antifraud

Antifraud refers to the policies, processes, and technologies used to prevent, detect, and respond to fraudulent activity across organizations and sectors. Its aim is to reduce financial losses, protect assets, and maintain trust by addressing deception that results in unauthorized transactions, misrepresentation, or exploitation of systems.

Fraud can occur in financial services, retail and ecommerce, healthcare, government programs, and telecommunications, among others. Common forms include identity theft, payment fraud, account takeover, insurance fraud, procurement fraud, and tax or embezzlement schemes. The antifraud program typically combines risk assessment, controls, monitoring, investigation, and remediation.

Key components include prevention through access controls, segregation of duties, and know-your-customer and know-your-business processes; detection via analytics, machine learning, anomaly scoring, and rule-based systems; and response through incident management, forensic analysis, and legal action. Technologies often include fraud scoring engines, device and identity verification, payment authentication, and data sharing across trusted partners.

Regulatory and governance frameworks increasingly require antifraud controls within financial and commercial ecosystems, with standards such as AML/KYC, PCI DSS, privacy laws, and security certifications. Common challenges include data quality, balancing false positives against missed fraud, cross-jurisdictional coordination, and maintaining privacy. Effectiveness is measured by fraud loss reduction, detection rate, and time to respond.