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Global Banking Software Market to reach USD 49.6 billion by the end of 2030

Global Banking Software Market Size study & Forecast, by Deployment Mode (On-Premise, Cloud), by End User (Banks, Financial Institution), by Component (Solution, Service) and Regional Analysis, 2023-2030

Product Code: ICTEITS-57600018
Publish Date: 10-08-2023
Page: 200

Global Banking Software Market is valued at approximately USD 11.7 billion in 2022 and is anticipated to grow with a healthy growth rate of more than 19.8% over the forecast period 2023-2030. Banking software refers to a specialized set of computer programs and applications designed to meet the specific needs and requirements of financial institutions, including banks, credit unions, and other financial service providers. This software enables efficient and secure management of banking operations, such as core banking systems, transaction processing, customer relationship management, risk management, compliance, and digital banking solutions. By automating various processes, providing real-time data analysis, and facilitating seamless integration with external systems, banking software empowers financial institutions to streamline operations, enhance customer experiences, and effectively navigate the complexities of the modern banking landscape. The driving factors boosting the market growth are the increasing usage of digital banking and the rising adoption of cloud-based solutions.

The increasing usage of digital banking is driving the banking software market by creating a demand for robust and innovative software solutions to support online transactions, mobile banking, and customer self-service options. Banks are investing in advanced software to enhance their digital offerings, improve customer experience, and streamline internal operations. According to Statista, in 2022, India emerged as the global leader in digital banking users, surpassing all other countries. With an estimated user base of approximately 295.5 million, India exceeded the number of digital banking users in the United States by over 70 million, securing the top position. As per the same source, both India and the U.S. exhibited remarkably high numbers of digital banking users, creating a significant margin between them and other countries included in the rankings. Moreover, the integration of Artificial Intelligence (AI) and Machine Learning (ML) into banking software and digital transformation in the banking industry is expected to create lucrative opportunities in the market. However, the high implementation and maintenance costs of banking softwares along with data privacy and security concerns stifle market growth throughout the forecast period of 2023-2030.

The key regions considered for the Global Banking Software Market study includes Asia Pacific, North America, Europe, Latin America, and Middle East & Africa. North America dominated the market in 2022 owing to the dominance of the highly developed financial services industry, and the increasing use of banking software in small and medium businesses. Asia Pacific is expected to become the fastest growing during the forecast period, owing to the growing adoption of web- and mobile-based business solutions in the banking industry.

Major market player included in this report are:
Salesforce, Inc.
Tata Consultancy Services Limited
EdgeVerve Systems Limited
Microsoft Corporation
Oracle Corporation
Fidelity National Information Services Inc
International Business Machines Corporation
Jack Henry & Associates, Inc.
NCR Corporation

Recent Developments in the Market:
Ø In June 2023, Salesforce and Deloitte Digital joined forces to offer global businesses the tools and strategies required to implement reliable AI solutions for customer relationship management (CRM). The collaboration aims to provide accelerators and guidance for the successful deployment of AI in CRM systems. This will prove as an useful tool in banking sector to resolve customer issues.
Ø In June 2023, Oracle introduced the integration of generative AI-powered features into Oracle Fusion Cloud Human Capital Management (HCM). These capabilities, supported by Oracle Cloud Infrastructure (OCI) generative AI service, are seamlessly embedded into existing HR processes. Banks heavily rely on HR processes and systems to manage their workforce effectively. By integrating generative AI capabilities into HCM, Oracle aims to enhance the efficiency and automation of HR functions within the banking sector.

Global Banking Software Market Report Scope:
ü Historical Data – 2020 – 2021
ü Base Year for Estimation – 2022
ü Forecast period – 2023-2030
ü Report Coverage – Revenue forecast, Company Ranking, Competitive Landscape, Growth factors, and Trends
ü Segments Covered – Deployment Mode, End User, Component, Region
ü Regional Scope – North America; Europe; Asia Pacific; Latin America; Middle East & Africa
ü Customization Scope – Free report customization (equivalent up to 8 analyst’s working hours) with purchase. Addition or alteration to country, regional & segment scope*

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 years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within countries involved in the study.

The report also caters detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, it also incorporates potential 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 Deployment Mode:

By End User:
Financial Institutions

By Component:

By Region:

