Preference disaggregation-based multiclass Mahalanobis-Taguchi system applied to medical insurance fraud

Key Points

• Medical insurance fraud can be effectively identified using the Mahalanobis-Taguchi system, enhancing detection rates.
• In this analysis, preference disaggregation techniques reveal anomalies in claim submissions, highlighting irregular patterns.
• The methodology utilizes multiclass classification to differentiate between legitimate and fraudulent claims, increasing accuracy.
• Findings suggest high application potential for advanced fraud detection systems in healthcare settings.