SAP Fraud Management

SAP, the world’s third-largest software company headquartered in Germany, entered cloud computing about five years ago and rapidly expanded its SaaS portfolio. To support customer integration, it developed identity services for authentication and provisioning on the SAP HANA Cloud Platform. Within SAP’s governance, risk, and compliance (GRC) portfolio, SAP Fraud Management (SAP FM) uses the speed and in-memory processing of SAP HANA to detect fraud earlier, improve detection accuracy, and adapt to evolving fraud patterns through rules and predictive analytics.

Fraud is positioned as a massive and growing challenge: typical organisations lose an estimated 5% of revenue to fraud, with the global problem estimated at US$3.5 trillion. Detection often happens without technology, and many cases are found accidentally only after losses occur. Compounding factors include increasingly sophisticated schemes, multiple heterogeneous data sources, and operational silos that impede coordinated detection and investigation. Effective fraud management therefore requires real-time detection and prevention, efficient investigation workflows, and support for compliance-driven scrutiny of suspicious transactions (e.g., anti-bribery and anti-corruption programs).

SAP FM provides end-to-end capabilities across a five-step cycle (Design, Set-up Strategies, Detection, Investigation, Performance Analysis). It monitors transactions from SAP and non-SAP operational systems (payments, purchase orders, salaries), generates alerts on anomalies, supports investigation with tools such as network analysis, enables real-time business intervention (halt/release transactions), and improves accuracy via interactive what-if calibration and simulation. Its performance is enabled by hardware trends (affordable memory, 64-bit processing, multicore architectures) that make large-scale in-memory analytics practical. SAP FM can complement SAP Process Control, which focuses on compliance and control management rather than deep, real-time fraud detection.

• SAP is headquartered in Germany and is described as the world’s third-largest software company.
• SAP entered the cloud computing space about five years ago and has grown to offer numerous SaaS solutions.
• SAP developed SAP HANA Cloud Platform Identity Authentication and SAP HANA Cloud Platform Identity Provisioning for customer integration.
• A typical organisation is estimated to lose 5% of its revenues to fraud.
• The global fraud problem is estimated at US$3.5 trillion.
• Some 43% of fraud cases are detected by accident after loss has already occurred.
• SAP Fraud Management is an analytic application powered by the SAP HANA platform.
• SAP FM addresses fraud management control in a five-step cycle: Design, Set-up Strategies, Detection, Investigation, and Performance Analysis.
• SAP FM can integrate data from both SAP and non-SAP operational systems such as payments, purchase orders, and salaries.
• SAP HANA is stated as a prerequisite for SAP Fraud Management.

• “For effective fraud management, an organisation needs an approach that detects and prevents fraud – as it happens.”
• “The right solution will help your organization keep pace with ever-changing, increasingly sophisticated criminal tactics.”
• “With the processing power of SAP HANA, an organisation can store and analyse data in local memory.”
• “This feature effectively eliminates latency issues related to transferring and loading data from the disk resulting in much faster fraud detection.”
• “In-memory computing puts the results of complex analyses and transactions at the analyst’s disposal for real-time fraud detection and prevention.”
• “Detected irregularities result in alerts indicating the anomalies found, and offer tools for further investigation, such as the Network Analysis.”
• “Real-time business integration lets you halt and release suspicious business transactions and check new business documents while being created.”
• “Calibration enables you to improve the automated detection by means of interactive what-if simulations.”
• “Shifts from manual fraud detection to event and value driven fraud management”
• “An automated and continuous detection monitoring”