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MoData + DataVisor partnership
Featured

DataVisor and MoData Partner to Accelerate Digital Fraud Prevention Across Africa

Featured
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Tony Kueh- Why I'm All In: Joining DataVisor as COO|Tony Kueh_COO_Why I'm All In_DataVisor
Quick Takes

Why I'm All In: Joining DataVisor as COO

Quick Takes
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Tackling the Complexities of Modern Payment Fraud, Yinglian Xie, CEO, DataVisor|
Digital Fraud Trends

Tackling the Complexities of Modern Payment Fraud: Key Insights from Fintech Meetup 2025

Digital Fraud Trends
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Wood blocks 2025
Quick Takes

Top Fraud Trends and Predictions for 2025 – And How Will the Industry Respond?

Quick Takes
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Fraud Prevention: What Fintechs Really Need from DataVisor. Fraud analyst overwhelmed by many screens
Quick Takes

Fraud Prevention: What Fintechs Really Need

Quick Takes
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FRAML done right: Fraud and AML teams tap shared date, but have separate workflows|FRAML Venn Diagram: Shared Dataset, Separate Workflows with different goals and needs
Quick Takes

FRAML Done Right: Shared Data, Not Workflows

Quick Takes
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Sponsor Banks and Fintechs collaborating to achieve global regulatory compliance
Quick Takes

7 Ways Sponsor Banks and Fintechs Are Collaborating to Achieve Regulatory Compliance in 2025

Quick Takes
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Unlocking Revenue Growth with Smart Fraud Prevention|Amanda Peterson, Director, Fraud and Risk, TabaPay|Mike Lavia, Director of Payments, DataVisor
Quick Takes

Unlock Revenue Potential with Smart Fraud Prevention

Quick Takes
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Digital Fraud Trends

Fraud Awards 2024: The Most Shocking and Sophisticated Schemes of the Year

Digital Fraud Trends
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Sponsor Banks' BaaS team working collaboratively across fraud and money laundering
Product Blogs

Why Banking-as-a-Service Sponsor Banks Are Unifying Fraud and AML

Product Blogs
Banking Fraud
fraud ring
Dummies Series

Fraud Rings: How They Work and Why Uncovering Them is a Challenge

Dummies Series
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Future Proof Customer Onboarding to be Fraud Resistant_Insights from Brian Hughes_DataVisor Blog|Future-Proof Fraud-Resistant Customer Onboarding_6 Core Capabilities_DataVisor Blog|10 ESSENTIAL SIGNALS Detecting and Mitigating Fraud Risk Signals Bot Detection Behavioral Analytics Device Intelligence Phone & Email Stolen ID Synthetic ID First Party Linkage Analysis Document Verification Government Sources|STRATEGY & GOVERNANCE 
The Foundation of Effective Fraud Prevention Key Components COMMON PITFALLS Strategy & 
Governance Benchmarking capabilities against industry best practices Cross-functional collaboration Shared scorecard for fraud metrics Alignment of fraud prevention with customer experience Waiting for large losses to justify fraud prevention investments Siloed approach to fraud management Lack of a unified strategy across departments Implementation Tips BEST PRACTICES Establish regular cross-functional meetings to manage the new account funnel Develop a comprehensive fraud risk management program Continuously assess and update fraud prevention strategies Ensure clear communication of fraud prevention goals across the organization Justify fraud investments based on capability benchmarks, not just loss reduction Involve marketing, fraud tech, and operations teams in managing the onboarding process Use a common scorecard with metrics for fraud rates, customer friction, and costs Recognize that great customer experience is backed by strong fraud capabilities|RAPID RESPONSE & CONTINUOUS OPTIMIZATION KEY COMPONENTS Response & 
Improvement Constant testing of signal providers Regular threshold adjustments 24-hour rule implementation Quarterly/monthly model updates Attack playbook preparation Fraud red team exercises Monitor early warning signals Implement new rules within 24 hours of vulnerability detection Maintain an up-to-date attack response plan Use AI-powered models for faster adaptation Conduct regular fraud defense simulations|ORCHESTRATIONConnecting Data for Effective Fraud Prevention KEY FEATURES KEY BENEFITS BEST PRACTICES Orchestration Streamlines access to diverse data sources Facilitates testing of new signal providers Offers insights for updating and expanding fraud strategies Connects to multiple signal providers through a single integration Simplifies contracting with resale agreements Provides strategic advice based on industry experience Regularly test new signal providers Leverage orchestrator's expertise for signal selection Utilize both third-party and internal data for comprehensive fraud prevention|DECISIONINGEvolving from Rules to AI-Powered Models AI MODELS RULES OPTIMAL SOLUTION Decisioning Improved scalability Enhanced accuracy Greater adaptability to new fraud patterns + Enforce non-negotiable policies (e.g., blocking known fraudsters) Serve as a secondary line of defense = Reduced manual management of complex rule sets Faster adaptation to evolving fraud tactics More efficient handling of multiple variables in onboarding|INVESTIGATION Swift Action on Fraud Alerts INVESTIGATION Swift Action on Fraud Alerts KEY FEATURES GOAL & IMPORTANCE BEST PRACTICES KEY FEATURES GOAL & IMPORTANCE BEST PRACTICES Investigation Rapid case connection through linkage analysis Threshold-based prioritization of losses Integration with decisioning platform for insights Identify vulnerabilities and implement fixes within 24 hours Fraud losses indicate system vulnerabilities Quick investigation enables rapid response and prevention Use linkage analysis to group related cases Focus on largest losses first Cross-train staff for surge capacity Leverage decisioning insights for efficient investigation Rapid case connection through linkage analysis Threshold-based prioritization of losses Integration with decisioning platform for insights Identify vulnerabilities and implement fixes within 24 hours Fraud losses indicate system vulnerabilities Quick investigation enables rapid response and prevention Use linkage analysis to group related cases Focus on largest losses first Cross-train staff for surge capacity Leverage decisioning insights for efficient investigation
Digital Fraud Trends

