The Environmental Policy Integrated Climate (EPIC) model was modified to include hail weather events, completing modification needed to simulate the four most frequent causes of crop yield loss (hail, too wet, too cold, too dry) in the Kansas crop insurance program. Yields were simulated for...

The analysis was conducted on the USDA's Risk Management Agency insurance data and NRCS Land Resource Regions from 1994 - 2001 to assist RMA in improving program integrity. The objective is to develop a data-mining algorithm that identifies anomalous producers and counties within LRRs based upon...

This article analyzes anomalous patterns of agent, adjuster, and producer claim outcomes and determines the most likely pattern of collusion that is suggestive of fraud, waste, and abuse in the federal crop insurance program. Log-linear analysis of Poisson-distributed counts of anomalous...

Defines data mining as the extraction of potentially useful information from large databases. Shows how data mining can be applied to detecting anomalous behaviour in American agriculture and thus support the Risk Protection Agency in its compliance mission to detect fraud in crop insurance,...