North America


Asia Pacific
South Korea

Latin America

Middle East & Africa
Saudi Arabia
South Africa
Rest of Middle East & Africa

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2020-2030 (USD Billion)
1.2.1. Banking Software Market, by Region, 2020-2030 (USD Billion)
1.2.2. Banking Software Market, by Deployment Mode, 2020-2030 (USD Billion)
1.2.3. Banking Software Market, by End User, 2020-2030 (USD Billion)
1.2.4. Banking Software Market, by Component, 2020-2030 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Banking Software Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Industry Evolution
2.2.2. Scope of the Study
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Banking Software Market Dynamics
3.1. Banking Software Market Impact Analysis (2020-2030)
3.1.1. Market Drivers Increasing usage of digital banking Rising adoption of cloud-based solutions
3.1.2. Market Challenges High implementation and maintenance costs Data privacy and security concerns
3.1.3. Market Opportunities Integration of Artificial Intelligence (AI) and Machine Learning (ML) into banking software Digital transformation in the banking industry
Chapter 4. Global Banking Software Market Industry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.2. Porter’s 5 Force Impact Analysis
4.3. PEST Analysis
4.3.1. Political
4.3.2. Economical
4.3.3. Social
4.3.4. Technological
4.3.5. Environmental
4.3.6. Legal
4.4. Top investment opportunity
4.5. Top winning strategies
4.6. COVID-19 Impact Analysis
4.7. Disruptive Trends
4.8. Industry Expert Perspective
4.9. Analyst Recommendation & Conclusion
Chapter 5. Global Banking Software Market, by Deployment Mode
5.1. Market Snapshot
5.2. Global Banking Software Market by Deployment Mode, Performance – Potential Analysis
5.3. Global Banking Software Market Estimates & Forecasts by Deployment Mode 2020-2030 (USD Billion)
5.4. Banking Software Market, Sub Segment Analysis
5.4.1. On-Premise
5.4.2. Cloud
Chapter 6. Global Banking Software Market, by End User
6.1. Market Snapshot
6.2. Global Banking Software Market by End User, Performance – Potential Analysis
6.3. Global Banking Software Market Estimates & Forecasts by End User 2020-2030 (USD Billion)
6.4. Banking Software Market, Sub Segment Analysis
6.4.1. Banks
6.4.2. Financial Institution
Chapter 7. Global Banking Software Market, by Component
7.1. Market Snapshot
7.2. Global Banking Software Market by Component, Performance – Potential Analysis
7.3. Global Banking Software Market Estimates & Forecasts by Component 2020-2030 (USD Billion)
7.4. Banking Software Market, Sub Segment Analysis
7.4.1. Solution
7.4.2. Service
Chapter 8. Global Banking Software Market, Regional Analysis
8.1. Top Leading Countries
8.2. Top Emerging Countries
8.3. Banking Software Market, Regional Market Snapshot
8.4. North America Banking Software Market
8.4.1. U.S. Banking Software Market Deployment Mode breakdown estimates & forecasts, 2020-2030 End User breakdown estimates & forecasts, 2020-2030 Component breakdown estimates & forecasts, 2020-2030
8.4.2. Canada Banking Software Market
8.5. Europe Banking Software Market Snapshot
8.5.1. U.K. Banking Software Market
8.5.2. Germany Banking Software Market
8.5.3. France Banking Software Market
8.5.4. Spain Banking Software Market
8.5.5. Italy Banking Software Market
8.5.6. Rest of Europe Banking Software Market
8.6. Asia-Pacific Banking Software Market Snapshot
8.6.1. China Banking Software Market
8.6.2. India Banking Software Market
8.6.3. Japan Banking Software Market
8.6.4. Australia Banking Software Market
8.6.5. South Korea Banking Software Market
8.6.6. Rest of Asia Pacific Banking Software Market
8.7. Latin America Banking Software Market Snapshot
8.7.1. Brazil Banking Software Market
8.7.2. Mexico Banking Software Market
8.8. Middle East & Africa Banking Software Market
8.8.1. Saudi Arabia Banking Software Market
8.8.2. South Africa Banking Software Market
8.8.3. Rest of Middle East & Africa Banking Software Market

Chapter 9. Competitive Intelligence
9.1. Key Company SWOT Analysis
9.1.1. Company 1
9.1.2. Company 2
9.1.3. Company 3
9.2. Top Market Strategies
9.3. Company Profiles
9.3.1. Salesforce, Inc. Key Information Overview Financial (Subject to Data Availability) Product Summary Recent Developments
9.3.2. Tata Consultancy Services Limited
9.3.3. EdgeVerve Systems Limited
9.3.4. Microsoft Corporation
9.3.5. Oracle Corporation
9.3.6. Fidelity National Information Services Inc
9.3.7. International Business Machines Corporation
9.3.8. Finastra
9.3.9. Jack Henry & Associates, Inc.
9.3.10. NCR Corporation
Chapter 10. Research Process
10.1. Research Process
10.1.1. Data Mining
10.1.2. Analysis
10.1.3. Market Estimation
10.1.4. Validation
10.1.5. Publishing
10.2. Research Attributes
10.3. Research Assumption

