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시장보고서
상품코드
1872026

Ecommerce 부정 방지 소프트웨어 : 세계 시장 점유율과 순위, 총판매량 및 수요 예측(2025-2031년)

Ecommerce Fraud Prevention Software - Global Market Share and Ranking, Overall Sales and Demand Forecast 2025-2031
발행일: | 리서치사: QYResearch | 페이지 정보: 영문 | 배송안내 : 2-3일 (영업일 기준)

    
    
    




■ 보고서에 따라 최신 정보로 업데이트하여 보내드립니다. 배송일정은 문의해 주시기 바랍니다.

세계의 Ecommerce 부정 방지 소프트웨어 시장 규모는 2024년에 47억 6,800만 달러로 추정되며, 2025-2031년의 예측 기간에 CAGR 11.2%로 성장하며, 2031년까지 99억 1,500만 달러로 확대할 것으로 예측되고 있습니다.

E-Commerce 사기 방지 소프트웨어는 온라인 거래에서 사기 행위를 식별, 방지 및 완화하기 위해 특별히 고안된 기술 툴입니다. 인공지능(AI), 머신러닝(ML), 행동분석 등의 기술을 활용하여 사용자 행동, 거래 데이터, 디바이스 정보를 실시간으로 모니터링하여 이상 패턴을 감지하고 의심스러운 거래를 차단합니다. 본 소프트웨어는 신용카드 사기, 계정 탈취, 부정환불, 허위 반품, 가명 등록 등 다양한 부정행위를 방지할 수 있습니다. 일반적으로 E-Commerce 플랫폼, 결제 게이트웨이, 고객 관리 시스템에 통합되어 기업의 재무 손실 감소, 지불 거절률 감소, 고객 데이터 보호, 사용자 신뢰도 향상을 돕습니다.

초기 단계의 급속한 확장을 거쳐 E-Commerce 부정방지 소프트웨어 시장은 구조적 심화와 기술 진화를 특징으로 하는 새로운 단계에 접어들었습니다. 성장률은 둔화되고 있지만, 시장은 여전히 안정적인 성장세를 유지하고 있으며, 특히 AI 기반 행동 인식, 계정 보안, 반품 주문 관리 분야에서 두드러집니다. 중소기업 수요 증가와 세계 컴플라이언스에 대한 압박이 증가함에 따라 기업은 더욱 정교하고 복잡한 예방 및 관리 시스템을 도입해야 하는 상황에 직면해 있습니다. 현재 시장에서는 클라우드 기반 구축이 주류를 이루고 있으며, 다양한 분야에서 활용되고 있습니다. 북미는 여전히 중요한 지역이지만, 유럽과 아시아태평양이 점차 부상하고 있으며, 지역적 분포 패턴이 다양해지고 있습니다. 동시에 Visa, Riskified, Ethoca, Signifyd 등의 기업이 비교적 집중된 경쟁 구도를 형성하고 있습니다. 기술 및 비즈니스 수요에 힘입어 시장 전체는 장기적인 발전 가능성이 매우 높을 것으로 예측됩니다.

E-Commerce용 부정행위 방지 소프트웨어 시장은 AI와 머신러닝을 핵심 기술로 삼아 새로운 부정행위에 대한 대응 능력을 지속적으로 향상시키는 등 기술 주도적 특성이 두드러집니다. SaaS 도입 방식이 확산됨에 따라 중소규모의 E-Commerce 기업이 경량화 솔루션을 채택하는 경향이 강해지면서 시장 수요 증가에 힘을 실어주고 있습니다. GDPR(EU 개인정보보호규정), PCI-DSS와 같은 규제 강화 환경은 기업의 데이터 보안 및 거래 모니터링에 대한 투자를 가속화하고 있습니다. 동시에, 부정 행위는 전통적 절도 행위에서 보다 복잡한 계정 탈취 및 소셜 엔지니어링 공격으로 진화하고 있으며, 소프트웨어 플랫폼은 다차원적인 행동 분석으로 진화해야 합니다. 향후 행동 생체인식, 자동 지불 거절 처리, 크로스 플랫폼 리스크 통합이 업계 혁신의 초점이 될 것입니다.

