은행 사기 탐지 및 방지 시장(2025-2030년)

'Fraud to Cost Financial Institutions $58.3 Billion by 2030 Globally, as Synthetic Identities Threaten Fraud Tidal Wave'

Overview

Our 'Fraud Detection and Prevention in Banking' research suite provides a comprehensive and in-depth analysis of the types of fraud, and methods that can be used to overcome them. This enables stakeholders such as banks, financial institutions, and fintechs to understand future growth, key trends and the competitive environment. The report evaluates emerging elements of banking fraud, highlights key market trends, and examines regional opportunities in fraud solution adoption.

The suite includes several different options that can be purchased separately, including access to data mapping the future spend on fraud solutions by financial institutions, an insightful study uncovering the latest trends and opportunities within the fraud prevention market, and a document containing extensive analysis of the 15 market leaders facilitating fraud prevention solutions. The coverage can also be purchased as a Full Research Suite, containing all these elements, at a substantial discount.

This report serves as an essential resource for understanding the rapidly evolving fraud landscape; empowering stakeholders to shape effective future strategies. With its comprehensive insights and extensive coverage, this research suite is an invaluable tool for navigating and planning in a fast-growing landscape.

All report content is delivered in the English language.

Key Features

• Market Dynamics: Insights into key trends and market expansion challenges within the fraud prevention solutions market, including drivers of fraud and major challenges faced by financial institutions regarding fraud. The report addresses the role of fraud prevention solutions in monitoring transactions for risk, the use of machine learning in fraud prevention, and the regulations affecting the fraud prevention landscape. The research also features a Country Readiness Index on the current development and segment growth of the fraud prevention market across eight key regions, as well as providing a future outlook.
• Key Takeaways & Strategic Recommendations: In-depth analysis of key development opportunities and findings within the solutions for fraud prevention market, accompanied by strategic recommendations for stakeholders.
• Benchmark Industry Forecasts: The fraud detection and prevention dataset includes forecasts for the total value of fraudulent transactions, including the spend on fraud prevention solutions by financial institutions, and the transaction volume of various market segments.
• Juniper Research Competitor Leaderboard: Key market player capability and capacity assessment for 15 fraud prevention vendors, via the Juniper Research Competitor Leaderboard; featuring market size for major players in the fraud prevention market.

SAMPLE VIEW

Market Data & Forecasting Report

The numbers tell you what's happening, but our written report details why, alongside the methodologies.

SAMPLE VIEW

Market Trends & Strategies Report

A comprehensive analysis of the current market landscape, alongside strategic recommendations.

Market Data & Forecasting Report

The market-leading research suite for the 'Fraud Detection and Prevention in Banking' market includes access to the full set of forecast data of 54 tables and 24,600 datapoints.

Metrics in the research suite include:

• Total Transaction Volume and Value of Fraudulent Transactions
• Total Annual Spend on Fraud Detection and Prevention Solutions by Banks and Financial Institutions, Split by the Following Market Segments:
  • Banks and Credit Unions
  • Fintechs
  • Investment Companies
  • Lending Companies

Juniper Research's Interactive Forecast Excel contains the following functionality:

• Statistics Analysis: Users benefit from the ability to search for specific metrics, displayed for all regions and countries across the data period. Graphs are easily modified and can be exported to the clipboard.
• Country Data Tool: This tool lets users look at metrics for all regions and countries in the forecast period. Users can refine the metrics displayed via a search bar.
• Country Comparison Tool: Users can select and compare specific countries. The ability to export graphs is included in this tool.
• What-if Analysis: Here, users can compare forecast metrics against their own assumptions, via five interactive scenarios.

Market Trends & Strategies Report

This report examines the 'Fraud Detection and Prevention in Banking' market landscape in depth; assessing trends and factors shaping the evolution of this rapidly growing market. The report delivers comprehensive analysis of the strategic opportunities for vendors providing fraud prevention solutions; addressing key verticals such as banks, credit unions, fintechs, investment companies, and lenders. This report also includes evaluation of key country-level opportunities for stakeholders in the fraud prevention market.

Competitor Leaderboard Report

The Competitor Leaderboard report provides a detailed evaluation and market positioning for 15 leading vendors in the fraud prevention space. The vendors are positioned as established leaders, leading challengers, or disruptors and challengers, based on capacity and capability assessments:

This document is centred around the Juniper Research Competitor Leaderboard; a vendor positioning tool that provides an at-a-glance view of the competitive landscape in a market, backed by a robust methodology.