Future-Proofing Customer Onboarding to Prevent Fraud: Insights from Brian Hughes

Digital Fraud Trends
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DataVisor’s Knowledge Graph: The Holy Grail for Financial Fraud Investigations

Compliance Solutions
DataVisor Knowledge Graph
Buy Now Pay Later (BNPL) Fraud_picture of mobile bnpl purchase_DataVisor|buy now pay later scam|How to Detect and Prevent BNPL Fraud Harness Comprehensive Data Sources Leverage third-party data connectors Implement device intelligence and behavioral biometrics Use Real-Time Data Orchestration Centralize information for 360° customer views Enable continuous transaction monitoring Customize Rules and Features Tailor fraud detection to your business needs Quickly develop and test new features Utilize Unsupervised Machine Learning Capture emerging fraud patterns in real-time Stay ahead of evolving threats Leverage Generative AI Automate tedious tasks Boost efficiency with AI-assisted rule tuning|
Digital Fraud Trends

Buy Now Pay Later (BNPL): The Rising E-commerce Payment Choice and Its Fraud Concerns

Digital Fraud Trends
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Is Vendor Consolidation the Right Approach? Understand the Benefits and Risks. Q& A with Yinglian Xie, CEO & Cofounder, DataVisor
Quick Takes

Vendor Consolidation vs Orchestration: Understand the Benefits and Risks with DataVisor's Co-founder and CEO, Yinglian Xie

Quick Takes
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fednow vs other payments|payment systems
Quick Takes

3 Ways FedNow is Different From Other Payments

Quick Takes
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Defining the Discretionary Other Firms in the Protecting Consumers from Payment Scams_MikeCook_DataVisor
Digital Fraud Trends

Defining the Discretionary "Other Firms" in the "Protecting Consumers from Payment Scams Act"

Digital Fraud Trends
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Zigzagging toward APP Fraud Liability, Article by Mike Cook of DataVisor
Digital Fraud Trends

Zig-zagging Toward Compliance: The Uncertain Certainty of APP Fraud Liability

Digital Fraud Trends
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Mike Cook_VP Product Solutions_Datavisor
Quick Takes

Interview with Mike Cook, VP Product Solutions: 35 Years of Protecting People from Fraud

