English

Artificial Intelligence | Fraud & Security Intelligence | Innovation
Seema Rathor 0
Synthetic data for next-generation fraud detection in banking

Financial fraud is a high-stakes issue in banking, where schemes are becoming increasingly sophisticated and costly. As a result, detecting anomalies quickly and accurately is a top priority. But traditional data-driven fraud detection models face challenges such as data scarcity, privacy constraints, and model bias. This is where synthetic data

Advanced Analytics
Bahar Biller 0
Optimize spare parts inventory under uncertainty with SAS: A simulation-based approach

Authors: Bahar Biller, Jagdishwar Mankala, and Jinxin Yi Managing spare parts inventory is a critical aspect of asset performance management, especially in industries where equipment downtime is costly. This post, based on a real-world project with a major aircraft manufacturer, explores how to optimize spare parts inventory under uncertainty. We

Fraud & Security Intelligence | Innovation | Risk Management
Liz Goldberg 0
The cost of fraud: Protecting public funds with AI

Government productivity and transparency are hot topics, with trust in public institutions declining worldwide and global public debt levels nearing 100 percent of global gross domestic product. Managing fraud, waste and abuse (FWA) is key to public sector productivity. The British Government estimates that £39.8 billion to £58.5 billion of

Cloud | Data Management | Work & Life at SAS
Margherita Albrizio 0
SAS Enhanced Support: More than support — a true technological partnership

SAS' Enhanced Support model is structured into five progressive levels, ranging from Limited Support—designed for outdated software versions—to Premium Support, which offers the highest service standards, including enhanced SLAs, 24/7 assistance, and direct access to product experts. In particular, the combination of Extended Technical Support and Premium Support has proven to be a winning strategy for many companies undergoing modernization. This approach allows continued support for legacy environments during the migration to newer versions, minimizing operational risks and ensuring service continuity.

Advanced Analytics | Analytics | Programming Tips
Kevin Scott 0
Detecting lags in nonlinear time series with PROC TSSELECTLAG in SAS Viya

Accurately identifying lag structures between related time series is essential in public health forecasting, particularly during epidemics where delays between infections and hospitalizations affect planning. Using a simulated SEIR model and SAS Viya’s PROC TSSELECTLAG, distance correlation is shown to outperform Pearson correlation by correctly identifying nonlinear lag relationships—such as the true seven-day lag between new infections and hospital admissions.

1 2 3 318