Table of Contents

Market Trends & Strategies

1. Market Summary

• 1.1. Key Takeaways & Strategic Recommendations
• 1.2. Strategic Recommendations

2. Market Landscape

• 2.1. Market Landscape & Segmentation
  • 2.1.1. Introduction
  • 2.1.2. Definitions and Scope
• 2.2. Types of Fraud
  • Figure 2.1: Types of Fraud
  • 2.2.1. First-party Fraud
    • i. Application Fraud and Fake Accounts
    • ii. Money Mules
    • iii. Fronting
    • iv. Sleeper Fraud
    • v. APP Fraud
    • vi. Social Engineering Fraud
  • 2.2.2. Money Laundering
  • 2.2.3. Chargeback Fraud
  • 2.2.4. ATO
  • 2.2.5. Synthetic Identity
    • i. Detection of Synthetic Identity Fraud
  • 2.2.6. AI-driven Fraud
  • 2.2.7. Insider Threat
• 2.3. Solutions Used in Issuer Fraud Detection & Prevention
  • 2.3.1. Fraud Detection & Prevention Systems
    • i. Biometric Identification
    • ii. Tokenisation
    • iii. Behavioural Analytics
    • iv. AML Software
• 2.4. Challenges
  • 2.4.1. Introduction
    • Figure 2.2: Major Challenges Faced by Financial Institutions in the Fraud Landscape
  • 2.4.2. Inflation and Financial Uncertainty
  • 2.4.3. Technological Advancement
  • 2.4.4. Urgent Need to Protect the 'Underbanked'
  • 2.4.5. Rapidly Evolving Fraud Landscape
  • 2.4.6. Cyber Security Talent Shortage

3. Sector Analysis: Payment Types

• 3.1. Payment Types
  • 3.1.1. Open Banking
    • i. Avenues of Fraud Through Open Banking
    • ii. How Open Banking Can Help Prevent Banking Fraud
  • 3.1.2. Buy Now, Pay Later
  • 3.1.3. CBDCs
  • 3.1.4. Cryptocurrency
  • 3.1.5. Instant Payments
  • 3.1.6. Money Transfer
  • 3.1.7. QR Codes
    • i. Avenues of Fraud Via QR Code Payments
    • ii. How QR Code Payments Can Reduce Fraud
• 4.1. Solutions & Opportunities
  • 4.1.1. AI
    • i. Advantages of AI in Fraud Detection and Prevention
    • ii. Disadvantages of AI in Fraud Detection and Prevention
  • 4.1.2. Machine Learning
    • i. Advantages of Machine Learning in Fraud Detection and Prevention
    • ii. Disadvantages of ML in Fraud Detection and Prevention
  • 4.1.3. APIs
    • i. Advantages of APIs in Fraud Detection and Prevention
    • ii. Disadvantages of APIs in Fraud Detection and Prevention
  • 4.1.4. Quantum-safe Cryptography
    • i. Advantages of Quantum-safe Cryptography in Fraud Detection and Prevention
    • ii. Disadvantages of Quantum-safe Cryptography in Fraud Detection and Prevention
• 4.2. Regulations
  • 4.2.1. UK Faster Payments Regulation
  • 4.2.2. PSD2
  • 4.2.3. Brazil's PIX Instant Payment Regulation
  • 4.2.4. India's UPI and Real-time Payment Regulation

5. Segment Analysis: Business Verticals

• 5.1. Segment Analysis
  • 5.1.1. Introduction
  • 5.1.2. Banks and Credit Unions
  • 5.1.3. Fintechs
  • 5.1.4. Lenders
  • 5.1.5. Investment Companies
  • 5.1.6. Value-added Services
  • 5.1.7. Invoice Financing
  • 5.1.8. Accounts Payable (AP) and Accounts Receivable (AR) Automation
  • 5.1.9. Trade Financing
  • 5.1.10. Cashflow Forecasting and Analytics
  • 5.1.11. Reconciliation Services