이 보고서는 세계의 E-Commerce 사기 방지 소프트웨어 시장에 대해 총매출액, 주요 기업의 시장 점유율 및 순위를 중심으로 지역별, 국가별, 유형별, 용도별 분석을 종합적으로 제시하는 것을 목적으로 합니다.

E-Commerce 부정방지 소프트웨어 시장 규모 추정 및 예측은 매출액 기준으로 제시되며, 2024년을 기준 연도로 하여 2020-2031년의 과거 데이터와 예측 데이터를 포함합니다. 정량적, 정성적 분석을 통해 독자들이 비즈니스/성장 전략 수립, 시장 경쟁 평가, 현재 시장에서의 포지셔닝 분석, E-Commerce 사기방지 소프트웨어에 대한 정보에 입각한 비즈니스 의사결정을 내릴 수 있도록 돕습니다.

시장 세분화

기업별

  • Stripe
  • Riskified
  • Sift
  • Ethoca(Mastercard)
  • Signifyd
  • NoFraud
  • Forter
  • Subuno
  • TransUnion
  • SEON
  • Shield
  • ACI Worldwide
  • Kount(Equifax)
  • PayPal
  • Visa
  • Razorpay
  • Bolt
  • DataDome
  • Ping Identity
  • ClearSale
  • Fingerprint
  • Arkose Labs

유형별 부문

  • 클라우드 기반
  • 온프레미스

용도별 부문

  • 중소기업
  • 대기업

지역별

  • 북미
    • 미국
    • 캐나다
  • 아시아태평양
    • 중국
    • 일본
    • 한국
    • 동남아시아
    • 인도
    • 호주
    • 기타 아시아태평양
  • 유럽
    • 독일
    • 프랑스
    • 영국
    • 이탈리아
    • 네덜란드
    • 북유럽 국가
    • 기타 유럽
  • 라틴아메리카
    • 멕시코
    • 브라질
    • 기타 라틴아메리카
  • 중동 및 아프리카
    • 튀르키예
    • 사우디아라비아
    • 아랍에미리트
    • 기타 중동 및 아프리카
KSA

The global market for Ecommerce Fraud Prevention Software was estimated to be worth US$ 4768 million in 2024 and is forecast to a readjusted size of US$ 9915 million by 2031 with a CAGR of 11.2% during the forecast period 2025-2031.

E-commerce anti-fraud software is a type of technical tool specifically designed to identify, prevent and mitigate fraud in online transactions. It uses technologies such as artificial intelligence (AI), machine learning (ML) and behavioral analysis to identify abnormal patterns and block suspicious transactions by monitoring user behavior, transaction data and device information in real time. The software can prevent a variety of frauds such as credit card fraud, account takeover, false refunds, false returns, false identity registration, etc. It is usually integrated into e-commerce platforms, payment gateways or customer management systems to help companies reduce financial losses, reduce chargeback rates, protect customer data and enhance user trust.

After experiencing rapid expansion in the early stage, the e-commerce anti-fraud software market is entering a new stage characterized by structural deepening and technological evolution. Although the growth rate has slowed down, the market still maintains a steady growth trend, especially in the fields of AI-driven behavior recognition, account security, and return order management. The rising demand of small and medium-sized enterprises, coupled with the strengthening of global compliance pressure, has prompted enterprises to deploy smarter and more complex prevention and control systems. The current market is mainly cloud-based deployment, with a wide range of applications. North America is still an important region, but Europe and Asia-Pacific are gradually rising, and the regional pattern is becoming more diversified. At the same time, companies such as Visa, Riskified, Ethoca, and Signifyd constitute a relatively concentrated competitive landscape. Driven by both technology and business needs, the overall market has strong long-term development potential.

The e-commerce anti-fraud software market has a strong technology-driven feature, with AI and machine learning as the core support, continuously improving recognition efficiency to deal with new fraudulent behaviors. With the popularization of SaaS deployment methods, small and medium-sized e-commerce companies are increasingly embracing lightweight solutions, driving the continued expansion of market demand. In an environment of stricter regulation, compliance requirements such as GDPR and PCI-DSS have also accelerated companies' investment in data security and transaction monitoring. At the same time, fraud has evolved from traditional theft to more complex account takeovers and social engineering attacks, prompting software platforms to evolve towards multi-dimensional behavioral analysis. In the future, behavioral biometrics, automated chargeback processing, and cross-platform risk integration will become the focus of industry innovation.

