Current analysis on payment security, fraud prevention, AML/KYC, and PCI DSS compliance.
Fraud Detection AnalyticsScope This guide outlines how to coordinate responses when an account takeover (ATO) involves both credential compromise and monetization. It s for teams that handle ATOs separately and need a model t
Chargebacks and DisputesDigital commerce brands lost an estimated $48 billion to fraud in 2025, according to the Merchant Risk Council ’s 2026 Global eCommerce Payments Suspicious Activity Report (SAR). More revealing: refun
Fraud TypologiesThe Conventional Wisdom When ANZ warned about the rise in scam-coaching, where criminals provide victims with scripts to deceive bank security measures, the industry s immediate response was predictab
Fraud Detection AnalyticsSocial engineering is now the main driver of fraud in over half of surveyed institutions. Standard controls often miss it because the legitimate customer authorizes the payment. They re using valid cr
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Fraud Detection AnalyticsFraud prevention systems built for human-speed attacks can t keep up when criminals use AI automation. The gap between credential compromise and fraudulent use has shrunk. Card-testing attacks increas
Cryptography FundamentalsYour fraud detection model needs to analyze transaction patterns without accessing cardholder data. Here s a configuration template that uses homomorphic encryption for inference workloads, allowing y
Fraud TypologiesPurpose of This Template This template provides a structured due diligence script for your account opening team when a business applicant s state registration shows recent changes to its registered ag
Chargebacks and DisputesYour fraud team faces a critical decision: invest in stronger authentication or focus on post-session monitoring. Most teams opt for authentication, thinking it s the best way to block fraudsters. Sto
Fraud Detection AnalyticsFraud teams often find themselves puzzled when incidents occur despite having solid control frameworks. The key question is: what do you do about the risk that remains after implementing controls? Her
Fraud TypologiesThe Conventional Wisdom Your team is likely focused on AI-native attacks: prompt injection exploits, model poisoning attempts, and adversarial inputs designed to manipulate large language models. You
Chargebacks and DisputesRefund and policy abuse have overtaken payment fraud as the top threat in digital commerce, according to the Merchant Risk Council s 2026 Global eCommerce Payments Suspicious Activity Report (SAR). Th
Fraud Detection AnalyticsYou ve assembled the fraud stack: a rules engine for payments, a separate AML tool for account monitoring, a third-party device fingerprinting service, and a manual review queue that somehow became yo
Fraud Detection AnalyticsYour fraud risk assessment shouldn t be a static document updated once a year and then forgotten. It should be a dynamic tool that accurately maps your organization s exposure to fraud schemes, reflec
Fraud Detection AnalyticsAn estimated 70% of fraud is committed by insiders, yet many organizations haven t clearly defined what their internal audit function should do when fraud surfaces. Your team might be asking too much
Incident Response and SkimmingYour fraud team spots unusual transaction patterns at 2 a.m. By 9 a.m., you re in a conference room with compliance, legal, IT, and your CISO. Everyone wants answers you don t have yet. Without a stru
Regulations and StandardsEvery fraud control program operates between what machines can process and what humans can interpret. You re under pressure to block more fraud, meet regulatory mandates, and avoid false positives tha
