Global Machine Learning in Banking Market Size study, By Component (Solution, Service), by Enterprise Size (Large Enterprises, Small and Medium-sized Enterprises (SMEs)), by Application (Credit Scoring, Risk Management Compliance and Security, Payments an

Global Machine Learning in Banking Market Size study, By Component (Solution, Service), by Enterprise Size (Large Enterprises, Small and Medium-sized Enterprises (SMEs)), by Application (Credit Scoring, Risk Management Compliance and Security, Payments and Transactions, Customer Service), and Regional Forecasts 2022-2028

Global Machine Learning in Banking Market is valued approximately USD XX million in 2021 and is anticipated to grow with a healthy growth rate of more than XX % over the forecast period 2022-2028.

In Banking sector Machine Learning solutions are utilized for automating different applications such as fraud prevention, anomaly detection, credit scoring, anti-money laundering and kyc process, payment processing, onboarding & document processing, and process automation among others. The rising expansion of banking sector worldwide and increasing adoption of AI and ML based services as well as recent strategic partnership from leading market players are factors that are accelerating the global market demand. For instance, according to India Brand Equity Forum (IBEF) – during FY 2020, total deposits in banking were estimated at USD 1936.29 billion, and the deposits are projected to grow to USD 2101.93 billion by end of 2022. Furthermore, leading market players are working towards strategic initiatives to leverage the growing adoption of Machine learning solutions in banking sector. For instance, in February 2022, Dubai, United Arab Emirates based Mashreq Bank announced a new partnership with Israel based ThetaRay, a fintech software and big data analytics solution provider. Through this collaboration the bank would utilize ThetaRay’s AI-driven solution. Moreover, in July 2022, Bentonville, Arkansas, United States based Arvest Bank entered in a five-year partnership with Google Cloud. Under this partnership the bank would leverage Google Cloud’s artificial intelligence (AI) and machine learning (ML) tools to enhance customer experience and streamline its banking services. Also, growing digitization in BFSI sector coupled with increasing emergence of neo banks are anticipated to act as a catalyzing factor for the market demand during the forecast period. However, a high deployment cost associated with AI and ML solutions impedes the growth of the market over the forecast period of 2022-2028.

The key regions considered for the global Machine Learning in Banking Market study include Asia Pacific, North America, Europe, Latin America, and the Rest of the World. North America is the leading region across the world in terms of market share owing to the growing number of governance and regulatory compliances and presence of leading financial institutions in the region. Whereas, Asia Pacific is anticipated to exhibit a significant growth rate over the forecast period 2022-2028. Factors such as the thriving growth of BFSI industry and increasing penetration of leading market players in the region, would create lucrative growth prospects for the global Machine Learning in Banking Market across the Asia Pacific region.

Major market players included in this report are:
Affirm Inc.
Amazon Web Services, Inc.
Big ML, Inc.
Cisco Systems, Inc.
FICO
Google LLC
Mindtree
Microsoft
SAP SE
SPD-Group

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming eight years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within each of the regions and countries involved in the study. Furthermore, the report also caters the detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, the report shall also incorporate available opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:
By Component
Solution
Service
By Enterprise Size
Large Enterprises
Small and Medium-sized Enterprises (SMEs)
By Application
Credit Scoring
Risk Management Compliance and Security
Payments and Transactions
Customer Service
By Region:
North America
U.S.
Canada
Europe
UK
Germany
France
Spain
Italy
ROE

Asia Pacific
China
India
Japan
Australia
South Korea
RoAPAC
Latin America
Brazil
Mexico
Rest of the World

Furthermore, years considered for the study are as follows:

Historical year – 2018, 2019, 2020
Base year – 2021
Forecast period – 2022 to 2028

Target Audience of the Global Machine Learning in Banking Market in Market Study:

Key Consulting Companies & Advisors
Large, medium-sized, and small enterprises
Venture capitalists
Value-Added Resellers (VARs)
Third-party knowledge providers
Investment bankers
Investors

Companies Mentioned

Affirm Inc.
Amazon Web Services, Inc.
Big ML, Inc.
Cisco Systems, Inc.
FICO
Google LLC
Mindtree
Microsoft
SAP SE
SPD-Group

Please note:The single user license is non-downloadable and non-printable. Global Site license allows these actions.