This report aims to provide a comprehensive presentation of the global market for Ecommerce Fraud Prevention Software, focusing on the total sales revenue, key companies market share and ranking, together with an analysis of Ecommerce Fraud Prevention Software by region & country, by Type, and by Application.

The Ecommerce Fraud Prevention Software market size, estimations, and forecasts are provided in terms of sales revenue ($ millions), considering 2024 as the base year, with history and forecast data for the period from 2020 to 2031. With both quantitative and qualitative analysis, to help readers develop business/growth strategies, assess the market competitive situation, analyze their position in the current marketplace, and make informed business decisions regarding Ecommerce Fraud Prevention Software.

Market Segmentation

By Company

  • Stripe
  • Riskified
  • Sift
  • Ethoca (Mastercard)
  • Signifyd
  • NoFraud
  • Forter
  • Subuno
  • TransUnion
  • SEON
  • Shield
  • ACI Worldwide
  • Kount (Equifax)
  • PayPal
  • Visa
  • Razorpay
  • Bolt
  • DataDome
  • Ping Identity
  • ClearSale
  • Fingerprint
  • Arkose Labs

Segment by Type

  • Cloud-Based
  • On-Premise

Segment by Application

  • SMES
  • Large Enterprise

By Region

  • North America
    • United States
    • Canada
  • Asia-Pacific
    • China
    • Japan
    • South Korea
    • Southeast Asia
    • India
    • Australia
    • Rest of Asia-Pacific
  • Europe
    • Germany
    • France
    • U.K.
    • Italy
    • Netherlands
    • Nordic Countries
    • Rest of Europe
  • Latin America
    • Mexico
    • Brazil
    • Rest of Latin America
  • Middle East & Africa
    • Turkey
    • Saudi Arabia
    • UAE
    • Rest of MEA

Chapter Outline

Chapter 1: Introduces the report scope of the report, global total market size. This chapter also provides the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by manufacturers in the industry, and the analysis of relevant policies in the industry.

Chapter 2: Detailed analysis of Ecommerce Fraud Prevention Software company competitive landscape, revenue market share, latest development plan, merger, and acquisition information, etc.

Chapter 3: Provides the analysis of various market segments by Type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.

Chapter 4: Provides the analysis of various market segments by Application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.

Chapter 5: Revenue of Ecommerce Fraud Prevention Software in regional level. It provides a quantitative analysis of the market size and development potential of each region and introduces the market development, future development prospects, market space, and market size of each country in the world.

Chapter 6: Revenue of Ecommerce Fraud Prevention Software in country level. It provides sigmate data by Type, and by Application for each country/region.

Chapter 7: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product revenue, gross margin, product introduction, recent development, etc.

Chapter 8: Analysis of industrial chain, including the upstream and downstream of the industry.

Chapter 9: Conclusion.

Table of Contents

1 Market Overview

  • 1.1 Ecommerce Fraud Prevention Software Product Introduction
  • 1.2 Global Ecommerce Fraud Prevention Software Market Size Forecast (2020-2031)
  • 1.3 Ecommerce Fraud Prevention Software Market Trends & Drivers
    • 1.3.1 Ecommerce Fraud Prevention Software Industry Trends
    • 1.3.2 Ecommerce Fraud Prevention Software Market Drivers & Opportunity
    • 1.3.3 Ecommerce Fraud Prevention Software Market Challenges
    • 1.3.4 Ecommerce Fraud Prevention Software Market Restraints
  • 1.4 Assumptions and Limitations
  • 1.5 Study Objectives
  • 1.6 Years Considered

