Case Study
Published February 5, 2025
Banks Fraud Management Identity
A top bank struggled to efficiently stop evolving fraud attacks. Fraudsters incurred unnecessary expenses as they worked downstream in the bank’s onboarding flow, with some even beating the bank’s defense’s entirely. After implementing behavioral analytics, the bank was able to detect attacks 4x faster and stop sophisticated attacks that their other tools couldn’t.
Key Results:
- 4x faster fraud detection resulting in a 30% reduction in digital onboarding costs
- Effective detection of modern attack strategies that bypassed other fraud mitigation tools
- 40% of manually approved fraud cases identified as risky by NeuroID
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The imposter in the session: Limited structure, limitless scalability
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.
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The imposter in the session: The power of one
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
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Fraud Attack Strategy Guide
Explore how modern fraudsters use coordinated, strategic attack methods—and learn how to detect, disrupt and prevent them using behavioral intelligence and real-time insights.
Key insights:
- Fraudsters use structured attack strategies like reconnaissance, blitzes and deception to exploit weaknesses
- AI-driven bots and automation are rapidly increasing the scale and speed of fraud attacks
- Behavioral analytics reveals hidden fraud signals traditional tools miss
- Early detection and layered defenses help stop attacks before they escalate
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The imposter in the session: The hub and the hive
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