User Segmentation for Fraudulent Appeasement Detection

The patent segments users into different groups based on their characteristics and ordering patterns. By dividing the user base into segments (e.g., new users, frequent users, users with specific ordering behaviors), the system can apply segment-specific appeasement request rate thresholds rather than a single universal threshold. This segmentation allows the system to maintain high detection speed while improving accuracy by contextualizing each user's request rate within their specific user segment, thereby differentiating between legitimate and fraudulent activities more effectively.

The patent applies local quality by setting different appeasement request rate thresholds for different user segments rather than using a uniform threshold for all users. For example, new users may have lower thresholds while frequent users with established patterns have higher thresholds. This localized approach ensures that each user segment is evaluated against appropriate benchmarks, reducing false positives for legitimate users while maintaining high detection accuracy for fraudulent requests across different segments.

The patent performs preliminary actions by pre-segmenting users into groups based on their characteristics and pre-establishing segment-specific appeasement request rate thresholds. When a user submits an appeasement request, the system can quickly determine their segment and compare their request rate against the pre-defined threshold for that segment, rather than conducting individual investigations. This preliminary segmentation and threshold establishment significantly reduces processing time while maintaining high detection accuracy through automated segment-based evaluation.