2 Competitive Analysis by Company

  • 2.1 Global Ecommerce Fraud Prevention Software Players Revenue Ranking (2024)
  • 2.2 Global Ecommerce Fraud Prevention Software Revenue by Company (2020-2025)
  • 2.3 Key Companies Ecommerce Fraud Prevention Software Manufacturing Base Distribution and Headquarters
  • 2.4 Key Companies Ecommerce Fraud Prevention Software Product Offered
  • 2.5 Key Companies Time to Begin Mass Production of Ecommerce Fraud Prevention Software
  • 2.6 Ecommerce Fraud Prevention Software Market Competitive Analysis
    • 2.6.1 Ecommerce Fraud Prevention Software Market Concentration Rate (2020-2025)
    • 2.6.2 Global 5 and 10 Largest Companies by Ecommerce Fraud Prevention Software Revenue in 2024
    • 2.6.3 Global Top Companies by Company Type (Tier 1, Tier 2, and Tier 3) & (based on the Revenue in Ecommerce Fraud Prevention Software as of 2024)
  • 2.7 Mergers & Acquisitions, Expansion

3 Segmentation by Type

  • 3.1 Introduction by Type
    • 3.1.1 Cloud-Based
    • 3.1.2 On-Premise
  • 3.2 Global Ecommerce Fraud Prevention Software Sales Value by Type
    • 3.2.1 Global Ecommerce Fraud Prevention Software Sales Value by Type (2020 VS 2024 VS 2031)
    • 3.2.2 Global Ecommerce Fraud Prevention Software Sales Value, by Type (2020-2031)
    • 3.2.3 Global Ecommerce Fraud Prevention Software Sales Value, by Type (%) (2020-2031)

4 Segmentation by Application

  • 4.1 Introduction by Application
    • 4.1.1 SMES
    • 4.1.2 Large Enterprise
  • 4.2 Global Ecommerce Fraud Prevention Software Sales Value by Application
    • 4.2.1 Global Ecommerce Fraud Prevention Software Sales Value by Application (2020 VS 2024 VS 2031)
    • 4.2.2 Global Ecommerce Fraud Prevention Software Sales Value, by Application (2020-2031)
    • 4.2.3 Global Ecommerce Fraud Prevention Software Sales Value, by Application (%) (2020-2031)

5 Segmentation by Region

  • 5.1 Global Ecommerce Fraud Prevention Software Sales Value by Region
    • 5.1.1 Global Ecommerce Fraud Prevention Software Sales Value by Region: 2020 VS 2024 VS 2031
    • 5.1.2 Global Ecommerce Fraud Prevention Software Sales Value by Region (2020-2025)
    • 5.1.3 Global Ecommerce Fraud Prevention Software Sales Value by Region (2026-2031)
    • 5.1.4 Global Ecommerce Fraud Prevention Software Sales Value by Region (%), (2020-2031)
  • 5.2 North America
    • 5.2.1 North America Ecommerce Fraud Prevention Software Sales Value, 2020-2031
    • 5.2.2 North America Ecommerce Fraud Prevention Software Sales Value by Country (%), 2024 VS 2031
  • 5.3 Europe
    • 5.3.1 Europe Ecommerce Fraud Prevention Software Sales Value, 2020-2031
    • 5.3.2 Europe Ecommerce Fraud Prevention Software Sales Value by Country (%), 2024 VS 2031
  • 5.4 Asia Pacific
    • 5.4.1 Asia Pacific Ecommerce Fraud Prevention Software Sales Value, 2020-2031
    • 5.4.2 Asia Pacific Ecommerce Fraud Prevention Software Sales Value by Region (%), 2024 VS 2031
  • 5.5 South America
    • 5.5.1 South America Ecommerce Fraud Prevention Software Sales Value, 2020-2031
    • 5.5.2 South America Ecommerce Fraud Prevention Software Sales Value by Country (%), 2024 VS 2031
  • 5.6 Middle East & Africa
    • 5.6.1 Middle East & Africa Ecommerce Fraud Prevention Software Sales Value, 2020-2031
    • 5.6.2 Middle East & Africa Ecommerce Fraud Prevention Software Sales Value by Country (%), 2024 VS 2031