Competitor Leaderboard

1. Competitor Leaderboard

• 1.1. Why Read This Report
  • Figure 1.1: Juniper Research Competitor Leaderboard: Fraud Detection & Prevention in Banking Vendor Product Portfolio
  • Figure 1.2: Juniper Research Leaderboard: Fraud Detection & Prevention in Banking Vendors
  • Table 1.3: Juniper Research Leaderboard: Fraud Detection & Prevention in Banking Vendor Positioning
  • Figure 1.4: Juniper Research Leaderboard Heatmap: Fraud Detection & Prevention in Banking Vendors
• 1.2. Issuer Fraud Prevention Vendor Profiles
  • 1.2.1. Accertify
    • i. Corporate Information
    • ii. Geographical Spread
    • iii. Key Clients & Strategic Partnerships
    • iv. High-level View of Offerings
    • v. Juniper Research's View: Key Strengths & Strategic Development Opportunities
  • 1.2.2. ACI Worldwide
    • i. Corporate Information
    • ii. Geographical Spread
    • iii. Key Clients & Strategic Partnerships
    • iv. High-level View of Offerings
    • v. Juniper Research's View: Key Strengths & Strategic Development Opportunities
  • 1.2.3. ComplyAdvantage
    • i. Corporate Information
    • ii. Geographical Spread
    • iii. Key Clients & Strategic Partnerships
    • iv. High-level View of Offerings
    • v. Juniper Research's View: Key Strengths & Strategic Development Opportunities
  • 1.2.4. Discover Financial Services
    • i. Corporate Information
    • ii. Geographical Spread
    • iii. Key Clients & Strategic Partnerships
    • iv. High-level View of Offerings
    • v. Juniper Research's View: Key Strengths & Strategic Development Opportunities
  • 1.2.5. Entrust
    • i. Corporate Information
    • ii. Geographical Spread
    • iii. Key Clients & Strategic Partnerships
    • iv. High-level View of Offerings
    • v. Juniper Research's View: Key Strengths & Strategic Development Opportunities
  • 1.2.6. Feedzai
    • i. Corporate Information
    • ii. Geographical Spread
    • iii. Key Clients & Strategic Partnerships
    • iv. High-level View of Offerings
    • v. Juniper Research's View: Key Strengths & Strategic Development Opportunities
  • 1.2.7. Fiserv
    • i. Corporate Information
    • ii. Geographical Spread
    • iii. Key Clients & Strategic Partnerships
    • iv. High-level View of Offerings
    • v. Juniper Research's View: Key Strengths & Strategic Development Opportunities
  • 1.2.8. Hawk
    • i. Corporate Information
    • ii. Geographical Spread
    • iii. Key Clients & Strategic Partnerships
    • iv. High-level View of Offerings
    • v. Juniper Research's View: Key Strengths & Strategic Development Opportunities
  • 1.2.9. LexisNexis Risk Solutions
    • i. Corporate Information
    • ii. Geographical Spread
    • iii. Key Clients & Strategic Partnerships
    • iv. High-level View of Offerings
    • v. Juniper Research's View: Key Strengths & Strategic Development Opportunities
  • 1.2.10. Mastercard
    • i. Corporate Information
    • ii. Geographical Spread
    • iii. Key Clients & Strategic Partnerships
    • iv. High-level View of Offerings
    • v. Juniper Research's View: Key Strengths & Strategic Development Opportunities
  • 1.2.11. SEON
    • i. Corporate Information
    • ii. Geographical Spread
    • iii. Key Clients & Strategic Partnerships
    • iv. High-level View of Offerings
    • v. Juniper Research's View: Key Strengths & Strategic Development Opportunities
  • 1.2.12. Thales
    • i. Corporate Information
    • ii. Geographical Spread
    • iii. Key Clients & Strategic Partnerships
    • iv. High-level View of Offerings
    • v. Juniper Research's View: Key Strengths & Strategic Development Opportunities
  • 1.2.13. Tookitaki
    • i. Corporate Information
    • ii. Geographical Spread
    • iii. Key Clients & Strategic Partnerships
    • iv. High-level View of Offerings
    • v. Juniper Research's View: Key Strengths & Strategic Development Opportunities
  • 1.2.14. TransUnion
    • i. Corporate Information
    • ii. Geographical Spread
    • iii. Key Clients & Strategic Partnerships
    • iv. High-level View of Offerings
    • v. Juniper Research's View: Key Strengths & Strategic Development Opportunities
  • 1.2.15. Visa
    • i. Corporate Information
    • ii. Geographical Spread
    • iii. Key Clients & Strategic Partnerships
    • iv. High-level View of Offerings
    • v. Juniper Research's View: Key Strengths & Strategic Development Opportunities

