Our XAI solutions go beyond traditional pattern matching, profile segmentation and rules processing to detect fraud, providing explainability that makes AI actionable in real-world compliance.
Cognitive map for detecting 80 fraud situations. CRex uses rules-based, and probabilistic Bayesian situation assessors for fraud identification, unifying both within a single holistic fraud model, combining available data and expert knowledge within a master model for explainable fraud detection. Above, the CRex dashboard explaining impacts of identified fraudulent situations
Fraud detection requires processing vast amounts of data to uncover noncompliant transactions, with reporting that is verifiable and explainable according to applicable regulations and laws. Further, the community of taxpayers is continually evolving, with dynamic and novel evasion strategies constantly emerging.