6 Segmentation by Key Countries/Regions

  • 6.1 Key Countries/Regions Ecommerce Fraud Prevention Software Sales Value Growth Trends, 2020 VS 2024 VS 2031
  • 6.2 Key Countries/Regions Ecommerce Fraud Prevention Software Sales Value, 2020-2031
  • 6.3 United States
    • 6.3.1 United States Ecommerce Fraud Prevention Software Sales Value, 2020-2031
    • 6.3.2 United States Ecommerce Fraud Prevention Software Sales Value by Type (%), 2024 VS 2031
    • 6.3.3 United States Ecommerce Fraud Prevention Software Sales Value by Application, 2024 VS 2031
  • 6.4 Europe
    • 6.4.1 Europe Ecommerce Fraud Prevention Software Sales Value, 2020-2031
    • 6.4.2 Europe Ecommerce Fraud Prevention Software Sales Value by Type (%), 2024 VS 2031
    • 6.4.3 Europe Ecommerce Fraud Prevention Software Sales Value by Application, 2024 VS 2031
  • 6.5 China
    • 6.5.1 China Ecommerce Fraud Prevention Software Sales Value, 2020-2031
    • 6.5.2 China Ecommerce Fraud Prevention Software Sales Value by Type (%), 2024 VS 2031
    • 6.5.3 China Ecommerce Fraud Prevention Software Sales Value by Application, 2024 VS 2031
  • 6.6 Japan
    • 6.6.1 Japan Ecommerce Fraud Prevention Software Sales Value, 2020-2031
    • 6.6.2 Japan Ecommerce Fraud Prevention Software Sales Value by Type (%), 2024 VS 2031
    • 6.6.3 Japan Ecommerce Fraud Prevention Software Sales Value by Application, 2024 VS 2031
  • 6.7 South Korea
    • 6.7.1 South Korea Ecommerce Fraud Prevention Software Sales Value, 2020-2031
    • 6.7.2 South Korea Ecommerce Fraud Prevention Software Sales Value by Type (%), 2024 VS 2031
    • 6.7.3 South Korea Ecommerce Fraud Prevention Software Sales Value by Application, 2024 VS 2031
  • 6.8 Southeast Asia
    • 6.8.1 Southeast Asia Ecommerce Fraud Prevention Software Sales Value, 2020-2031
    • 6.8.2 Southeast Asia Ecommerce Fraud Prevention Software Sales Value by Type (%), 2024 VS 2031
    • 6.8.3 Southeast Asia Ecommerce Fraud Prevention Software Sales Value by Application, 2024 VS 2031
  • 6.9 India
    • 6.9.1 India Ecommerce Fraud Prevention Software Sales Value, 2020-2031
    • 6.9.2 India Ecommerce Fraud Prevention Software Sales Value by Type (%), 2024 VS 2031
    • 6.9.3 India Ecommerce Fraud Prevention Software Sales Value by Application, 2024 VS 2031

