Transaction monitoring
Transaction monitoring systems observe financial transactions continuously, looking for patterns associated with money laundering, sanctions violations, and financial crime. Unlike real-time fraud detection (which focuses on preventing individual fraudulent transactions), transaction monitoring takes a longitudinal view — identifying suspicious patterns across a customer's transaction history over time. Banks and payment companies are legally required to monitor transactions and report suspicious activity to financial intelligence units.
Identity fraud detection
Identity fraud detection focuses specifically on the fraud typologies that exploit identity — synthetic identities (fabricated personas combining real and fake data), stolen identities (using another person's credentials), account takeover (gaining unauthorised access to a legitimate account), and first-party fraud (a real person misrepresenting themselves). Identity fraud detection uses document verification, biometric checks, device intelligence, behavioural signals, and cross-reference against fraud databases to catch these patterns at onboarding and throughout the customer lifecycle.
Cybersecurity tools
Cybersecurity tools for financial services protect institutions from digital attacks — data breaches, ransomware, phishing, DDoS attacks, and insider threats. DORA, the EU's Digital Operational Resilience Act fully in force from January 2025, requires financial entities to maintain comprehensive resilience programmes including cyber threat intelligence, penetration testing, and incident response capabilities. Financial services is the most targeted sector for cyberattacks globally, making cybersecurity tooling a critical operational investment.
Payment protection
Payment protection encompasses the tools and processes that secure individual payment transactions against fraud, chargebacks, and unauthorised use. This includes 3D Secure authentication for card payments, device fingerprinting, velocity checks, geolocation verification, and machine learning models that score individual transactions for risk. Payment protection is increasingly important as instant payments reduce the window available to detect and stop fraudulent transactions before funds leave an account.
Behavioral analytics
Behavioral analytics platforms analyse how users interact with digital interfaces — typing rhythm, mouse movement, navigation patterns, swipe speed, and subtle anomalies in normal behaviour — to detect fraud, account takeover, and social engineering scams. Behavioural biometrics is particularly powerful for detecting authorised push payment (APP) fraud, where a legitimate user has been manipulated into authorising a fraudulent transaction. The user's behaviour during the session can reveal coercion or distress even when credentials are technically valid.