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Dive into a large-scale account takeover (ATO) attack where loosely coordinated fraudsters use low-touch logins to validate credentials and harvest data across 100+ accounts. Learn how unstructured fraud rings achieve rapid scale, why behavior is the hardest signal to fake, and how multidimensional analysis exposes hidden connections to stop attacks early.

See how a single attacker leveraged fraud ring tactics to compromise over 50 accounts in under 30 days—and how to detect and stop solo account takeover attacks at scale.

Key insights:

• Lone fraudsters can replicate fraud ring tactics using playbooks, tools and stolen credentials
• A single device can target dozens of accounts rapidly with consistent, repeatable actions
• Behavioral, device and location signals help distinguish imposters from legitimate users
• Stopping high-risk devices early prevents attacks from scaling across multiple accounts

Uncover a coordinated account takeover fraud ring in action and learn how it was stopped using behavioral, device and network intelligence.

Key insights:

• Fraud rings operate with structured roles to efficiently execute account takeover attacks
• Compromised accounts can be connected across devices, revealing coordinated activity
• Behavioral, device and network intelligence expose fraud signals traditional tools miss
• Stopping ATO requires identifying and dismantling the full fraud ring, not just individual logins

Recoveries hinge on knowing who can pay, not just who owes. This infographic explores how debt buyers and collections agencies can better identify signals of true payment capacity.

Did you know?

• U.S. household debt surpassed $18 trillion in Q3 2025.¹
• The average age of debt in collections is ~3.5 years.²
• The average recovery rate on delinquent accounts is ~20%.³

Read the infographic for more insights and strategies to drive smarter recoveries.

¹Household Debt and Credit report, Q3 2025, Federal Reserve Bank of New York.

²Debt Collection Industry Statistics, zipdo.

³Collections Industry Statistics, Gitnux.