Fraud Prevention | Techlist.io

stripeJul 21, 20263 min readCurated summary

Analyzing the evidence that helps businesses win “product not received” disputes

“Product not received” disputes are Stripe’s most common nonfraud dispute category, and strong, specific fulfillment evidence is closely associated with higher win rates. Analysis of one million disputes found that physical-goods businesses benefited most from confirmed delivery data, while digital businesses benefited from usage records and processor-verified refunds. The findings suggest businesses should connect fulfillment systems to dispute workflows and submit evidence strategically. ## Delivery Evidence for Physical Goods - Delivery confirmation correlated with a **27 percentage point** higher win rate than disputes without it. - Adding a GPS delivery map increased the lift by another **15 percentage points**. - A recipient signature added a further **2 percentage points**. - Disputes containing all three forms of evidence had a **44 percentage point** higher win rate. - Many businesses fail to provide this evidence because shipping and dispute systems are disconnected, making order matching a manual, difficult-to-scale process. ## Timing of Tracking Evidence - A tracking number is much more persuasive once it shows confirmed delivery. - Evidence submitted after delivery was confirmed correlated with a **27 percentage point** higher win rate. - Evidence submitted while a package was still in transit produced only a **2 percentage point** lift. - If the response window allows, businesses should wait for delivery confirmation. - If early submission is necessary, they should document that the shipment remains within the delivery timeframe agreed to at checkout. ## Evidence for Digital Goods - Digital activity and usage logs—such as records showing that a customer streamed, downloaded, or accessed the purchased product—correlated with a **10 percentage point** higher win rate. - Service documentation, including provisioning records, produced an **8 percentage point** lift. - Specific evidence of consuming the purchased content is stronger than general proof that the customer had access to the service. ## Refund Verification - For digital-goods businesses, evidence of a full refund processed through Stripe correlated with a **63 percentage point** higher win rate. - Refunds issued through other channels, such as store credit, produced only a **6 percentage point** lift. - Processor-issued refunds are more verifiable to card issuers because they leave a record on the card network. ## Stripe’s Automated Approach - Stripe’s Smart Disputes can automatically assemble evidence packets using shipping and fulfillment data. - Businesses can provide a carrier and tracking number, after which Stripe retrieves delivery status, timestamps, and location information from supported providers. - Additional communications or documentation can be combined with the generated packet. - If no action is taken before the deadline, Smart Disputes can submit the response automatically. Businesses should prioritize specific, independently verifiable fulfillment evidence and coordinate submission timing with the actual delivery or usage status.:VEVENT

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Fraud Prevention AI Stripe Payment Processing+3

stripeJun 3, 20262 min readCurated summary

Helping businesses optimize network costs with the Visa Digital Commerce Authentication Program (DCAP)

Visa’s Digital Commerce Authentication Program (DCAP) rewards US businesses for sharing richer transaction data with issuers during authentication, offering a five-basis-point net interchange reduction on qualifying transactions. However, businesses must balance savings against integration complexity, latency, fraud risk, and authorization rates. Stripe addresses this with transaction-level decisions about when to use Data Only 3DS. ## DCAP’s Opportunity and Complexity - DCAP is designed to reduce card-not-present fraud and improve authorization rates. - Businesses can share data such as: - Device ID - Billing address - IP address - Customer email - Participation requires sending the required cardholder data through frictionless authentication. - Issuers may interpret newer data signals differently, creating uncertainty around performance and latency. - Businesses must evaluate whether interchange savings improve overall transaction economics without reducing conversions. ## Stripe’s Transaction-Level Optimization - Stripe worked with Visa on readiness testing before rolling out DCAP. - Stripe Authorization Boost determines which transactions should use Data Only 3DS. - Data Only 3DS sends additional risk information through the card network to issuers without adding unnecessary customer friction. - Instead of static rules, Authorization Boost evaluates each transaction based on: - Potential cost savings - Conversion impact - Fraud risk - Authorization performance ## Results and Eligibility - Since April 18, Stripe has helped businesses generate $18.4 million in annualized network cost savings. - Collecting and passing the required data increased DCAP-eligible transactions eightfold. - Stripe continues working with Visa to expand eligibility. ## How to Participate - Businesses using Authorization Boost and collecting the required data already receive the optimizations automatically. - Businesses using standalone 3DS can participate by setting `flow_preference[type]` to `data_share` and ensuring all required fields are populated. Businesses should adopt DCAP with transaction-level optimization rather than applying it indiscriminately, maximizing interchange savings while protecting authorization rates and customer conversion.

