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Welcome to News & Events

Published on June 22, 2020, by in Industry News.

Welcome to The Fraud Practice’s FraudBlog; your source for updates on current events, commentary and best practices related to the eCommerce CNP payments and fraud industry.

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More than 1-in-10 Ransomware Attacks Involve Threat of Releasing Consumer or Client Data

Published on July 13, 2020, by in Data Breach.

Turning ransomware attacks into data breaches if the ransom isn’t paid, what’s being called exfiltration+encryption attacks, can be damaging on multiple levels. In the first half of this year 11 percent of ransomware attacks have adopted this tactic.

ID Ransomware, a website and free tool that allows ransomware victims to upload a ransom note or sample encrypted file to identify the ransomware used against them, had over 100,000 submissions between January 1 and June 30, 2020.

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Who Is Looking Out For eCommerce Merchants?

Guest Post Written by: Daryn Griggs, Co-Founder, Payshield, Certified eCommerce Fraud Professional

The events of COVID 19 have seen a massive increase in online shopping around the world including people who have never shopped online before. Naturally with an increase in online shopping comes an increase in online fraud, and the biggest fraud increase? Friendly Fraud!

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State Unemployment Systems Battered With Breaches and Identity Fraud

Published on May 18, 2020, by in Data Breach.

The state of Arkansas shut down their unemployment application website which exposed the PII of nearly 30,000 applicants and Illinois faced a similar issue. Meanwhile, the U.S. Secret Service reports that hundreds of mules are being used to funnel unemployment benefits to an organized fraud ring in Nigeria falsely filing for benefits with stolen identity information.

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Best Practices for Achieving Success with Custom Modeling and Machine Learning

One of the most common reasons organizations fail to realize significant improvements in risk management after implementing custom modeling solutions can be described with one phrase: Junk in. Junk out. This article discusses best practices as it relates to data management and other factors that are shown to improve performance when it comes to custom modeling and machine learning or artificial intelligence.

It’s not just breadth of data, but also quality of data, that is important. One of the biggest misconceptions about machine learning (ML) and artificial intelligence (AI) is that you can just flip a switch and let the technology work its magic.

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The Role of Custom Modeling in Lending, Card Issuance and Insurance

Fraudulent insurance claims are responsible for more than $80 billion in losses per year in the United States, leading to higher premiums for all policy holders. It is estimated that card issuers will lose $1.3 billion this year from cards issued to synthetic identities. Total fraud losses from synthetic identities receiving loans and credit cards are estimated at $6 billion annually. Lenders, issuers and insurance carriers are increasingly combating fraudulent applications and claims with custom modeling solutions and AI.

Checking pay stubs to verify income is no longer sufficient. Completing an application with their authentic identity, a consumer can easily fabricate paycheck stubs or purchase them online for less than ten dollars. When fraudsters create synthetic identities to take out an uncollateralized loan with no intention of paying it back, they can just easily create or buy fake pay stubs to corroborate their synthesized existence.

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Custom Modeling for Risk Management Requires Human Element, Not Just AI

While there is value in leveraging Artificial Intelligence for modeling and analytics to detect cyber threats and fraud, security professionals are still more likely to indicate that a human touch is more valuable. A recent survey found that half of organizations are making use AI or machine learning but 60 percent put more trust in findings verified by humans. Meanwhile, changing consumer patterns and the rush to work from home in response to the pandemic has likely led to higher rates of false positives.

This isn’t to say AI and ML are not important – they are. In the same survey, 65% said these tools allow them to focus more on preventing cyber attacks than before and 40% reported feeling less stress.

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