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Global Payment Monitoring Market to reach USD 59.57 billion by the end of 2030.

Global Payment Monitoring Market Size Study & Forecast, by Component (Solution, Services), By Organization Size (Large Enterprises, Small & Medium Enterprises), By Application (Anti-Money Laundering, Compliance Management & Customer Identity Management, Fraud Detection & Prevention), By End User (BFSI, IT & Telecom, Healthcare, Retail & e-commerce, Government & Defense, Others), and Regional Analysis, 2023-2030

Product Code: ICTNGT-24150846
Publish Date: 20-05-2023
Page: 200

Global Payment Monitoring Market is valued at approximately USD 8.18 billion in 2022 and is anticipated to grow with a healthy growth rate of more than 28.17% over the forecast period 2023-2030. Payment Monitoring is the process of monitoring and analyzing payment transactions to detect and prevent fraudulent activities, money laundering, cyber threats, and other financial crimes. It assists financial institutions, payment service providers, and other organizations to mitigate risk and ensure compliance with regulatory requirements. These solutions use advanced analytics, machine learning algorithms, and real-time monitoring to analyze payment data and identify suspicious transactions. The increasing requirement for managing KYC compliance and CTF activities, growing awareness among organizations to comply with regulatory requirements and multi-channel monitoring, the surge in the payment data volumes, and rise in payment fraudulent activities are the most prominent factors that are propelling the market demand across the globe.

The rising inclination towards digital payments is acting as a catalyzing factor for the growth of the market. The shift towards digital payments and online transactions has created new opportunities for payment monitoring solutions. Accordingly, increasing adoption of digital payment methods by consumers and businesses is stipulating demand for payment monitoring. According to Statista, in 2022, the overall transaction value in the digital payments segment is estimated to account for USD 8.49 trillion. Also, it is projected that the total amount is likely to reach USD 15.17 trillion by 2027 with a CAGR of 12.31% during 2022-2027. Hence, the increasing preference for digital payments is exhibiting a positive influence on the market demand in the global market. Moreover, the rise in advancement in payment monitoring solution incorporating AI and ML and the growing awareness for real-time monitoring presents various lucrative opportunities over the forecasting years. However, the lack of risk analysis professionals and difficulties in managing cross-border and multi-jurisdictional AML compliance are hindering the market growth throughout the forecast period of 2023-2030.

The key regions considered for the Global Payment Monitoring Market study include Asia Pacific, North America, Europe, Latin America, and Middle East & Africa. North America dominated the market in 2022 owing to the growing need for managing KYC compliance and CTF activities, as well as early implementation of novel technologies and solutions for proficiently managing business operations. Whereas, Asia Pacific is expected to grow at the highest CAGR over the forecasting years. The rapid growth of the e-commerce industry, growing payment data volumes, increasing number of payment fraudulent activities, along with the presence of emerging economies are significantly propelling the market demand across the region.

Major market players included in this report are:
BAE Systems
Fair Isaac Corporation
ACI Worldwide Inc.
Fiserv Inc.
Oracle Corporation
SAS Institute
Nice Ltd.
Software AG
Thomson Reuters Corporation

Recent Developments in the Market:
Ø In November 2022, Travelex Bank, a foreign exchange specialist in Brazil unveiled hteir preparation for a growth spurt across its money transfer business by deploying ThetaRay’s SONAR anti-money laundering (AML) SaaS solution for domestic and international transaction monitoring and real-time sanctions screening.

Global Payment Monitoring 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 – Component, Organization Size, Application, End User, 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 Component:

By Organization Size:
Large Enterprises
Small & Medium Enterprises

By Application:
Anti-Money Laundering
Compliance Management & Customer Identity Management
Fraud Detection & Prevention

