Service Data Processing for Mobile Payment Alarm Accuracy
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Solution Overview
Problem
Existing mobile payment services face challenges in accurately identifying abnormal service data, leading to inefficient use of resources due to incorrect alarms, which are often triggered by normal fluctuations caused by events like natural disasters or traffic control.
Innovation Solution
A service data processing method that performs a secondary check on payment service data by obtaining location-specific events, determining if these events include predetermined conditions such as natural disasters or traffic control, and adjusting alarms accordingly to avoid false notifications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If service data monitoring is performed without considering local events, then monitoring coverage is comprehensive, but alarm accuracy deteriorates due to false alarms from normal fluctuations
Solution Approach 1:
The patent introduces local events as an intermediary factor between service data monitoring and alarm generation. The monitoring system queries local events (such as natural disasters, traffic control, parades) at the customer's location and uses these events as mediators to explain service data fluctuations. When a local event is detected, it serves as a justification for abnormal service data, preventing false alarms while maintaining comprehensive monitoring coverage.
2Reliability
If manual follow-up is performed for all alarm notifications, then all potential issues are investigated, but resource consumption increases significantly
Solution Approach 1:
The patent performs preliminary action by proactively querying local events before generating alarm notifications. The system obtains location information from service data, queries local events at that location, and uses the event information to pre-judge whether the service data anomaly is caused by external factors. This preliminary check filters out false alarms before they reach human operators, ensuring that manual follow-up resources are only allocated to genuine service issues.
3Measurement precision
If location information is obtained and local events are queried for every alarm, then alarm accuracy is improved, but processing time increases
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting the monitoring and query parameters based on service data characteristics. The system evaluates service data against service indicator ranges first, and only when anomalies are detected does it proceed to obtain location information and query local events. Additionally, the system considers the level and duration of local events to determine whether they sufficiently explain the service data anomaly, optimizing the query process by avoiding unnecessary location lookups for normal service variations.
Data Source
AI summary
One or more computing devices obtains service data of a user payment service. The one or more computing devices determines whether the service data of the user payment service falls within a service indicator range. In response to determining that the service data does not fall within the service indicator range, the one or more computing devices obtains location information of a target customer corresponding to the service data. The one or more computing devices obtains one or more local events corresponding to the location information. The one or more computing devices determines, based on the one or more local events, whether to output an alarm for the service data. In response to determining to output the alarm for the service data, the one or more computing devices outputs the alarm for the service data.