BANKING, FINANCIAL SERVICES & INSURANCE
Global Fraud Management in Banking Market - Industry Trends and Forecast to 2032
REPORT OVERVIEW
Global Fraud Management in Banking Market, By Component (Solution, Service), Fraud Type (Payment Fraud, Loan Fraud, Identity Theft, Money Laundering, Others), Application (Fraud Detection and Prevention Systems, Identity and Access Management (IAM), Customer Authentication, Transaction Monitoring, Others), Region (North America, Europe, Asia-Pacific, South America, Middle East and Africa) – Industry Trends and Forecast to 2032.
Market Insights
The global Fraud Management in Banking market size is valued to be USD xx million in 2023 and is expected to reach USD xx million by 2032, and it is expected to register a CAGR of xx% over the forecast period 2024-2032.
Fraud management in banking refers to the comprehensive set of strategies, processes, technologies, and measures implemented by financial institutions to detect, prevent, and mitigate fraudulent activities.
Market Dynamics
DRIVERS
- Increasing Sophistication of Fraud Techniques
- Rise in Digital Banking and Online Transactions
RESTRAINTS
- Balancing Security with Customer Experience
- Complexity of Multi-Channel Transactions
OPPORTUNITIES
- Behavioral Biometrics and Authentication Innovations
- Blockchain and Distributed Ledger Technology
CHALLENGES
- Resource Constraints and Budget Limitations
- Insider Threats and Employee Fraud
SEGMENTATION
MARKET SEGMENTATION
- Component
- Solution
- Service
- Fraud Type
- Payment Fraud
- Loan Fraud
- Identity Theft
- Money Laundering
- Others
- Application
- Fraud Detection and Prevention Systems
- Identity and Access Management (IAM)
- Customer Authentication
- Transaction Monitoring
- Others
The respective global report is completely customizable specific to regions (North America, Europe, Asia-Pacific, South America, Middle East and Africa), countries, segments, and key players as per the client requirements.
REGIONAL SEGMENTATION
- North America
- U.S.
- Canada
- Mexico
- Rest of North America
- Europe
- Germany
- U.K.
- France
- Italy
- Spain
- Russia
- The Netherlands
- Belgium
- Turkey
- Rest of Europe
- Asia-Pacific
- China
- India
- Japan
- South Korea
- Singapore
- Malaysia
- Australia
- Thailand
- Philippines
- Rest of Asia-Pacific
- South America
- Brazil
- Argentina
- Chile
- Colombia
- Rest of South America
- Middle East and Africa
- Kingdom of Saudi Arabia
- South Africa
- U.A.E.
- Egypt
- Rest of Middle East and Africa
KEY MARKET PLAYERS
- IBM Corporation
- SAS Institute Inc
- SAP SE
- NICE Actimize
- ACI Worldwide Inc
- Experian PLC
- BAE Systems
- FIS Global
- LexisNexis Risk Solutions
- BioCatch Ltd
Table OF CONTENTS
- SECTION 1 - INTRODUCTION
- 1.1 Taxonomy
- 1.2 Market Overview
- 1.3 Currency and Limitations
- 1.3.1 Currency
- 1.3.2 Limitations
- 1.4 Key Competitors
- SECTION 2 - RESEARCH METHODOLOGY
- 2.1 Research Approach
- 2.2 Data Collection and Validation
- 2.2.1 Secondary Research
- 2.2.2 Primary Research
- 2.3 Market Assessment
- 2.3.1 Market Size Estimation
- 2.3.2 Bottom-up Approach
- 2.3.3 Top-down Approach
- 2.3.4 Growth Forecast
- 2.4 Market Study Assumptions
