive analysis is dynamic and can encourage the efficiency and expansion of several banking operations. It aids superior judgment by comprehending extensive amounts of information and is capable of detecting trends beneficial to lending and investing for banks.
Based on geography, the AI in banking market is extending majorly in the North America region due to various variables. The North American region is expected to grow due to the increased adoption of fast-changing digital technologies like data analytics, AI, blockchain, the Internet of Things, cloud computing, and internet services in the region. Thus, this region will lead when it comes to the adoption of AI in the banking sector. In addition, the local market is anticipated to grow owing to the rising digitization of the banking industry within this region with the rise in regional players developing improved AI for the banking sector.
As a part of the report, the major players operating in the AI in banking market that have been covered are Zest AI, IBM, Data Robot Inc., Accenture, Personetics Technologies, Kensho Technologies, LLC, Wipro, Intel, SAP, Temenos, SAS, Abe AI and OSP Labs.
View a sample of the report or purchase the complete study at https://www.knowledge-sourcing.com/report/artificial-intelligence-ai-in-banking-market
This analytics report segments the AI in banking market on the following basis:
- 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
- China
- Japan
- South Korea
- India
- Thailand
- Taiwan
- Indonesia
- Others
- North America
- Artificial Intelligence As A Service (AIaaS) Market Report
- AI In Retail Market Size
- AI In E-commerce Market Report
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