
AI In Banking Market Set For Rapid Expansion, Forecasted To Reach USD 64.03 Billion By 2030 With A Remarkable 32.6% CAGR
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Artificial intelligence in banks is helping the financial industry to streamline and optimize processes ranging from credit decisions to quantitative trading and financial risk management. In addition, it provides solutions to process automation to replace routine manual work in most cases. Furthermore, the key factor that drives the market includes improvement in data collection technology among the banks and financial institutions positively impacts the AI in banking market growth. In addition, increase in investment by banks in AI and rise in customer preferences for personalized financial services boost the growth of the market across the globe. However, factors such as higher deployment cost of AI and lack of skilled labor are limiting the growth of the market. On the contrary, surge in adoption of modern applications in banks is expected to offer remunerative opportunities for the expansion of the market during the forecast period.
Drivers, restraints, and opportunities-
Rise in investment by banking companies in AI and machine learning, surge in preference for personalized financial services, and increase in collaboration between financial institutes and AI & machine learning solution companies drive the growth of the global AI in banking market. On the other hand, higher deployment cost of AI and machine learning and lack of skilled labor restrain the growth to some extent. However, upsurge in government initiatives and growing investments to leverage the AI technology are expected to create lucrative opportunities in the industry.
COVID-19 scenario-
The outbreak of COVID-19 is anticipated to have a positive impact on growth of AI in banking market. This is attributed to rise in demand for anti-money laundering (AML) and fraud detection solutions during the pandemic situation.
At the same time, with the significant rise in digitization among both the financial institutes and end users, the demand for AI technology has been increased so as to reduce the load on the banking servers, thereby easing up transaction delays throughout this unprecedented time.
The Customer Relationship Management (CRM) segment to retain the lion's share-
On the basis of solution type, the Customer Relationship Management (CRM) segment held the major share in 2020, garnering nearly one-fifth of the global AI in banking market. The same segment is also projected to cite the fastest CAGR of 34.0% throughout the forecast period. Growing need for CRM solution to gain deeper insights into customer's habits and personal preferences drives the segment growth.
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The machine learning & deep learning segment to dominate by 2030-
On the basis of technology, the machine learning & deep learning segment contributed to the lion's share in 2020, holding around one-third of the global AI in banking market share. However, the same segment is also expected to cite the fastest CAGR of 33.5% from 2021 to 2030. This is attributed to increase in adoption of machine learning among banking institutes to support artificial intelligence software developed by various companies to improve their bias decisions while doing critical jobs.
North America held the major share in 2020-
By region, the market across North America dominated in 2020, garnering more than two-fifths of the global AI in banking market, owing to increase in demand for advanced analytics in this province. Simultaneously, the Asia-Pacific region is expected to cite the fastest CAGR of 34.3% throughout the forecast period. This is due to increase in investment by banks across China, Japan, and India for analyzing loan sanction patterns.
Key players in the industry-
BigML, Inc.
Cisco Systems, Inc.
Fair Isaac Corporation
SAP SE
Hewlett Packard Enterprise Development LP
SAS Institute Inc.
International Business Machines Corporation
Amazon Web Services Inc.
Microsoft Corporation
RapidMiner, Inc.
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Key Market Segments
Component
Solution
Chatbot
Customer Behavior Analytics
Customer Relationship Management (CRM)
Data Analytics and Visualization
Fraud Detection
Others
Service
By Enterprise Size
Large Enterprise
SMEs
By Application
Risk Management Compliance & Security
Customer Service
Back Office/Operations
Financial Advisory
Others
By Technology
Machine Learning & Deep Learning
Natural Language Processing (NLP)
Computer Vision
Others
By Region
North America
U.S.
Canada
Europe
UK
Germany
France
Italy
Spain
Netherlands
Rest of Europe
Asia-Pacific
China
Japan
India
Australia
South Korea
Rest of Asia-Pacific
LAMEA
Latin America
Middle East
Africa
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