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银行诈欺侦测与预防全球市场：2024-2029
市场调查报告书
商品编码
1494937

银行诈欺侦测与预防全球市场：2024-2029

Global Fraud Detection & Prevention in Banking Market: 2024-2029
出版日期: | 出版商: Juniper Research Ltd | 英文 | 商品交期: 最快1-2个工作天内

价格
简介目录
关键统计
诈欺侦测与预防解决方案支出金额（2024年）： 173亿元
诈欺侦测与预防解决方案支出金额（2029年）： 322亿元
市场成长率（2024-2029） 86%
存款期限： 2024-2029

本报告提供银行业诈欺侦测和预防市场研究、不断演变的诈欺情况详细审查和分析、法律体系、诈欺侦测和预防利用技术和解决方案、市场成长促进因素和问题、非法交易金额、金额造成的损失、每年各类金融设备诈欺侦察和防范解决方案的支出、各地区的详细分析以及主要供应商消除竞争的措施等。

模型视图

市场材料/预测报告

Juniper Research的市场资料和预测报告，除了透过数字了解现状之外，详细解释了方法和原因。

市场趋势与策略报告

对当前市场情势的综合分析和策略建议。

市场资料与预测报告

  • 与诈欺侦测和预防解决方案相关的多家银行和金融机构
  • 用于银行诈欺侦测和预防的支出金额
  • 非法交易金额

次要指标，由各主要市场提供如下：

  • 银行和金融机构
  • 信用合作公司
  • 贷方
  • 投资公司

目次

市场趋势/策略

第1章 要点与策略建议

  • 要点
  • 策略建议

第2章 市场状况

  • 定义范围
  • 诈欺类型
    • 第一方欺诈
    • 洗钱
    • 退款欺诈
    • ATO
    • 合成 ID
  • 侦测并防止犯罪者诈欺的解决方法
    • 诈欺侦测/预防系统
      • 生物鑑定
      • 代币化
      • 行动分析
      • AML 软体

第3章 新诈欺市场

  • 主要主题相关领域
  • 主要趋势与直接驱动市场因素
  • 付款方式
    • 开放银行
    • BNPL
    • CBDC
    • 加密货币
    • 即时支付
    • 汇款
  • 技术
    • 人工智慧
    • ML
    • API
  • 规则
    • 英国快速支付规定
    • PSD2
    • RTS 对支付服务提供者的影响

第4章 细分市场分析

  • 介绍
    • 银行和信用合作社
    • 金融科技
    • 贷方
      • 减少诈欺损失
      • 加强风险管理
      • 提高贷款组合的品质
      • 保持信用和声誉
    • 投资公司
  • 主要问题

竞争排除政策

第1章 Juniper Research 竞争排行榜

第2章 公司简介

  • 发行人反诈骗供应商简介
    • Accertify
    • ACI Worldwide
    • ComplyAdvantage
    • Discover
    • Feauturespace
    • Feedzai
    • Fiserv
    • Fraudio
    • GBG
    • LexisNexis Risk Solution
    • Mastercard
    • SEON
    • Thales
    • TransUnion
    • Visa
    • Juniper Research排行榜评估方法
  • 限制和解释

材料/预测

第1章 市场概述

  • 定义/范围

第2章 方法假设总结

  • 预测概述
  • 研究方法/前提

第3章 预测概述

  • 发行者预防诈欺预测：摘要
    • 使用诈欺侦测和预防解决方案的银行和其他金融机构的数量
    • 诈欺检测和预防解决方案的年度总支出
    • 银行和汇款诈欺交易总数
    • 银行和汇款诈欺交易总数

第4章 银行及其他金融机构支出

  • 银行和信用合作社用于侦测和预防诈欺的支出
    • 使用诈欺侦测和预防解决方案的银行和信用社数量
    • 银行和信用合作社用于诈欺检测和预防解决方案的总支出
  • 金融科技诈欺侦测与预防支出
    • 使用诈欺侦测和预防解决方案的金融科技公司数量
    • 金融科技诈欺侦测与预防解决方案的总支出
  • 投资公司诈欺检测与预防支出
    • 使用诈欺侦测和预防解决方案的投资公司数量
    • 投资公司在诈欺检测和预防解决方案上的总支出
  • 贷方诈欺检测和预防支出
    • 使用诈欺检测和预防解决方案的贷方数量
    • 贷方在诈欺检测和预防解决方案上的总支出