By End User:
IT & Telecom
Retail & e-commerce
Government & Defense

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. Payment Monitoring Market, by Region, 2020-2030 (USD Billion)
1.2.2. Payment Monitoring Market, by Component, 2020-2030 (USD Billion)
1.2.3. Payment Monitoring Market, by Organization Size, 2020-2030 (USD Billion)
1.2.4. Payment Monitoring Market, by Application, 2020-2030 (USD Billion)
1.2.5. Payment Monitoring Market, by End User, 2020-2030 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Payment Monitoring 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 Payment Monitoring Market Dynamics
3.1. Payment Monitoring Market Impact Analysis (2020-2030)
3.1.1. Market Drivers Increase in payment fraudulent activities Rising inclination towards digital payments
3.1.2. Market Challenges Lack of risk analysis professionals Difficulties in managing cross-border and multi-jurisdictional AML compliance
3.1.3. Market Opportunities Rise in advancement in payment monitoring solution incorporating AI and ML Growing awareness for real-time monitoring
Chapter 4. Global Payment Monitoring 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 Payment Monitoring Market, by Component
5.1. Market Snapshot
5.2. Global Payment Monitoring Market by Component, Performance – Potential Analysis
5.3. Global Payment Monitoring Market Estimates & Forecasts by Component 2020-2030 (USD Billion)
5.4. Payment Monitoring Market, Sub Segment Analysis
5.4.1. Solution
5.4.2. Services
Chapter 6. Global Payment Monitoring Market, by Organization Size
6.1. Market Snapshot
6.2. Global Payment Monitoring Market by Organization Size, Performance – Potential Analysis
6.3. Global Payment Monitoring Market Estimates & Forecasts by Organization Size 2020-2030 (USD Billion)
6.4. Payment Monitoring Market, Sub Segment Analysis
6.4.1. Large Enterprises
6.4.2. Small & Medium Enterprises
Chapter 7. Global Payment Monitoring Market, by Application
7.1. Market Snapshot
7.2. Global Payment Monitoring Market by Application, Performance – Potential Analysis
7.3. Global Payment Monitoring Market Estimates & Forecasts by Application 2020-2030 (USD Billion)
7.4. Payment Monitoring Market, Sub Segment Analysis
7.4.1. Anti-Money Laundering
7.4.2. Compliance Management & Customer Identity Management
7.4.3. Fraud Detection & Prevention
Chapter 8. Payment Monitoring Market, by End User
8.1. Market Snapshot
8.2. Global Payment Monitoring Market by End User, Performance – Potential Analysis
8.3. Global Payment Monitoring Market Estimates & Forecasts by End User 2020-2030 (USD Billion)
8.4. Payment Monitoring Market, Sub Segment Analysis
8.4.1. BFSI
8.4.2. IT & Telecom
8.4.3. Healthcare
8.4.4. Retail & e-commerce
8.4.5. Government & Defense
8.4.6. Others
Chapter 9. Global Payment Monitoring Market, Regional Analysis
9.1. Top Leading Countries
9.2. Top Emerging Countries
9.3. Payment Monitoring Market, Regional Market Snapshot
9.4. North America Payment Monitoring Market
9.4.1. U.S. Payment Monitoring Market Component breakdown estimates & forecasts, 2020-2030 Organization Size breakdown estimates & forecasts, 2020-2030 Application breakdown estimates & forecasts, 2020-2030 End User breakdown estimates & forecasts, 2020-2030
9.4.2. Canada Payment Monitoring Market
9.5. Europe Payment Monitoring Market Snapshot
9.5.1. U.K. Payment Monitoring Market
9.5.2. Germany Payment Monitoring Market
9.5.3. France Payment Monitoring Market
9.5.4. Spain Payment Monitoring Market
9.5.5. Italy Payment Monitoring Market
9.5.6. Rest of Europe Payment Monitoring Market
9.6. Asia-Pacific Payment Monitoring Market Snapshot
9.6.1. China Payment Monitoring Market
9.6.2. India Payment Monitoring Market
9.6.3. Japan Payment Monitoring Market
9.6.4. Australia Payment Monitoring Market
9.6.5. South Korea Payment Monitoring Market
9.6.6. Rest of Asia Pacific Payment Monitoring Market
9.7. Latin America Payment Monitoring Market Snapshot
9.7.1. Brazil Payment Monitoring Market
9.7.2. Mexico Payment Monitoring Market
9.8. Middle East & Africa Payment Monitoring Market
9.8.1. Saudi Arabia Payment Monitoring Market
9.8.2. South Africa Payment Monitoring Market
9.8.3. Rest of Middle East & Africa Payment Monitoring Market

Chapter 10. Competitive Intelligence
10.1. Key Company SWOT Analysis
10.1.1. Company 1
10.1.2. Company 2
10.1.3. Company 3
10.2. Top Market Strategies
10.3. Company Profiles
10.3.1. BAE Systems Key Information Overview Financial (Subject to Data Availability) Product Summary Recent Developments
10.3.2. Fair Isaac Corporation
10.3.3. ACI Worldwide Inc.
10.3.4. Fiserv Inc.
10.3.5. Oracle Corporation
10.3.6. SAS Institute
10.3.7. FIS
10.3.8. Nice Ltd.
10.3.9. Software AG
10.3.10. Thomson Reuters Corporation
Chapter 11. Research Process
11.1. Research Process
11.1.1. Data Mining
11.1.2. Analysis
11.1.3. Market Estimation
11.1.4. Validation
11.1.5. Publishing
11.2. Research Attributes
11.3. 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.
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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.
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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.
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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
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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.
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