Each model used by the Attestiv platform is tested to a minimum of 97% AUC and biased toward false negatives to try to avoid false positives. However, each model is trained on certain types of anomalies or potential fraud and is not all-encompassing. We strive to identify new threats and include them as part of our analysis as soon as we can.