Improved productivity of banks and faster banking operations using machine learning have boosted the growth of the global machine learning in banking market.
PORTLAND, Ore., Sept. 26, 2022 /PRNewswire/ -- Allied Market Research recently published a report, titled, "Machine Learning in Banking Market By Component (Solution and Service), Enterprise Size (Large Enterprises, Small and Medium-Sized Enterprises [SMEs]), Application (Credit Scoring, Risk Management Compliance and Security, Payments and Transactions, Customer Service, and Others): Global Opportunity Analysis and Industry Forecast, 2021-2031". As per the report, the global machine learning in banking industry accounted for $1.33 billion in 2021, and is expected to reach $21.27 billion by 2031, growing at a CAGR of 32.2% from 2021 to 2030.
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Major determinants of the market growth
Improved productivity of banks and faster banking operations using machine learning have boosted the growth of the global machine learning in banking market. However, higher cost of implementation of machine learning technology and risk of unemployment with adoption of machine learning technology hinder the market growth. On the contrary, technological developments in machine learning would open new opportunities in the future.
Report Coverage and Details:
Market Size in 2021
Market Size in 2031
No. of Pages in Report
Component, Enterprise Size, Application, and Region
Improved productivity of banks owing to adoption of ML
Effective risk assessment through machine learning in financial industry and efficient customer service
Technological advancements in ML technology
High costs of implementation of ML technology
Risk of unemployment owing to adoption of ML
The COVID-19 pandemic had a positive impact on the market as most of the banks adopted technologies such as machine learning. These technologies helped the financial institutes by making credit repair and credit monitoring more accurate and faster.
Machine learning have helped banking sector leaders to deliver better results for customers and reduce credit frauds from process automation to biometric identification.
During the pandemic, several banks experienced surge in demand as working practices and customer banking habits changed drastically.
The solution segment dominated the market growth
By component, the solution segment held the largest share in 2021, accounting for nearly three-fourths of the global machine learning in banking market. Moreover, the segment is expected to continue its dominance in terms revenue throughout the forecast period. However, the service segment is expected to manifest the highest CAGR of 36.5% during the forecast period, due to Surge in demand for cloud-based machine learning services. Moreover, rise in demand for software-as-a-service (SaaS) due to its numerous benefits such as scalability and one-time customer acquisition cost is expected to provide lucrative opportunities for the growth of the market.
The small and medium-sized enterprises (SMEs) segment to manifest the highest CAGR through 2031
By enterprise size, the small and medium-sized enterprises (SMEs) segment is projected to register the highest CAGR of 35.6% during the forecast period, due to their less risk-taking capabilities. In addition, the segment is expected to hold the largest share by 2031. However, the large enterprises segment held the largest share in 2021, contributing to more than one-fourth of the global machine learning in banking market.
The credit scoring segment dominated the market
By application, the credit scoring segment held the largest share in 2021, accounting for more than one-fourth of the global machine learning in banking market. Furthermore, the segment is expected to maintain its dominance the largest share during the forecast period. However, the payments and transactions segment is anticipated to register the highest CAGR of 35.4% during the forecast period. Payment providers are well familiar with machine learning, as it pertains to credit card transaction monitoring, where learning algorithms play important roles in near real-time authorization of transactions. These are the major growth factors for the payments and transactions in the machine learning in banking market.
North America held the largest share
By region, the global machine learning in banking market across North America held the largest share in 2021, accounting for nearly two-fifths of the market. However, market across Asia-Pacific is expected to showcase the highest CAGR of 35.5% during the forecast period, owing to surge in need to monitor growing number of financial violations and offences. Moreover, the region is projected to hold the largest share throughout the forecast period.
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Major Market Players
Amazon Web Services, Inc.
Cisco Systems, Inc.
The report analyzes these key players of the global machine learning in banking market. These players have adopted various strategies such as expansion, new product launches, partnerships, and others to increase their market penetration and strengthen their position in the industry. The report is helpful in determining the business performance, operating segments, product portfolio, and developments by every market player.
Key Benefits For Stakeholders:
This report provides a quantitative analysis of market segments, current trends, estimations, and dynamics of the machine learning in banking market share from 2021 to 2031 to identify the prevailing market opportunities.
In-depth analysis of the machine learning in banking market forecast segmentation assists to determine the prevailing machine learning in banking market opportunity.
Market player positioning facilitates benchmarking and provides a clear understanding of the present position of the market players.
The report includes the analysis of the regional as well as global machine learning in banking market trends, key players, market segments, application areas, and market growth strategies.
Machine Learning in Banking Market Key Segments:
By Enterprise Size:
Small and Medium-Sized Enterprises (SMEs)
Risk Management Compliance and Security
Payments and Transactions
North America (U.S., Canada, and Mexico)
Europe (Germany, Italy, France, Spain, U.K., Russia, and Rest of Europe)
Asia-Pacific (China, India, Japan, South Korea, and Rest of Asia-Pacific)
LAMEA (Latin America, Middle East and Africa)
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