7 Company Profiles

  • 7.1 Stripe
    • 7.1.1 Stripe Profile
    • 7.1.2 Stripe Main Business
    • 7.1.3 Stripe Ecommerce Fraud Prevention Software Products, Services and Solutions
    • 7.1.4 Stripe Ecommerce Fraud Prevention Software Revenue (US$ Million) & (2020-2025)
    • 7.1.5 Stripe Recent Developments
  • 7.2 Riskified
    • 7.2.1 Riskified Profile
    • 7.2.2 Riskified Main Business
    • 7.2.3 Riskified Ecommerce Fraud Prevention Software Products, Services and Solutions
    • 7.2.4 Riskified Ecommerce Fraud Prevention Software Revenue (US$ Million) & (2020-2025)
    • 7.2.5 Riskified Recent Developments
  • 7.3 Sift
    • 7.3.1 Sift Profile
    • 7.3.2 Sift Main Business
    • 7.3.3 Sift Ecommerce Fraud Prevention Software Products, Services and Solutions
    • 7.3.4 Sift Ecommerce Fraud Prevention Software Revenue (US$ Million) & (2020-2025)
    • 7.3.5 Sift Recent Developments
  • 7.4 Ethoca (Mastercard)
    • 7.4.1 Ethoca (Mastercard) Profile
    • 7.4.2 Ethoca (Mastercard) Main Business
    • 7.4.3 Ethoca (Mastercard) Ecommerce Fraud Prevention Software Products, Services and Solutions
    • 7.4.4 Ethoca (Mastercard) Ecommerce Fraud Prevention Software Revenue (US$ Million) & (2020-2025)
    • 7.4.5 Ethoca (Mastercard) Recent Developments
  • 7.5 Signifyd
    • 7.5.1 Signifyd Profile
    • 7.5.2 Signifyd Main Business
    • 7.5.3 Signifyd Ecommerce Fraud Prevention Software Products, Services and Solutions
    • 7.5.4 Signifyd Ecommerce Fraud Prevention Software Revenue (US$ Million) & (2020-2025)
    • 7.5.5 Signifyd Recent Developments
  • 7.6 NoFraud
    • 7.6.1 NoFraud Profile
    • 7.6.2 NoFraud Main Business
    • 7.6.3 NoFraud Ecommerce Fraud Prevention Software Products, Services and Solutions
    • 7.6.4 NoFraud Ecommerce Fraud Prevention Software Revenue (US$ Million) & (2020-2025)
    • 7.6.5 NoFraud Recent Developments
  • 7.7 Forter
    • 7.7.1 Forter Profile
    • 7.7.2 Forter Main Business
    • 7.7.3 Forter Ecommerce Fraud Prevention Software Products, Services and Solutions
    • 7.7.4 Forter Ecommerce Fraud Prevention Software Revenue (US$ Million) & (2020-2025)
    • 7.7.5 Forter Recent Developments
  • 7.8 Subuno
    • 7.8.1 Subuno Profile
    • 7.8.2 Subuno Main Business
    • 7.8.3 Subuno Ecommerce Fraud Prevention Software Products, Services and Solutions
    • 7.8.4 Subuno Ecommerce Fraud Prevention Software Revenue (US$ Million) & (2020-2025)
    • 7.8.5 Subuno Recent Developments
  • 7.9 TransUnion
    • 7.9.1 TransUnion Profile
    • 7.9.2 TransUnion Main Business
    • 7.9.3 TransUnion Ecommerce Fraud Prevention Software Products, Services and Solutions
    • 7.9.4 TransUnion Ecommerce Fraud Prevention Software Revenue (US$ Million) & (2020-2025)
    • 7.9.5 TransUnion Recent Developments
  • 7.10 SEON
    • 7.10.1 SEON Profile
    • 7.10.2 SEON Main Business
    • 7.10.3 SEON Ecommerce Fraud Prevention Software Products, Services and Solutions
    • 7.10.4 SEON Ecommerce Fraud Prevention Software Revenue (US$ Million) & (2020-2025)
    • 7.10.5 SEON Recent Developments
  • 7.11 Shield
    • 7.11.1 Shield Profile
    • 7.11.2 Shield Main Business
    • 7.11.3 Shield Ecommerce Fraud Prevention Software Products, Services and Solutions
    • 7.11.4 Shield Ecommerce Fraud Prevention Software Revenue (US$ Million) & (2020-2025)
    • 7.11.5 Shield Recent Developments
  • 7.12 ACI Worldwide
    • 7.12.1 ACI Worldwide Profile
    • 7.12.2 ACI Worldwide Main Business
    • 7.12.3 ACI Worldwide Ecommerce Fraud Prevention Software Products, Services and Solutions
    • 7.12.4 ACI Worldwide Ecommerce Fraud Prevention Software Revenue (US$ Million) & (2020-2025)
    • 7.12.5 ACI Worldwide Recent Developments
  • 7.13 Kount (Equifax)
    • 7.13.1 Kount (Equifax) Profile
    • 7.13.2 Kount (Equifax) Main Business
    • 7.13.3 Kount (Equifax) Ecommerce Fraud Prevention Software Products, Services and Solutions