Quick Takes
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UK PSR APP fraud reimbursement cap changes and what they mean for risk and compliance_DataVisor
Digital Fraud Trends

Guide to UK's New APP Fraud Reimbursement Cap: What It Means for Risk & Compliance

Digital Fraud Trends
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How to Choose the Right Fraud Detection Platform for E-Commerce|How E-Commerce Companies Choose the Right Fraud Detection Platform 1|How E-Commerce Companies Choose the Right Fraud Detection Platform|illustration of a man working on a laptop to secure his accounts
Quick Takes

How E-Commerce Companies Choose the Right Fraud Detection Platform

Quick Takes
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4 Types of Digital Bank Fraud_DataVisor_Graphic||fintech fraud|datavisor device intelligence impact. Reduced attack events within three weeks
Digital Fraud Trends

4 Major Digital Bank Frauds and How to Stop Them

Digital Fraud Trends
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Anatomy of an Account Takeover (ATO) Attack|
Quick Takes

Account Takeover Fraud: The Anatomy of an ATO Attack

Quick Takes
Account Takeover
Financial Fraud
first-party fraud|prevent payment fraud
Digital Fraud Trends

Fighting Authorized Payment Fraud: How to Stop Real-time Scams

Digital Fraud Trends
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Blog_3-ways-ot-use-AI-in-AML-Compliance_Datavisor
Product Blogs

3 Ways You Should be Using AI in Your AML Compliance

Product Blogs
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DataVisor 4 reasons to use uml for fraud detection|unspuervised machine learning datavisor|unsupervised machine learning
Product Blogs

4 Super Powers of Unsupervised Machine Learning

Product Blogs
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A complete guide to the proposed Regulation E changes, plus how Financial Institutions are preparing|Complete Guide to Regulation E Proposed Changes
CPO Corner

Complete Guide to Proposed Regulation E Changes

CPO Corner
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friendly fraud
Digital Fraud Trends

Strategies and Tools to Prevent Friendly Fraud in 2024

Digital Fraud Trends
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fraud prevention discussion
Quick Takes

AI-Powered Fraud, First-Party Fraud, and Data Consortiums: Around the Fraud Prevention Water Cooler

Quick Takes
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grow credit union
Quick Takes

5 Ways to Grow Your Credit Union Without Increasing Fraud

Quick Takes
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|DEFEND day zero risk
On-Demand Webinar

Customer-Centric Strategies to Achieve True Day Zero Risk

On-Demand Webinar
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DEFEND day zero risk|
Quick Takes

Why Day Zero Risk Matters and Which Tools Achieve It

Quick Takes
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evolve bank and trust cease and desist order
Digital Fraud Trends

9 Important Lessons from Evolve Bank & Trust’s Cease and Desist

Digital Fraud Trends
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|BaaS compliance 2024|lunch and learn BaaS datavisor
Digital Fraud Trends

BaaS Beyond the Boom - Compliance in 2024 and Beyond

Digital Fraud Trends
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designing financial products with AI|ai improving internal processes
Digital Fraud Trends

How to Build Safe, Usable Products with AI

Digital Fraud Trends
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banking as a service
CPO Corner

The Evolution of BaaS: Redefining Risk and Responsibility in Banking

CPO Corner
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device intelligence|dEdge integration|DataVisor device intelligence
FraudTech

Why Device Intelligence is Critical for Fraud Fighters

FraudTech
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dennis maicon datavisor
Product Blogs

A Leader’s Guide to Navigating the Future of Fraud Prevention with DataVisor’s Dennis Maicon

Product Blogs
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Brenda Banks DataVisor
Product Blogs

A Q&A with DataVisor’s new VP of BaaS and BSA Brenda Banks

Product Blogs
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check fraud 2024|check walker
Digital Fraud Trends

How to Defeat Rising Check Fraud in 2024

Digital Fraud Trends
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automated rule tuning|automated rule tuning false positive decrease detection accuracy increase|AI co-pilot ebook|generative AI|generative AI|comparative insights automated rule tuning|automated rule tuning ai co-pilot|ai co-pilot||AI co-pilot
FraudTech

How to Save 50% of Your Fraud Team’s Time with Automated Rule Tuning

FraudTech
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data orchestration real time fraud
FraudTech

How to Use Data Orchestration to Fight Real-Time Fraud

FraudTech
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fraud prevention platform
Product Blogs

Can You Use the DataVisor Platform to Build Your Own Fraud Solution?