- 2.5 Data Sources
- SECTION 3 - EXECUTIVE SUMMARY
- 3.1 Global Fraud Management in Banking Market, by Component
- 3.2 Global Fraud Management in Banking Market, by Fraud Type
- 3.3 Global Fraud Management in Banking Market, by Application
- 3.4 Global Fraud Management in Banking Market, by Geography
- 3.5 Market Position Grid
- SECTION 4 - PREMIUM INSIGHTS
- 4.1 Regulatory Framework
- 4.1.1 Standards
- 4.1.2 Regulatory Landscape
- 4.2 Value Chain Analysis
- 4.3 Supply Chain Analysis
- 4.4 COVID-19 Impact
- 4.5 Russia-Ukraine War Impact
- 4.6 PORTER's Five Force Analysis
- 4.7 PESTLE Analysis
- 4.8 SWOT Analysis
- 4.9 Go to Market Strategy
- 4.10 Opportunity Orbit
- 4.11 Multivariate Modelling
- 4.12 Pricing Analysis
- SECTION 5 - MARKET DYNAMICS
- 5.1 Trends
- 5.1.1 Trend 1
- 5.1.2 Trend 2
- 5.1.3 Trend 3
- 5.2 Drivers
- 5.2.1 Increasing Sophistication of Fraud Techniques
- 5.2.2 Rise in Digital Banking and Online Transactions
- 5.2.3 Driver 3
- 5.2.4 Driver 4
- 5.3 Restraints
- 5.3.1 Balancing Security with Customer Experience
- 5.3.2 Complexity of Multi-Channel Transactions
- 5.3.3 Restraint 3
- 5.4 Opportunities
- 5.4.1 Behavioral Biometrics and Authentication Innovations
- 5.4.2 Blockchain and Distributed Ledger Technology
- 5.4.3 Opportunity 3
- 5.4.4 Opportunity 4
- 5.5 Challenges
- 5.5.1 Resource Constraints and Budget Limitations
- 5.5.2 Insider Threats and Employee Fraud
- 5.5.3 Challenge 3
- SECTION 6 - GLOBAL FRAUD MANAGEMENT IN BANKING MARKET, BY COMPONENT
- 6.1 Component Summary
- 6.2 Market Attractive Index
- 6.3 Global Fraud Management in Banking Market, by Component (2019-2032)
- SECTION 7 - GLOBAL FRAUD MANAGEMENT IN BANKING MARKET, BY FRAUD TYPE
- 7.1 Fraud Type Summary
- 7.2 Market Attractive Index
- 7.3 Global Fraud Management in Banking Market, by Fraud Type (2019-2032)
- SECTION 8 - GLOBAL FRAUD MANAGEMENT IN BANKING MARKET, BY APPLICATION
- 8.1 Application Summary
- 8.2 Market Attractive Index
- 8.3 Global Fraud Management in Banking Market, by Application (2019-2032)
- SECTION 9 - GLOBAL FRAUD MANAGEMENT IN BANKING MARKET, BY GEOGRAPHY
- 9.1 Regional Summary
- 9.2 Market Attractive Index
- 9.3 Global Fraud Management in Banking Market, by Geography (2019-2032)
- SECTION 10 - NORTH AMERICA FRAUD MANAGEMENT IN BANKING MARKET
- 10.1 North America Summary
- 10.2 Market Attractive Index
- 10.3 North America Fraud Management in Banking Market, by Component (2019-2032)
- 10.4 North America Fraud Management in Banking Market, by Fraud Type (2019-2032)
- 10.5 North America Fraud Management in Banking Market, by Application (2019-2032)
- 10.6 North America Fraud Management in Banking Market, by Country (2019-2032)
- 10.6.1 U.S.
- 10.6.2 Canada
- 10.6.3 Mexico
- 10.6.4 Rest of North America
- SECTION 11 - EUROPE FRAUD MANAGEMENT IN BANKING MARKET
- 11.1 Europe Summary
- 11.2 Market Attractive Index
- 11.3 Europe Fraud Management in Banking Market, by Component (2019-2032)
- 11.4 Europe Fraud Management in Banking Market, by Fraud Type (2019-2032)
- 11.5 Europe Fraud Management in Banking Market, by Application (2019-2032)
- 11.6 Europe Fraud Management in Banking Market, by Country (2019-2032)
- 11.6.1 Germany
- 11.6.2 U.K.