第5章 银行与汇款中的诈欺交易

  • 数位银行中的诈骗交易
    • 数位银行诈欺交易总数
    • 数位银行诈欺交易总额
  • 汇款诈欺交易率
    • 汇款诈欺交易总数
    • 汇款诈欺交易总额
简介目录
KEY STATISTICS
Spend on fraud detection and prevention solutions in 2024:$17.3 billion
Spend on fraud detection and prevention solutions in 2029:$32.2 billion
2024 to 2029 market growth:86%
Forecast period:2024-2029

Overview

Our "Fraud Detection & Prevention in Banking" research report provides a detailed evaluation and analysis of the evolving fraud landscape when it comes to banking and the financial industry, including the impact of evolving payment types such as instant payments, blockchain and CBDCs (central bank digital currencies). The fraud analytics and prevention techniques study examines other initiatives and fraudulent schemes disrupting the market, such as the changing scope of government regulations and the use of artificial intelligence by both good and bad actors.

The banking fraud detection research also considers future challenges within fraud detection and prevention for banking, such as false positives and emerging trends in the banking sector space, including the increased use of behavioural analysis and transaction monitoring.

In addition, this fraud detection and prevention market report covers fraud risks market segment opportunities; providing a comprehensive approach with strategic insights into the development of advanced methods of fraud detection and prevention capabilities for banks and other financial institutions, in line with new technologies, such as AI and machine learning.

Through advanced analytics, It highlights future opportunities and technologies that are important for fraud detection and prevention vendors, banks and financial institutions to consider when adapting fraud detection and prevention solutions for the future, incorporating advanced fraud detection aspects such as AI and real-time data.

The report positions 15 fraud detection in banking and prevention vendors in the financial services sector across the Juniper Research Competitor Leaderboard; delivering an invaluable resource for stakeholders seeking to understand the competitive landscape in the financial fraud market.

The research suite contains a detailed dataset; providing forecasts for 60 countries across a wide range of different metrics and instances of fraud, including total number of banks, credit unions, lenders and investment companies using types of fraud detection and prevention solutions, total annual spend on fraud detection and prevention solutions, total number of fraudulent transactions in banking and money transfer and total fraudulent transaction value.

Key Features

  • Market Dynamics: A strategic analysis of the major drivers, challenges, and innovations shaping the adoption and development of the fraud detection and prevention in banking industry, including:
  • Key Takeaways & Strategic Recommendations: In-depth analysis of key development opportunities and key findings within the fraud detection and prevention in banking market, accompanied by key strategic recommendations for stakeholders.
  • Benchmark Industry Forecasts: Includes forecasts for the total money transfer for both domestic and international money movement, as well as the total money sent through consumer instant payments. This data is split by our 8 key forecast regions and 60 countries.
  • Juniper Research Competitor Leaderboard: Key player capability and capacity assessment for 15 vendors in the fraud detection and fraud prevention solutions space, via a Juniper Research Competitor Leaderboard.

SAMPLE VIEW

Market Data & Forecasting Report

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

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 over 24,000 datapoints. Metrics in the research suite include:

  • Total number of Banks and Financial Institutions Using Fraud Detection and Prevention Solutions
  • Total Spend on Fraud Detection and Prevention in Banking
  • Total Fraudulent Transaction Value

These metrics are provided for the following key market verticals:

  • Banks and Financial Institutions
  • Credit Unions
  • Lenders
  • Investment Companies

Juniper Research 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 5 interactive scenarios.

Market Trends & Strategies Report

Juniper Research's new report examines the "Fraud Detection and Prevention in Banking" market landscape in detail; assessing current fraud trends and factors shaping the market, such as the growing use and anticipation surrounding different technologies such as AI and ML (Machine Learning), and the existing and impending regulations in the space. The report delivers comprehensive analysis of the strategic opportunities for fraud detection and prevention providers within banking; addressing key verticals, developing challenges, and how stakeholders should navigate these.

Competitor Leaderboard Report

Juniper Research's Competitor Leaderboard provides detailed evaluation and market positioning for 15 leading vendors in the payment fraud detection and prevention space. The vendors are positioned either as established leaders, leading challengers or disruptors and challengers, based on capacity and capability assessments.

The vendors in the Leaderboard include:

  • Accertify
  • ACI Worldwide
  • Comply Advantage
  • Discover
  • Featurespace
  • Feedzai
  • Fiserv
  • Fraudio
  • GBG
  • LexisNexis Risk Solutions
  • Mastercard
  • SEON
  • Thales
  • TransUnion
  • Visa

Backed by a robust and comprehensive scoring methodology, Juniper Research's Competitor Leaderboard allows readers to gain greater insight into leading market players; enabling them to view which companies have the highest market prospects and the strategies being implemented.

