NSF developed a statistical predictive model and web scraper using data from the Federal Audit Clearinghouse and open source development platforms to help forecast which NSF awardees may present relatively higher risk of improper payments. This minimizes manual burden through automation and provides a more quantitative view of risk, allowing NSF better allocate its resources in risk assessment and grant monitoring activities. By using open source code and free technologies, the bulk of this model is transferable to other agencies and can be customized to accommodate specific program risk factors and help address Payment Integrity Information Act of 2019 (PIIA) compliance requirements