AI Claim Denial
The RAALS AI Claim Denial module applies machine learning to evaluate claim validity by comparing data against contractual obligations and historical claim outcomes.
It identifies anomalies, inconsistencies, or policy breaches that may justify claim rejection — reducing manual effort and improving decision accuracy.
By learning from previous fraud cases and legitimate denials, the module refines its predictive power, helping insurers make faster, fairer, and data-backed decisions.
Automated claim evaluation: Analyzes data, documents, and rules to assess validity.
Policy alignment: Checks claims against contractual terms and insurer rules.
AI-based recommendation: Suggests approval or denial based on case context and risk score.
Reduced false positives: Differentiates between legitimate claims and suspicious ones.
Operational efficiency: Accelerates claim assessment and decision-making.