Product Blogs
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crypto scams
Digital Fraud Trends

Crypto Fraud Scams: A Deep Dive

Digital Fraud Trends
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BaaS regulatory requirements for sponsor banks and fintechs
Digital Fraud Trends

Regulatory Requirements for Sponsor Banks: What You Need to Know

Digital Fraud Trends
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romance scams
Digital Fraud Trends

How Romance Scams are Evolving and Ways to Stay Safe

Digital Fraud Trends
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Fraud trends 2023|
Digital Fraud Trends

Experts Name the Most Challenging Fraud Threats from 2023 to Watch in 2024

Digital Fraud Trends
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generative ai||generative ai fraud
Digital Fraud Trends

The Transformative Impact of Generative AI for Fraudsters and Fraud Fighters

Digital Fraud Trends
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2023 holiday frauds|fraud attack
Digital Fraud Trends

2023 Holiday Fraud Attacks to Watch For

Digital Fraud Trends
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data orchestration|data orchestration webinar|data orchestration
Digital Fraud Trends

Harmonizing Defense: The Power of Data Orchestration in Fraud Prevention

Digital Fraud Trends
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|changing fraud prevention provider
Quick Takes

7 Common Mistakes to Avoid When Migrating to a New Fraud Solution

Quick Takes
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check fraud|AI check fraud
Digital Fraud Trends

How to Stop Check and Deposit Fraud with AI

Digital Fraud Trends
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Product Blogs

Introducing AI Co-pilot: Your New Generative AI-Powered Fraud-Fighting Companion

Product Blogs
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fraud attack
Quick Takes

How to Bounce Back from a Major Fraud Attack

Quick Takes
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DataVisor CRO Kevin McWey|Kevin mcwey datavisor|Kevin McWey DataVisor|Kevin McWey DataVisor
Quick Takes

A Q&A with DataVisor’s new CRO Kevin McWey

Quick Takes
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Product Blogs

How DataVisor Provided NASA FCU with Award-winning Fraud Prevention

Product Blogs
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||Best Transaction Fraud Monitoring and Decisioning Solution|
In-Person Event

Let’s meet! Here’s Where You Can Find DataVisor This Fall

In-Person Event
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machine learning fraud detection|machine learning fraud prevention
CPO Corner

5 Things Every Fraud Leader Should Know About Machine Learning

CPO Corner
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AI fraud fighter robot|fraud detection machine learning webinar
Product Blogs

The Changing Landscape of Fraud Detection in the Age of Data Science

Product Blogs
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fraud trends 2023
Digital Fraud Trends

Here are the Top Fraud Trends of 2023 (So Far...)

Digital Fraud Trends
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cryptocurrency fraud
Digital Fraud Trends

How Do We Make Cryptocurrency Safe?

Digital Fraud Trends
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Best fraud detection|types of machine learning fraud detection
Quick Takes

3 Key Ways Machine Learning Powers Fraud Prevention

Quick Takes
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FedNow
Digital Fraud Trends

FedNow: Everything You Need to Know

Digital Fraud Trends
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detect fraud
Product Blogs

Preventing the Fraud on the Edge

Product Blogs
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AI fraud prevention|FedNow fraud
CPO Corner

How AI is Defeating Real-time Fraud

CPO Corner
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instant payment scam
Digital Fraud Trends

How Real-time Payments Became the Epicenter for Scams

Digital Fraud Trends
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Digital fraud investigations|case management system fraud prevention|case management|fraud analyst|fraud analyst
Dummies Series

Starter's Guide to Digital Fraud Investigations

Dummies Series
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fraud analytics
Product Blogs

5 Signs It's Time for a New Fraud Solution

Product Blogs
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CPO Corner

AML Transaction Monitoring Explained: How to Catch a Money Launderer

CPO Corner
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How to Detect Call Center Fraud_1|||How to Detect Call Center Fraud
Quick Takes