Data & Forecasting

1. Market Overview

• 1.1. Introduction
• 1.2. Definitions and Scope
  • 1.2.1. Forecast Introduction
  • 1.2.2. Methodology & Assumptions
    • i. Methodology
    • ii. Assumptions
      • Figure 1.1: Fraud Detection & Prevention in Banking Market 2025-2030: Forecast Methodology

2. Forecast Summary

• 2.1. Issuer Fraud Prevention Forecast Summary
  • 2.1.1. Number of Banks and Other Financial Institutions Using Fraud Detection & Prevention Solutions
    • Figure & Table 2.1: Number of Banks & FIs Using FDP Solutions, Split by 8 Key Regions, 2025-2030
  • 2.1.2. Total Annual Spend on Fraud Detection & Prevention Solutions by Banks & FIs
    • Figure & Table 2.2: Total Annual Spend on FDP Solutions by Banks & FIs ($m), Split by 8 Key Regions, 2025-2030
  • 2.1.3. Total Number of Fraudulent Transactions across Digital Banking and Money Transfers
    • Figure & Table 2.3: Total Number of Fraudulent Transactions across Digital Banking and Money Transfer (m), Split by 8 Key Regions, 2025-2030
  • 2.1.4. Total Value of Fraudulent Transactions across Banking and Money Transfers
    • Figure & Table 2.4: Total Value of Fraudulent Banking & Money Transfer Transactions ($m), Split by 8 Key Regions, 2025-2030

3. Banks and Other Financial Institutions

• 3.1.1. Number of Banks and Credit Unions Using Fraud Detection & Prevention Solutions
  • Figure & Table 3.1: Banks & Credit Unions Using FDP Solutions, Split by 8 Key Regions, 2025-2030
• 3.1.2. Total Spend by Banks & Credit Unions on Fraud Detection & Prevention Solutions
  • Figure & Table 3.2: Total Spend by Banks & Credit Unions on FDP Solutions ($m), Split by 8 Key Regions, 2025-2030

4. Fintechs

• 4.1.1. Number of Fintechs Using Fraud Detection & Prevention Solutions
  • Figure & Table 4.1: Number of Fintechs Using FDP Solutions, Split by 8 Key Regions, 2025-2030
• 4.1.2. Total Spend by Fintechs on Fraud Detection & Prevention Solutions
  • Figure & Table 4.2: Total Spend by Fintechs on FDP Solutions ($m), Split by 8 Key Regions, 2025-2030

5. Investment Companies

• 5.1.1. Number of Investment Companies Using Fraud Detection & Prevention Solutions
  • Figure & Table 5.1: Number of Investment Companies Using FDP Solutions, Split by 8 Key Regions, 2025-2030
• 5.1.2. Total Spend by Investment Companies on Fraud Detection & Prevention Solutions
  • Figure & Table 5.2: Total FDP Spend by Investment Companies ($m), Split by 8 Key Regions, 2025-2030

6. Lenders

• 6.1.1. Number of Lenders Using Fraud Detection & Prevention Solutions
  • Figure & Table 6.1: Number of Lenders Using FDP Solutions, Split by 8 Key Regions, 2025-2030
• 6.1.2. Total Spend by Lenders on Fraud Detection & Prevention Solutions
  • Figure & Table 6.2: Total Spend by Lenders on FDP Solutions ($m), Split by 8 Key Regions, 2025-2030

7. Fraudulent Transactions in Banking and Money Transfers

• 7.1.1. Total Number of Fraudulent Transactions in Digital Banking
  • Figure & Table 7.1: Total Number of Fraudulent Transactions in Digital Banking (m), Split by 8 Key Regions, 2025-2030
• 7.1.2. Total Value of Fraudulent Transactions in Digital Banking
  • Figure & Table 7.2: Total Value of Fraudulent Transactions in Digital Banking ($m), Split by 8 Key Regions, 2025-2030
• 7.1.3. Total Number of Fraudulent Transactions in Money Transfer
  • Figure & Table 7.3: Total Number of Fraudulent Transactions in Money Transfer (m), Split by 8 Key Regions, 2025-2030
• 7.1.4. Total Fraudulent Transactions Value in Money Transfer
  • Figure & Table 7.4: Total Fraudulent Transactions Value ($m), Split by 8 Key Regions, 2025-2030