Table of Contents

Market Trends & Strategies

1. Key Takeaways & Strategic Recommendations

  • 1.1. Key Takeaways
  • 1.2. Strategic Recommendations

2. Market Landscape

  • 2.1. Introduction
  • 2.2. Definitions and Scope
    • Figure 2.1: Visualisation of Fraud
  • 2.3. Types of Fraud
    • 2.3.1. First-party Fraud
      • i. Application Fraud and Fake Accounts
      • ii. Money Mules
      • iii. Fronting
      • iv. Sleeper Fraud
      • v. APP Fraud
      • vi. Social Engineering
    • 2.3.2. Money Laundering
      • Figure 2.2: Visualisation of Money Laundering
    • 2.3.3. Chargeback Fraud
      • Figure 2.3: Visualisation of Chargeback Fraud
    • 2.3.4. ATO
      • Figure 2.4: Visualisation of Account Takeover
    • 2.3.5. Synthetic Identity
      • Figure 2.5: Visualisation of Synthetic Identity Fraud
      • i. Detection of Synthetic Identity Fraud
  • 2.4. Solutions Utilised in Issuer Fraud Detection & Prevention
    • 2.4.1. Fraud Detection and Prevention Systems
      • Figure 2.6: Types of Fraud Detection and Techniques
      • i. Biometrics
      • ii. Tokenisation
      • iii. Behavioural Analytics
      • iv. AML Software

3. Emerging Fraud Market

  • 3.1. Key Themes and Areas Involved
  • 3.2. Key Trends & Current Market Drivers
  • 3.3. Payment Types
    • 3.3.1. Open Banking
      • i. Increase in Fraud Through Open Banking
        • Figure 3.1: Visualisation of Open Banking
      • ii. Decrease in Fraud Through Open Banking
        • Figure 3.2: Visualisation of Open Banking
    • 3.3.2. BNPL
      • i. Increase in Fraud Through BNPL
        • Figure 3.3: Buy Now Pay Later Flow
      • ii. Decrease in Fraud Through BNPL
    • 3.3.3. CBDCs
      • Figure 3.4: Visualisation of CBDC
      • i. Increase in Fraud Through CBDCs
      • ii. Decrease in Fraud Through CBDCs
      • iii. Mitigating CBDC Fraud
    • 3.3.4. Cryptocurrency
      • i. Increase in Fraud Through Cryptocurrency
      • ii. Mitigating Cryptocurrency Fraud
    • 3.3.5. Real-time Payments
      • Figure 3.5: Visualisation of Instant Payments
      • i. Increase in Fraud Through Real-time Payments
      • ii. Decrease in Fraud Through Real-time Payments
    • 3.3.6. Money Transfer
      • i. Increase in Fraud Through Money Transfer
      • Figure 3.6: Total Number of Fraudulent Money Transfer Transactions (m), Split by 8 Key Regions, 2024-2029
      • ii. Decrease in Fraud Through Money Transfer
  • 3.4. Technologies
    • 3.4.1. AI
      • i. Benefits of AI in Fraud Detection
        • Figure 3.7: Benefits of AI in Fraud Detection
      • ii. How AI Is Being Utilised by Fraudsters
    • 3.4.2. ML
      • i. Benefits of ML in Fraud Detection
      • ii. How ML Is Being Utilised by Fraudsters
    • 3.4.3. APIs
      • i. Benefits of APIs in Fraud Detection
      • ii. How APIs Are Being Utilised by Fraudsters
      • iii. Open Banking APIs
      • iv. FAPI (Financial-grade API)
  • 3.5. Regulations
    • 3.5.1. UK Faster Payments Regulation
    • 3.5.2. PSD2
    • 3.5.3. RTS (Regulatory Technical Standards) Implications for Payment Service Providers
      • i. Fraud Detection
      • ii. Merger of Home Working, Personal Devices and Corporate Access
      • iii. Exemptions from SCA
      • iv. Implications
      • v. Network Tokenisation in India
      • vi. Regulation Differences

4. Segment Analysis

  • 4.1. Introduction
    • 4.1.1. Banks and Credit Unions
      • Figure 4.1: Total Spend on Fraud Detection and Prevention by Banks and Credit Unions ($m), Globally, Split by 8 Key Regions, 2024-2029
    • 4.1.2. Fintechs
      • Figure 4.2: Total Number of Fintechs Using Fraud Detection and Prevention Solutions, 2024-2029
    • 4.1.3. Lenders
      • i. Reducing Exposure to Fraud
      • ii. Enhance Risk Management
      • iii. Improved Quality of Loan Portfolio
      • iv. Protect Trust and Reputation
        • Figure 4.3: Total Spend on Fraud Detection and Prevention by Lenders Globally ($m), Split by 8 Key Regions, 2024-2029
    • 4.1.4. Investment Companies
      • Figure 4.4: Total Spend on Fraud Detection and Prevention from Investment Companies ($m), Split by 8 Key Regions, 2024-2029
  • 4.2. Key Challenges