How to Detect and Mitigate Call Center Fraud

Quick Takes
Account Takeover
Call Center Fraud
Fraud Detection
Identity Theft
ANG Report Featured Image
Digital Fraud Trends

Why Aite-Novarica's Fraud Trend Report is 2023's Best Fraud Prevention Guide Yet

Digital Fraud Trends
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illustration case management in fraud detection
Quick Takes

Key Takeaways from our First DEFEND Webinar of 2023

Quick Takes
DEFEND
Webinar
digital fraud infographic
CPO Corner

Why Fake Accounts are a Starting Point for Fraud

CPO Corner
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DEFEND Feb 2023 banner
Featured

4 Fraud Strategy Topics I Can’t Wait to Discuss at DataVisor’s DEFEND Webinar

Featured
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Best fraud detection
CPO Corner

3 Tips to Enhance Fraud Detection While Minimizing Costs

CPO Corner
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illustration case management in fraud detection|digital fraud investigations handbook download banner
Dummies Series

Case Management Software - The Backbone of Your Digital Fraud Prevention Strategy

Dummies Series
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Risk and Payments in the Internet of Things (IoT) Part Two - Getting Ready for IoT Payments
Quick Takes

Risk and Payments in the Internet of Things (IoT) Part Two – Getting Ready for IoT Payments

Quick Takes
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How to Stop Chargeback Fraud with AI-Powered Detection|How to Stop Chargeback Fraud with AI-Powered Detection600x400 (1)
Quick Takes

How to Stop Chargeback Fraud with AI-Powered Detection

Quick Takes
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Abusive Customers - How to Spot the Iron Fist in the Velvet Glove - 1@300x|Promotion abuse|Abusive Customers - How to Spot the Iron Fist in the Velvet Glove
Quick Takes

Abusive Customers - How to Spot the Iron Fist in the Velvet Glove

Quick Takes
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3 Payment Acceptance Strategies to Improve eCommerce Revenue and Reduce Fraud|Payment Acceptance Strategies to Improve eCommerce Revenue and Reduce Fraud|A Practical Guide to Eliminating False Positives in Fraud Management_Social
Quick Takes

3 Payment Acceptance Strategies to Improve eCommerce Revenue and Reduce Fraud

Quick Takes
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How Banks Can Respond to New FFIEC Guidelines|How Banks Can Respond to New FFIEC Guidelines|How Banks Can Respond to New FFIEC Guidelines1200x630
Quick Takes

How Banks Can Respond to New FFIEC Guidelines

Quick Takes
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5 Tips for Better Online Fraud Detection RFPs|5 Tips for Better Online Fraud Detection RFPs|Best Practices for a Killer RFP + Bonus Template - social
Quick Takes

5 Tips for Better Online Fraud Detection RFPs

Quick Takes
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20211117_How to Stop Chargeback Fraud with AI-Powered Detection1200x630|20211117_How to Stop Chargeback Fraud with AI-Powered Detection600x400|DataVisor - Request Demo Banner|first-party fraud
Quick Takes

How to Prevent Policy Abuse Fraud and Friendly Fraud

Quick Takes
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Holiday Ecommerce Alert: Stop Chargeback Fraud with These Tips|Holiday Ecommerce Alert: Stop Chargeback Fraud with These Tips (2)|Holiday Ecommerce Alert- Stop Chargeback Fraud with These Tips|Holiday Ecommerce Alert: Stop Chargeback Fraud with These Tips
Quick Takes

Holiday Ecommerce Alert: Stop Chargeback Fraud with These Tips

Quick Takes
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Digital fraud investigations|A Closer Look at Digital Identities and Fraud (1)|Digital fraud investigations and CMS|Open Finance: The Future and Challenge of Data Sharing SOCIAL|Open Finance: The Future and Challenge of Data Sharing
Quick Takes

A Closer Look at Digital Identities and Fraud

Quick Takes
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Say 'Yes' to Good Customers and 'No' to Digital Fraud––Why a Holistic Approach is Needed|Say 'Yes' to Good Customers and 'No' to Digital Fraud––Why a Holistic Approach is Needed|Say 'Yes' to Good Customers and 'No' to Digital Fraud––Why a Holistic Approach is Needed
Quick Takes