- 11.6.3 France
- 11.6.4 Italy
- 11.6.5 Spain
- 11.6.6 Russia
- 11.6.7 The Netherlands
- 11.6.8 Belgium
- 11.6.9 Turkey
- 11.6.10 Rest of Europe
- SECTION 12 - ASIA-PACIFIC FRAUD MANAGEMENT IN BANKING MARKET
- 12.1 Asia-Pacific Summary
- 12.2 Market Attractive Index
- 12.3 Asia-Pacific Fraud Management in Banking Market, by Component (2019-2032)
- 12.4 Asia-Pacific Fraud Management in Banking Market, by Fraud Type (2019-2032)
- 12.5 Asia-Pacific Fraud Management in Banking Market, by Application (2019-2032)
- 12.6 Asia-Pacific Fraud Management in Banking Market, by Country (2019-2032)
- 12.6.1 China
- 12.6.2 India
- 12.6.3 Japan
- 12.6.4 South Korea
- 12.6.5 Singapore
- 12.6.6 Malaysia
- 12.6.7 Australia
- 12.6.8 Thailand
- 12.6.9 Philippines
- 12.6.10 Rest of Asia-Pacific
- SECTION 13 - SOUTH AMERICA FRAUD MANAGEMENT IN BANKING MARKET
- 13.1 South America Summary
- 13.2 Market Attractive Index
- 13.3 South America Fraud Management in Banking Market, by Component (2019-2032)
- 13.4 South America Fraud Management in Banking Market, by Fraud Type (2019-2032)
- 13.5 South America Fraud Management in Banking Market, by Application (2019-2032)
- 13.6 South America Fraud Management in Banking Market, by Country (2019-2032)
- 13.6.1 Brazil
- 13.6.2 Argentina
- 13.6.3 Chile
- 13.6.4 Colombia
- 13.6.5 Rest of South America
- SECTION 14 - MIDDLE EAST AND AFRICA FRAUD MANAGEMENT IN BANKING MARKET
- 14.1 Middle East and Africa Summary
- 14.2 Market Attractive Index
- 14.3 Middle East and Africa Fraud Management in Banking Market, by Component (2019-2032)
- 14.4 Middle East and Africa Fraud Management in Banking Market, by Fraud Type (2019-2032)
- 14.5 Middle East and Africa Fraud Management in Banking Market, by Application (2019-2032)
- 14.6 Middle East and Africa Fraud Management in Banking Market, by Country (2019-2032)
- 14.6.1 Kingdom of Saudi Arabia
- 14.6.2 South Africa
- 14.6.3 U.A.E.
- 14.6.4 Egypt
- 14.6.5 Rest of Middle East and Africa
- SECTION 15 - COMPANY SHARE ANALYSIS
- 15.1 Global Fraud Management in Banking Market, Company Share Analysis
- 15.2 North America Fraud Management in Banking Market, Company Share Analysis
- 15.3 Europe Fraud Management in Banking Market, Company Share Analysis
- 15.4 Asia-Pacific Fraud Management in Banking Market, Company Share Analysis
- SECTION 16 - COMPANY PROFILES
- 16.1 IBM Corporation
- 16.1.1 Company Snapshot
- 16.1.2 Financial Overview
- 16.1.3 Product Portfolio
- 16.1.4 Recent Developments
- 16.2 SAS Institute Inc
- 16.2.1 Company Snapshot
- 16.2.2 Financial Overview
- 16.2.3 Product Portfolio
- 16.2.4 Recent Developments
- 16.3 SAP SE
- 16.3.1 Company Snapshot
- 16.3.2 Financial Overview
- 16.3.3 Product Portfolio
- 16.3.4 Recent Developments
- 16.4 NICE Actimize
- 16.4.1 Company Snapshot
- 16.4.2 Financial Overview
- 16.4.3 Product Portfolio
- 16.4.4 Recent Developments
- 16.5 ACI Worldwide Inc
- 16.5.1 Company Snapshot
- 16.5.2 Financial Overview
- 16.5.3 Product Portfolio
- 16.5.4 Recent Developments
- 16.6 Experian PLC
- 16.6.1 Company Snapshot
- 16.6.2 Financial Overview
- 16.6.3 Product Portfolio
- 16.6.4 Recent Developments
- 16.7 BAE Systems
- 16.7.1 Company Snapshot
- 16.7.2 Financial Overview
- 16.7.3 Product Portfolio
- 16.7.4 Recent Developments
- 16.8 FIS Global
- 16.8.1 Company Snapshot
- 16.8.2 Financial Overview
- 16.8.3 Product Portfolio
- 16.8.4 Recent Developments
- 16.9 LexisNexis Risk Solutions
- 16.9.1 Company Snapshot
- 16.9.2 Financial Overview
- 16.9.3 Product Portfolio
- 16.9.4 Recent Developments
- 16.10 BioCatch Ltd
- 16.10.1 Company Snapshot
- 16.10.2 Financial Overview
- 16.10.3 Product Portfolio
- 16.10.4 Recent Developments
- SECTION 17 - RELATED REPORTS
- SECTION 18 - DISCLAIMER
RESEARCH METHODOLOGY
The research methodology employed in Uniprism Market Research involves four basic steps namely research and data collection, data pre-processing, modeling and forecasting, quality assurance and output.
RESEARCH AND DATA COLLECTION
