Our UK Fraud Detection & Prevention in Banking research suite provides detailed evaluation and analysis of the evolving fraud landscape in the UK for banking and the financial industry, including fraud trends and the impact of evolving payment types, such as instant payments, blockchain and CBDCs (Central Bank Digital Currencies). This cutting-edge fraud analytics and prevention techniques study examines other initiatives and fraud types disrupting the market, such as increasing APP fraud rate and the use of artificial intelligence by both good and bad actors.
By gaining access to this report, readers will gain a greater understanding of how to best formulate fraud prevention strategies across various types of fraud, and implement processes that enable more efficient decisions about fraud claims. They will also better understand the warning signs that can be detected by payment service providers.
The suite includes a data deliverable, sizing and providing key forecast data; comprising splits for type of financial institutions in the UK fraud, such as and credit unions, fintechs, investment companies and lenders.
Also included is a comprehensive assessment of the key trends, fraud risks, and recommendations for stakeholders. The research suite is a comprehensive tool for understanding this major market; allowing stakeholders to make better-informed decisions on future strategies and predictive intelligence in the UK fraud detection & prevention in banking market.
Key Features
Market Dynamics: strategic analysis of the major drivers, challenges, and innovations shaping the adoption and development of the tools that provide defence against fraud, including:
The importance of using real-time fraud detection & prevention solutions in the face of growing fraudulent activity in financial transactions.
Future strategic directions and market outlook for fraud detection & prevention in banking vendors.
Key drivers and benefits of financial fraud activity detection & prevention solutions in the fight against fraud, including an increase in global fraud rates and fraud losses, the implementation of AI and ML, the analysis of real-time data and pattern recognition, highlighting the impact on the payments and banking space, as well as how fraud detection & prevention platforms can improve the way they operate in the banking space.
Key Takeaways & Strategic Recommendations: In-depth analysis of emerging fraudulent activities and key findings within the UK fraud detection & prevention in banking market, accompanied by strategic recommendations for stakeholders against rising incidents of fraud.
Benchmark Industry Forecasts: The research suite includes five-year forecasts for the UK fraud detection & prevention market, split by banks and financial institutions. The forecast also comprises splits by money transfer and banking.
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:
Accertify
AccessPay
ACI Worldwide
Comply Advantage
Featurespace
Feedzai
Fiserv
Fraudio
GBG
LexisNexis Risk Solutions
Mastercard
SEON
Thales
TransUnion
Visa
Please note: the online download version of this report is for a global site license.
- 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
- 2.2.1 Future Outlook
- 2.2.2 Juniper Research’s Recommendations
- 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
- vii. Money Laundering
- Figure 2.2: Visualisation of Money Laundering
- viii. Chargeback Fraud
- Figure 2.3: Visualisation of Chargeback Fraud
- ix. ATO
- Figure 2.4: Visualisation of Account Takeover
- x. Synthetic Identity
- Figure 2.5: Visualisation 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
- 2.5 UK Activities and Regulations Aiming to Prevent Fraud
- 2.5.1 Instant Payment Regulation
- 2.5.2 Dedicated Card and Payment Crime Unit
- 2.5.3 The Banking Protocol Rapid Response Scheme
- 2.5.4 BPS (Best Practice Standards) System
- 2.5.5 Customer Education and Awareness Campaigns
- 2.5.6 Juniper Research’s View
- 3. Competitor Leaderboard
- 3.1 Why Read This Report
- Table 3.1: Juniper Research Leaderboard: UK Fraud Detection & Prevention Vendors Included & Product Portfolio
- Figure 3.2: Juniper Research Leaderboard: UK Fraud Detection & Prevention in Banking Leaderboard
- Table 3.3: Juniper Research Leaderboard: Fraud Detection & Prevention in Banking Vendors
- Table 3.4: Juniper Research Leaderboard Heatmaps: UK Fraud Detection & Prevention in Banking Vendors
- 3.2 UK Fraud Detection & Prevention in Banking Vendors
- 3.2.1 Accertify
- i. Corporate
- ii. Geographical Spread
- iii. Key Clients & Strategic Partnerships
- iv. High-level View of Offering
- Figure 3.5: Accertify Financial Institution Fraud Prevention Solution
- v. Juniper Research’s View: Key Strengths & Strategic Opportunities
- 3.2.2 AccessPay
- i. Corporate
- ii. Geographical Spread
- iii. Key Clients and Strategic Partnerships
- iv. High-level View of Offering
- v. Juniper Research’s View: Key Strengths & Strategic Opportunities
- 3.2.3 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
- 3.2.4 ComplyAdvantage
- 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
- 3.2.5 Featurespace
- 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
- 3.2.6 Feedzai
- 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
- 3.2.7 Fiserv
- 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
- 3.2.8 Fraudio
- 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
- 3.2.9 GBG
- 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
- 3.2.10 LexisNexis Risk Solutions
- 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
- 3.2.11 Mastercard
- 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
- 3.2.12 SEON
- 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
- 3.2.13 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
- 3.2.14 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
- 3.2.15 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
- 3.3 Juniper Research Leaderboard Assessment Methodology
- 3.3.1 Limitations & Interpretations
- Table 3.8: Juniper Research’s Competitor Leaderboard Scoring Criteria – Fraud Detection & Prevention in Banking
- 4. Forecast Summary
- 4.1 Forecast Introduction
- 4.2 Methodology & Assumptions
- Figure 4.1: Spend on Fraud Detection and Prevention in Banking UK Forecast Methodology
- Figure 4.2: Fraudulent Transaction Value UK Forecast Methodology
- 4.3 Forecast Overview
- 4.3.1 Total Number of Banks and Financial Institutions Using Fraud Detection and Prevention Solutions
- Figure & Table 4.3: Total Number of Banks and Financial Institutions Using Fraud Detection and Prevention Solutions, 2024-
- 4.3.2 Total Spend on Fraud Detection and Prevention
- Figure & Table 4.4: Total Spend on Fraud Detection and Prevention Solutions ($m), Split by Financial Institution, 2024-
- 4.3.3 Total Number of Fraudulent Transactions in Banking and Money Transfer
- Figure & Table 4.5: Total Number of Fraudulent Transaction in Banking and Money Transfer (m), 2024
- 4.3.4 Total Value of Fraudulent Transactions in Banking and Money Transfer
- Figure & Table 4.6: Total Value of Fraudulent Transaction in Banking and Money Transfer ($m), 2024
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