Say 'Yes' to Good Customers and 'No' to Digital Fraud––Why a Holistic Approach is Needed

Quick Takes
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Practical Guide to Stop Loan Stacking|Practical Guide to Stop Loan Stacking|illustration canceling a person standing on a stack of gold coins
Quick Takes

Practical Guide to Stop Loan Stacking

Quick Takes
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What Finance Professionals Can Learn from Fraud History|Infamous Fraud Cases and Their Implications for Modern Fraud Experts|DataVisor - Digital Fraud Tracker Download Banner|illustration of three professionals having a discussion
Quick Takes

Infamous Fraud Cases and Their Implications for Modern Fraud Experts

Quick Takes
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What Is Expense Fraud and How Can You Detect It?|What Is Expense Fraud and How Can You Detect It?|illustration depicting secure online shopping
Quick Takes

What Is Expense Fraud and How Can You Detect It?

Quick Takes
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Tradeoff Between Fraud Prevention and CX_1200x628|Fight Fraud in a Mobile-first World with Device Intelligence|Tradeoff Between Fraud Prevention and CX_Social|
Quick Takes

Does There Have to Be a Tradeoff Between Fraud Prevention and Customer Experience?

Quick Takes
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Demystifying Modern Fraud Attacks in Banking|Demystifying Modern Fraud Attacks in Banking|webinar banner modern fraud in banking
Quick Takes

Demystifying Modern Fraud Attacks in Banking

Quick Takes
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PSD2: A Gateway to Customer-Centric Financial Services|PSD2: A Gateway to Customer-Centric Financial Services|illustration of a man and gold coins|PSD2 guide download banner
Quick Takes

PSD2: A Gateway to Customer-Centric Financial Services

Quick Takes
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Point of Sale Finance: Stopping Fraud in the Fintech Revolution|Point of Sale Finance: Stopping Fraud in the Fintech Revolution - Social|illustration of a man working on a laptop
Quick Takes

Point of Sale Finance: Stopping Fraud in the Fintech Revolution

Quick Takes
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Data Sharing with Open Finance- A Look at the Future_1|Data Sharing with Open Finance- A Look at the Future_Social|infographic of cash in a wallet|open finance ebook download banner
Quick Takes

Data Sharing with Open Finance: A Look at the Future

Quick Takes
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Fraud Detection- A Competitive Advantage for Online Lenders_1|Fraud Detection- A Competitive Advantage for Online Lenders_Social
Quick Takes

Fraud Detection: A Competitive Advantage for Online Lenders

Quick Takes
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Fraud Detection Software in Financial Services- Build vs. Buy_1|To Build or to Buy. The ultimate software dilemma.|illustration depicting online shopping
Quick Takes

To Build or to Buy. The ultimate software dilemma.

Quick Takes
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Are You Treating Your Customers Like Criminals?|Are You Treating Your Customers Like Criminals?|illustration of a cop ensuring fraud protection
Quick Takes

Are You Treating Your Customers Like Criminals?

Quick Takes
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Banking- How Unsupervised ML Auguments Rules and Supervised ML_1|Banking How Machine Learning Augments Rules to Boost Fraud Detection|illustration of a secure digital ecosystem|infographic depicting differences between supervised machine learning and unsupervised machine learning
Quick Takes

Banking: How Machine Learning Augments Rules to Boost Fraud Detection

Quick Takes
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Use Advanced AI to Stop Card Not Present Fraud_1|Banking How Machine Learning Augments Rules to Boost Fraud Detection copy|illustration of fraudsters stealing credit card info
Quick Takes

How to use Artificial Intelligence to Stop Card Not Present Fraud

Quick Takes
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How to Optimize The Total Cost of Fraud: 3 Areas to Consider-1|How to Optimize The Total Cost of Fraud: 3 Areas to Consider|How to Optimize The Total Cost of Fraud: 3 Areas to Consider|money fraud illustration
Quick Takes

How to Optimize The Total Cost of Fraud: 3 Areas to Consider

Quick Takes
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