Competitor Leaderboard

1. Juniper Research Competitor Leaderboard

  • 1.1. Why Read This Report
    • Table 1.1: Juniper Research Competitor Leaderboard Vendors: Fraud Detection & Prevention in Banking
    • Figure 1.2: Juniper Research Competitor Leaderboard - Fraud Detection & Prevention in Banking
    • Table 1.3: Juniper Research Competitor Leaderboard: Fraud Detection & Prevention in Banking Vendor Ranking
    • Table 1.4: Juniper Research Competitor Leaderboard Fraud Detection & Prevention in Banking - Heatmap

2. Company Profiles

  • 2.1. Issuer Fraud Prevention Vendor Profiles
    • 2.1.1. Accertify
      • i. Corporate Information
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High-level View of Offering
        • Figure 2.1: Accertify Financial Institution Fraud Prevention Solution
      • v. Juniper Research's View: Key Strengths & Strategic Opportunities
    • 2.1.2. ACI Worldwide
      • i. Corporate
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High-level View of Offering
      • v. Juniper Research's View: Key Strengths & Strategic Opportunities
    • 2.1.3. ComplyAdvantage
      • i. Corporate Information
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High-level View of Offering
      • v. Juniper Research's View: Key Strengths & Strategic Opportunities
    • 2.1.4. Discover
      • i. Corporate Information
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High-level View of Offering
      • v. Juniper Research's View: Key Strengths & Strategic Opportunities
    • 2.1.5. Feauturespace
      • i. Corporate Information
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High-level View of Offering
      • v. Juniper Research's View: Key Strengths & Strategic Opportunities
    • 2.1.6. Feedzai
      • i. Corporate Information
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High-level View of Offering
      • v. Juniper Research's View: Key Strengths & Strategic Opportunities
    • 2.1.7. Fiserv
      • i. Corporate Information
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High-level View of Offering
      • v. Juniper Research's View: Key Strengths & Strategic Opportunities
    • 2.1.8. Fraudio
      • i. Corporate Information
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High-level View of Offering
      • v. Juniper Research's View: Key Strengths & Strategic Opportunities
    • 2.1.9. GBG
      • i. Corporate Information
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High-level View of Offering
      • v. Juniper Research's View: Key Strengths & Strategic Opportunities
    • 2.1.10. LexisNexis Risk Solution
      • i. Corporate Information
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High-level View of Offering
      • v. Juniper Research's View: Key Strengths & Strategic Opportunities
    • 2.1.11. Mastercard
      • i. Corporate Information
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High-level View of Offering
      • v. Juniper Research's View: Key Strengths & Strategic Opportunities
    • 2.1.12. SEON
      • i. Corporate Information
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High-level View of Offering
      • v. Juniper Research's View: Key Strengths & Strategic Opportunities
    • 2.1.13. Thales
      • i. Corporate
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High-level View of Offering
      • v. Juniper Research's View: Key Strengths & Strategic Opportunities
    • 2.1.14. TransUnion
      • i. Corporate
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High-level View of Offering
      • v. Juniper Research's View: Key Strengths & Strategic Opportunities
    • 2.1.15. Visa
      • i. Corporate
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High-level View of Offering
      • v. Juniper Research's View: Key Strengths & Strategic Opportunities
  • 2.2. Juniper Research Leaderboard Assessment Methodology
    • 2.2.1. Limitations & Interpretations
      • Table 2.4: Juniper Research Fraud Detection & Prevention in Banking Assessment Criteria

Data & Forecasting

1. Market Overview

  • 1.1. Introduction
  • 1.2. Definitions and Scope
    • Figure 1.1: Visualisation of Fraud

2. Methodology Assumptions and Summary

  • 2.1. Forecast Introduction
  • 2.2. Methodology & Assumptions
    • Figure 2.1: Spend on Fraud Detection & Prevention Methodology
    • Figure 2.2: Fraudulent Transaction Value Forecast