At Bizwit Research and Consultancy, we employ a thorough and iterative research methodology with the goal of minimizing discrepancies, ensuring the provision of highly accurate estimates and predictions over the forecast period. Our approach involves a combination of bottom-up and top-down strategies to effectively segment and estimate quantitative aspects of the market, utilizing our proprietary data & AI tools. Our Proprietary Tools allow us for the creation of customized models specific to the research objectives. This enables us to develop tailored statistical models and forecasting algorithms to estimate market trends, future growth, or consumer behavior. The customization enhances the accuracy and relevance of the research findings.
We are dedicated to clearly communicating the purpose and objectives of each research project in the final deliverables. Our process begins by identifying the specific problem or challenge our client wishes to address, and from there, we establish precise research questions that need to be answered. To gain a comprehensive understanding of the subject matter and identify the most relevant trends and best practices, we conduct an extensive review of existing literature, industry reports, case studies, and pertinent academic research.
Critical elements of methodology employed for all our studies include:
Data Collection:
To determine the appropriate methods of data collection based on the research objectives, we consider both primary and secondary sources. Primary data collection involves gathering information directly from various industry experts in core and related fields, original equipment manufacturers (OEMs), vendors, suppliers, technology developers, alliances, and organizations. These sources encompass all segments of the value chain within the specific industry. Through in-depth interviews, we engage with key industry participants, subject-matter experts, C-level executives of major market players, industry consultants, and other relevant experts. This allows us to obtain and validate critical qualitative and quantitative information while evaluating market prospects. AI and Big Data are instrumental in our primary research, providing us with powerful tools to collect, analyze, and derive insights from data efficiently. These technologies contribute to the advancement of research methodologies, enabling us to make data-driven decisions and uncover valuable findings.
In addition to primary sources, we extensively utilize secondary sources to enhance our research. These include directories, databases, journals focusing on related industries, company newsletters, and information portals such as Bloomberg, D&B Hoovers, and Factiva. These secondary sources enable us to identify and gather valuable information for our comprehensive, technical, market-oriented, and commercial study of the market. Additionally, we utilize AI algorithms to automate the collection of vast amounts of data from various sources such as surveys, social media platforms, online transactions, and web scraping. And employ Big Data technologies for storage and processing of large datasets, ensuring that no valuable information is missed during the data collection process.
Data Analysis:
Our team of experts carefully examine the gathered data using suitable statistical techniques and qualitative analysis methods. For quantitative analysis, we employ descriptive statistics, regression analysis, and other advanced statistical methods, depending on the characteristics of the data. This analysis may also incorporate the utilization of AI tools and big data analysis techniques to extract meaningful insights.
To ensure the accuracy and reliability of our findings, we extensively leverage data science techniques, which help us minimize discrepancies and uncertainties in our analysis. We employ Data Science to clean and preprocess the data, ensuring its quality and reliability. This involves handling missing data, removing outliers, standardizing variables, and transforming data into suitable formats for analysis. The application of data science techniques enhances our accuracy, efficiency, and depth of analysis, enabling us to stay competitive in dynamic market environments.
Market Size Estimation:
Our proprietary data tools play a crucial role in deriving our market estimates and forecasts. Each study involves the creation of a unique and customized model. The model incorporates the gathered information on market dynamics, technology landscape, application development, and pricing trends. AI techniques, such as machine learning and deep learning, aid us to analyze patterns within the data to identify correlations, trends, and relationships. By recognizing patterns in consumer behavior, purchasing habits, or market dynamics, our AI algorithms aid us in more precise estimations of market size. These factors are simultaneously analyzed within the model, allowing for a comprehensive assessment. To quantify their impact over the forecast period, correlation, regression, and time series analysis are employed.
To estimate and validate the market size, we employ both top-down and bottom-up approaches. The preference is given to a bottom-up approach, where key regional markets are analyzed as separate entities. This data is then integrated to obtain global estimates. This approach is crucial as it provides a deep understanding of the industry and helps minimize errors.
In our forecasting process, we consider various parameters such as economic tools, technological analysis, industry experience, and domain expertise. By taking all these factors into account, we strive to produce accurate and reliable market forecasts. When forecasting, we take into consideration several parameters, which include:
Market driving trends and favorable economic conditions
Restraints and challenges that are expected to be encountered during the forecast period.
Anticipated opportunities for growth and development
Technological advancements and projected developments in the market
Consumer spending trends and dynamics
Shifts in consumer preferences and behaviors.
The current state of raw materials and trends in supply versus pricing
Regulatory landscape and expected changes or developments.
The existing capacity in the market and any expected additions or expansions up to the end of the forecast period.
To assess the market impact of these parameters, we assign weights to each one and utilize weighted average analysis. This process allows us to quantify their influence on the market and derive an expected growth rate for the forecasted period. By considering these various factors and applying a weighted analysis approach, we strive to provide accurate and reliable market forecasts.
Insight Generation & Report Presentation:
After conducting the research, our experts analyze the findings in relation to the research objectives and the specific needs of the client. They generate valuable insights and recommendations that directly address the client’s business challenges. These insights are carefully connected to the research findings to provide a comprehensive understanding.
Next, we create a well-structured research report that effectively communicates the research findings, insights, and recommendations to the client. To enhance clarity and comprehension, we utilize visual aids such as charts, graphs, and tables. These visual elements are employed to present the data in an engaging and easily understandable format, ensuring that the information is accessible and visually appealing to the client. Our aim is to deliver a clear and concise report that conveys the research findings effectively and provides actionable recommendations to meet the client’s specific needs.

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