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Fraud Prevention Stripe 3d Secure Payment Authentication+2

cloudflareMar 12, 20262 min readCurated summary

Announcing Cloudflare Account Abuse Protection: prevent fraudulent attacks from bots and humans

Cloudflare’s new Account Abuse Protection suite targets fraud from both bots and humans, focusing on whether activity is authentic rather than merely automated. It combines leaked-credential detection and account-takeover signals with new tools for identifying risky signups and suspicious identities. The capabilities are in Early Access for Bot Management Enterprise customers at no additional cost temporarily. ## Leaked Credentials and Account Takeover - Cloudflare reports that 41% of network logins use leaked credentials, with password reuse allowing old breaches to compromise valuable accounts. - Its leaked credential check compares hashed passwords against known breach data without storing or accessing plaintext passwords. - More than 60% of login-page traffic during the 2024 Black Friday analysis was automated, enabling attackers to test stolen credentials at scale. - Account takeover (ATO) detections identify customer-specific suspicious login behavior and expose attempted attacks in the Security analytics dashboard. - These detections caught an average of 6.9 billion suspicious login attempts per day across Cloudflare’s network during the referenced week. ## Fraud Requires More Than Bot Detection - Modern abuse combines automation, human fraud farms, device and location spoofing, and synthetic identities. - Attackers may use valid credentials, operate at human speed, or employ AI agents, making simple bot classification insufficient. - Common customer problems include fake users exploiting free trials, attackers logging in with correct passwords, and human-paced account draining. - Effective protection must evaluate intent, identity, and authenticity alongside automation. ## Detecting Suspicious Account Creation - Disposable email addresses allow attackers to create large numbers of accounts for promotions or other abuse without maintaining real email infrastructure. - Cloudflare’s disposable email check provides a binary signal that customers can use in security rules. - Organizations can block disposable addresses outright or challenge users who register with them. - Cloudflare also introduces email-risk assessment based on suspicious email patterns and infrastructure, helping identify potentially fraudulent signups. ## Privacy-Preserving User Identification - Hashed User IDs are per-domain identifiers created by cryptographically hashing usernames. - They help customers correlate suspicious activity and mitigate fraudulent traffic without exposing users’ original identifiers. - The feature is intended to identify risky account behavior while preserving end-user privacy. Cloudflare recommends enabling leaked-credential checks and using the new signup, identity, and behavioral signals together. This layered approach is better suited to fraud campaigns that blend valid credentials, human activity, and automated tools.

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Fraud Prevention Cloudflare Bot Management Database Security+4

stripeMar 10, 20263 min readCurated summary

Analyzing first-party fraud trends: Account, free trial, and refund abuse

First-party fraud is rising as legitimate customers exploit account, trial, and refund policies rather than using stolen credentials. Stripe’s analysis identifies account abuse, free-trial abuse, and refund fraud as rapidly growing problems, with AI companies particularly exposed because free access consumes costly compute resources. Stripe is expanding Radar with tools to detect these behaviors across the customer lifecycle. ## Account Abuse at Sign-Up - Users create multiple accounts to repeat free trials, reuse promotional offers, or evade fraud detection. - A single payment method may be linked to dozens or hundreds of emails, IP addresses, and names. - About 20% of consumers admit to using different contact details to access promotions repeatedly; the figure rises to 29% among Gen Z and 27% among millennials. - AI companies are especially vulnerable because repeated free-tier access consumes compute resources. Stripe found suspected multiaccount abuse in 7.4% of AI-company sign-ups. - Stripe is introducing Radar capabilities to assess sign-ups and login events, helping businesses distinguish genuine prospects from repeat abusers. ## Free-Trial Abuse and Virtual Cards - Customers may cycle through multiple trials to extend free access beyond the stated terms. - AI startups with self-serve registration and direct API access experience 10 times more attempted abuse than enterprise AI offerings. - Blocking virtual cards is no longer an effective solution because many legitimate customers use them for privacy and security. - Stripe’s new solution predicts common trial-term abuse with 90% accuracy. - Radar also provides analytics showing blocked high-risk payments and, for businesses without the control enabled, payments that would have been blocked. ## Refund Abuse After Purchase - Customers may falsely claim that products were defective or never delivered while keeping the merchandise. - Stripe estimates global refund-abuse losses at roughly $100 billion annually. - “Wardrobing”—wearing items briefly before returning them—was admitted by 27% of shoppers who returned an online purchase, rising to 49% among Gen Z shoppers. - Social-media shopping hauls can create costs through return shipping, processing, markdowns, and unsellable inventory. - Organized abusers may use more than 100 email variations and multiple cards to bypass refund limits and “no questions asked” policies. - Because purchases often use valid credentials, the abuse may only become visible after the refund is issued. - Stripe is developing tools to identify refund abuse and is seeking preview participants. ## Stripe’s Broader Fraud-Prevention Strategy - Stripe plans to use its network data, existing AI infrastructure, and Radar to detect repeat abusers, fake-account networks, and emerging first-party fraud tactics. - The broader objective is to monitor and reduce abuse throughout registration, trial access, payment, and post-purchase refund processes. Businesses should treat first-party fraud as a lifecycle-wide risk rather than relying only on transaction-time fraud checks. More targeted, AI-based detection can reduce abuse without unnecessarily rejecting legitimate users, especially those using virtual cards.

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Fraud Prevention AI Stripe Payment Processing+3