3. Forecast Summary

  • 3.1. Issuer Fraud Prevention Forecast Summary
    • 3.1.1. Number of Bank and Other Financial Institutions Using Fraud Detection & Prevention Solutions
      • Figure & Table 3.1: Total Number of Banks and Financial Institutions Using Fraud Detection & Prevention Solutions (m), Split by 8 Key Regions, 2024-2029
    • 3.1.2. Total Annual Spend on Fraud Detection & Prevention Solutions
      • Figure & Table 3.2: Total Spend on Fraud Detection & prevention Solutions by Banks and Other Financial Institutions ($m), Split by 8 Key Regions, 2024-2029
      • Table 3.3: Total Spend from Banks and Credit Unions Using Fraud Detection & Prevention Solutions ($m), Split by Company Vertical, 2024-2029
    • 3.1.3. Total Number of Fraudulent Transactions across Banking and Money Transfer
      • Figure & Table 3.4: Total Number of Fraudulent Transactions across Banking and Money Transfer (m), Split by 8 Key Regions 2024-2029
    • 3.1.4. Total Value of Fraudulent Transactions across Banking and Money Transfer
      • Figure & Table 3.5: Total Value of Fraudulent Transactions across Digital Banking and Money Transfer ($m), Split by 8 Key Regions, 2024-2029

4. Banks and Other Financial Institutions Spend

  • 4.1. Banks and Credit Unions Fraud Detection & Prevention Spend
    • 4.1.1. Number of Banks and Credit Unions Using Fraud Detection & Prevention Solutions
      • Figure & Table 4.1: Total Number of Banks and Credit Unions Using Fraud Detection & Prevention Solutions (m), Split by 8 Key Regions, 2024-2029
    • 4.1.2. Total Spend by Banks and Credit Unions on Fraud Detection & Prevention Solutions
      • Figure & Table 4.2: Total Spend from Banks and Credit Unions Using Fraud Detection & Prevention Solutions ($m), Split by 8 Key Regions 2024-2029
  • 4.2. Fintechs Fraud Detection & prevention Spend
    • 4.2.1. Number of Fintechs Using Fraud Detection & Prevention Solutions
      • Figure & Table 4.3: Total Number of Fintechs Using Fraud Detection & Prevention Solutions (m), Split by 8 Key Regions, 2024-2029
    • 4.2.2. Total Spend by Fintechs on Fraud Detection & Prevention Solutions
      • Figure & Table 4.4: Total Spend from Fintechs Using Fraud Detection & Prevention Solutions ($m), Split by 8 Key Regions 2024-2029
  • 4.3. Investment Companies Fraud Detection & prevention Spend
    • 4.3.1. Number of Investment Companies Using Fraud Detection & Prevention Solutions
      • Figure & Table 4.5: Total Number of Investment Companies Using Fraud Detection & Prevention Solutions (m), Split by 8 Key Regions, 2024-2029
    • 4.3.2. Total Spend by Investment Companies on Fraud Detection & Prevention Solutions
      • Figure & Table 4.6: Total Spend from Investment Companies Using Fraud Detection & Prevention Solutions ($m), Split by 8 Key Regions, 2024-2029
  • 4.4. Lenders Fraud Detection & prevention Spend
    • 4.4.1. Number of Lenders Using Fraud Detection & Prevention Solutions
      • Figure & Table 4.7: Total Number of Lenders Using Fraud Detection & Prevention Solutions (m), Split by 8 Key Regions, 2024-2029
    • 4.4.2. Total Spend by Lenders on Fraud Detection & Prevention Solutions
      • Figure & Table 4.8: Total Spend from Lenders Using Fraud Detection & Prevention Solutions ($m), Split by 8 Key Regions, 2024-2029

5. Fraudulent Transactions in Banking and Money Transfer

  • 5.1. Fraudulent Transactions in Digital Banking
    • 5.1.1. Total Number of Fraudulent Transactions in Digital Banking
      • Figure & Table 5.1: Total Number of Fraudulent Transactions within Digital Banking (m), Split by 8 Key Regions, 2024-2029
    • 5.1.2. Total Fraudulent Transaction Values in Digital Banking
      • Figure & Table 5.2: Total Fraudulent Transaction Values in Digital Banking ($m), Split by 8 Key Regions, 2024-2029
  • 5.2. Fraudulent Transaction Rates in Money Transfer
    • 5.2.1. Total Number of Fraudulent Transactions in Money Transfer
      • Figure & Table 5.3: Total Number of Fraudulent Transactions within Money Transfer (m), Split by 8 Key Regions, 2024-2029
    • 5.2.2. Total Fraudulent Transaction Values in Money Transfer
      • Figure & Table 5.4: Total Fraudulent Transaction Values in Money Transfer ($m), Split by 8 Key Regions, 2024-2029