# multi-account abuse

Published articles for multi-account abuse.

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## iGaming Fraud Prevention: Key Strategies to Implement

DevFeed: [iGaming Fraud Prevention: Key Strategies to Implement](<https://devfeed.tech/articles/igaming-fraud-prevention-key-strategies-to-implement-20431.md>)

Original publisher: [Read original article](<https://sift.com/blog/implement-igaming-fraud-prevention/>)

Author: Ben Price

Published: 2026-09-14T21:00:00Z

Content type: article

Language: en

Sources: [Sift Science](<https://devfeed.tech/sources/sift-science.md>)

Topics: [Security, Privacy and Abuse Prevention](<https://devfeed.tech/topics/security-privacy-and-abuse-prevention.md>), [Exploit](<https://devfeed.tech/topics/exploit.md>), [math](<https://devfeed.tech/topics/math.md>)

Tags: [2025](<https://devfeed.tech/tags/2025.md>), [2026](<https://devfeed.tech/tags/2026.md>), [acquisition](<https://devfeed.tech/tags/acquisition.md>), [bonus-abuse](<https://devfeed.tech/tags/bonus-abuse.md>), [customer](<https://devfeed.tech/tags/customer.md>), [fraud-prevention](<https://devfeed.tech/tags/fraud-prevention.md>), [gaming-fraud](<https://devfeed.tech/tags/gaming-fraud.md>), [igaming](<https://devfeed.tech/tags/igaming.md>), [igaming-fraud](<https://devfeed.tech/tags/igaming-fraud.md>), [igaming-fraud-prevention](<https://devfeed.tech/tags/igaming-fraud-prevention.md>), [industrial](<https://devfeed.tech/tags/industrial.md>), [marketing](<https://devfeed.tech/tags/marketing.md>), [multi-account-abuse](<https://devfeed.tech/tags/multi-account-abuse.md>), [multi-accounting-detection](<https://devfeed.tech/tags/multi-accounting-detection.md>), [multi-accounting-fraud](<https://devfeed.tech/tags/multi-accounting-fraud.md>), [network](<https://devfeed.tech/tags/network.md>), [prevent-fraud](<https://devfeed.tech/tags/prevent-fraud.md>), [revenue](<https://devfeed.tech/tags/revenue.md>), [synthetic](<https://devfeed.tech/tags/synthetic.md>), [time](<https://devfeed.tech/tags/time.md>), [trust-and-safety](<https://devfeed.tech/tags/trust-and-safety.md>), [verification](<https://devfeed.tech/tags/verification.md>), [volume](<https://devfeed.tech/tags/volume.md>)

### AI overview

This article explains how bonus abuse and multi-accounting have become major sources of iGaming fraud. It describes fraudsters exploiting promotional offers through repeated registrations, synthetic identities, stolen credentials, device farms, residential proxies, and synthetic documents, and argues that operators should justify prevention spending by measuring protected revenue.

### Source excerpt

While every operator budgets for promotions as a customer acquisition cost, very few budget for the version of that cost that never converts into a real player. Bonus abuse and multi-accounting now account for the single largest fraud category in iGaming, making up 64% of fraud according to a recent study. But unlike chargebacks or [...] The post iGaming Fraud Prevention: Key Strategies to Implement appeared first on Sift.

## What Stripe data shows about fraud at AI startups

DevFeed: [What Stripe data shows about fraud at AI startups](<https://devfeed.tech/articles/what-stripe-data-shows-about-fraud-at-ai-startups-26921.md>)

Original publisher: [Read original article](<https://stripe.com/blog/what-stripe-data-shows-about-fraud-at-ai-startups>)

Author: Jacob Meltzer; Samuel Bakouch

Published: 2026-09-15T00:00:00Z

Content type: article

Language: en

Sources: [Stripe Blog](<https://devfeed.tech/sources/stripe-blog.md>)

Topics: [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [stripe](<https://devfeed.tech/topics/stripe.md>), [Security, Privacy and Abuse Prevention](<https://devfeed.tech/topics/security-privacy-and-abuse-prevention.md>), [multi-account abuse](<https://devfeed.tech/topics/multi-account-abuse.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [fraud](<https://devfeed.tech/tags/fraud.md>), [multi-account-abuse](<https://devfeed.tech/tags/multi-account-abuse.md>), [stripe](<https://devfeed.tech/tags/stripe.md>)

### AI overview

Stripe reports that AI startups experienced higher attempted transaction fraud and multi-account abuse than startups overall. Its data found a 4.3x higher attempted transaction fraud rate in Q3 2025, falling to 2.6x by Q1 2026.

### Source excerpt

We analyzed attempted fraud rates and customer abuse patterns on Stripe over the past year and found that AI companies faced 4.3x more fraud attempts than startups overall in Q3 2025.