A tripod model research technique is followed for research and data collection in which various approaches such as primary research, secondary research, and product mapping are considered.
Primary research basically involves the process of conducting personalized interviews with market related professionals of major market players, investors, distributors, vendors and many more.
The secondary research include data published by government, annual reports, press releases, investor presentations of companies, white papers, certified publications, annual manufacturing limit of the respective industries related to the market, production consumption analysis of certain products respective to the market and many more.
Below mention are few of the sources which we have considered while estimating the market size:
For instance,
- Research articles published on Technium
- Science and MDPI
- Research publications by government approved associations and societies
Product mapping means the process of mapping the list of products that a key player contributes to the market as well as estimating the revenue of those products in order to define the Global Company share analysis of the respective Global Company in global, regional, and country level markets.
DATA PRE-PROCESSING
The term "data pre-processing" refers to the collection of procedures and methods used to clean, modify, and make ready for analysis the raw data gathered during research and data collection. The completion of this phase is necessary to guarantee that the data are reliable, consistent, and appropriate for statistical analysis and other data-driven tasks. The data pre-processing ensures that the information gathered from research and data collection is comparable and expressed in standard units, by the integration of missing data pointers and algorithmic approaches.
MODELING AND FORECASTING
The process of developing mathematical, statistical, or computational representations of real-world occurrences or relationships is known as modelling. These models are intended to replicate and explain market interactions, interdependence, and dynamics. These models are used by Uniprism Market Research to acquire a better knowledge of numerous market characteristics such as customer preferences, pricing elasticity, competition dynamics, and more. Depending on the individual study aims, many types of models are utilized, such as regression models, econometric models, decision tree models, and machine learning models.
Forecasting is the process of predicting future market conditions, trends, and occurrences using past data and models. Forecasting is used by Uniprism Market Research to estimate future sales, demand for products or services, market growth, and other important performance metrics. Forecasting accurately can assist organizations in making educated decisions about resource allocation, pricing, inventory management, and marketing tactics.
We create standardized bottom-up or top-down models that scale by leveraging data science and machine learning technology. All our market models consider the unique market characteristics of each country. Forecasting is based on major market indicators and a combination of traditional methodologies, such as exponential smoothing, time series analysis, regression analysis, and more modern techniques such as machine learning algorithms are all forecasting methodologies. The method chosen is determined on the nature of the data and the specific forecasting aims.
QUALITY ASSURANCE AND OUTPUT
Quality assurance and output involves the process of validation, adjustments, further publications of key market indicators. Extensive plausibility and consistency tests are performed on derived time series to ensure the high degree of quality of our market analysis. This quality assurance procedure also includes rigorous inspection, validation, and editing by an experienced management team to assure the dependability of the published data.