    • 7.13.4 Kount (Equifax) Ecommerce Fraud Prevention Software Revenue (US$ Million) & (2020-2025)
    • 7.13.5 Kount (Equifax) Recent Developments
  • 7.14 PayPal
    • 7.14.1 PayPal Profile
    • 7.14.2 PayPal Main Business
    • 7.14.3 PayPal Ecommerce Fraud Prevention Software Products, Services and Solutions
    • 7.14.4 PayPal Ecommerce Fraud Prevention Software Revenue (US$ Million) & (2020-2025)
    • 7.14.5 PayPal Recent Developments
  • 7.15 Visa
    • 7.15.1 Visa Profile
    • 7.15.2 Visa Main Business
    • 7.15.3 Visa Ecommerce Fraud Prevention Software Products, Services and Solutions
    • 7.15.4 Visa Ecommerce Fraud Prevention Software Revenue (US$ Million) & (2020-2025)
    • 7.15.5 Visa Recent Developments
  • 7.16 Razorpay
    • 7.16.1 Razorpay Profile
    • 7.16.2 Razorpay Main Business
    • 7.16.3 Razorpay Ecommerce Fraud Prevention Software Products, Services and Solutions
    • 7.16.4 Razorpay Ecommerce Fraud Prevention Software Revenue (US$ Million) & (2020-2025)
    • 7.16.5 Razorpay Recent Developments
  • 7.17 Bolt
    • 7.17.1 Bolt Profile
    • 7.17.2 Bolt Main Business
    • 7.17.3 Bolt Ecommerce Fraud Prevention Software Products, Services and Solutions
    • 7.17.4 Bolt Ecommerce Fraud Prevention Software Revenue (US$ Million) & (2020-2025)
    • 7.17.5 Bolt Recent Developments
  • 7.18 DataDome
    • 7.18.1 DataDome Profile
    • 7.18.2 DataDome Main Business
    • 7.18.3 DataDome Ecommerce Fraud Prevention Software Products, Services and Solutions
    • 7.18.4 DataDome Ecommerce Fraud Prevention Software Revenue (US$ Million) & (2020-2025)
    • 7.18.5 DataDome Recent Developments
  • 7.19 Ping Identity
    • 7.19.1 Ping Identity Profile
    • 7.19.2 Ping Identity Main Business
    • 7.19.3 Ping Identity Ecommerce Fraud Prevention Software Products, Services and Solutions
    • 7.19.4 Ping Identity Ecommerce Fraud Prevention Software Revenue (US$ Million) & (2020-2025)
    • 7.19.5 Ping Identity Recent Developments
  • 7.20 ClearSale
    • 7.20.1 ClearSale Profile
    • 7.20.2 ClearSale Main Business
    • 7.20.3 ClearSale Ecommerce Fraud Prevention Software Products, Services and Solutions
    • 7.20.4 ClearSale Ecommerce Fraud Prevention Software Revenue (US$ Million) & (2020-2025)
    • 7.20.5 ClearSale Recent Developments
  • 7.21 Fingerprint
    • 7.21.1 Fingerprint Profile
    • 7.21.2 Fingerprint Main Business
    • 7.21.3 Fingerprint Ecommerce Fraud Prevention Software Products, Services and Solutions
    • 7.21.4 Fingerprint Ecommerce Fraud Prevention Software Revenue (US$ Million) & (2020-2025)
    • 7.21.5 Fingerprint Recent Developments
  • 7.22 Arkose Labs
    • 7.22.1 Arkose Labs Profile
    • 7.22.2 Arkose Labs Main Business
    • 7.22.3 Arkose Labs Ecommerce Fraud Prevention Software Products, Services and Solutions
    • 7.22.4 Arkose Labs Ecommerce Fraud Prevention Software Revenue (US$ Million) & (2020-2025)
    • 7.22.5 Arkose Labs Recent Developments

8 Industry Chain Analysis

  • 8.1 Ecommerce Fraud Prevention Software Industrial Chain
  • 8.2 Ecommerce Fraud Prevention Software Upstream Analysis
    • 8.2.1 Key Raw Materials
    • 8.2.2 Raw Materials Key Suppliers
    • 8.2.3 Manufacturing Cost Structure
  • 8.3 Midstream Analysis
  • 8.4 Downstream Analysis (Customers Analysis)
  • 8.5 Sales Model and Sales Channels
    • 8.5.1 Ecommerce Fraud Prevention Software Sales Model
    • 8.5.2 Sales Channel
    • 8.5.3 Ecommerce Fraud Prevention Software Distributors

9 Research Findings and Conclusion

10 Appendix

  • 10.1 Research Methodology
    • 10.1.1 Methodology/Research Approach
      • 10.1.1.1 Research Programs/Design
      • 10.1.1.2 Market Size Estimation
      • 10.1.1.3 Market Breakdown and Data Triangulation
    • 10.1.2 Data Source
      • 10.1.2.1 Secondary Sources
      • 10.1.2.2 Primary Sources
  • 10.2 Author Details
  • 10.3 Disclaimer
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