Automated M2M Billing Reconciliation Engine
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Solution Overview
Problem
Current M2M billing systems face challenges in accurately identifying and resolving billing discrepancies, leading to potential revenue leakage and manual intensive reconciliation processes that are time-consuming and prone to errors.
Innovation Solution
A computer-implemented method and system that includes a reconciliation engine to compare application usage information and cloud service usage information for discrepancies, enabling automated reconciliation and reporting, thereby streamlining the billing process and reducing manual interventions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated reconciliation is implemented, then productivity and accuracy of billing reconciliation are improved, but device complexity increases
Solution Approach 1:
The billing reconciliation system is segmented into distinct functional modules: a usage data reception module that collects data from multiple sources, a comparison module that identifies discrepancies, and a reporting module that generates reconciliation reports. This segmentation improves productivity by enabling specialized processing in each module while managing complexity through modular design.
Solution Approach 2:
The patent introduces an intermediary reconciliation system that acts as a mediator between usage data sources and billing systems. This intermediary automatically compares usage data against billing records, identifies discrepancies, and generates reports, thereby improving reconciliation efficiency without requiring direct complex integration between all system components.
2Loss of time
If manual reconciliation processes are used, then device complexity is reduced, but loss of time and productivity decrease
Solution Approach 1:
The reconciliation system performs self-service by automatically comparing usage data against billing records without requiring manual intervention. The system autonomously identifies discrepancies, determines their nature, and generates reconciliation reports, thereby eliminating time losses associated with manual processes while maintaining manageable complexity through automated rule-based logic.
3Reliability
If comprehensive discrepancy identification is performed, then reliability of billing accuracy is improved, but device complexity increases
Solution Approach 1:
The system implements feedback mechanisms where discrepancy identification results are fed back into the billing process for correction. The reconciliation module continuously monitors and compares usage data, providing feedback on billing accuracy and enabling ongoing improvements in reliability while managing complexity through iterative refinement rather than comprehensive simultaneous analysis.
Solution Approach 2:
The patent replaces manual mechanical reconciliation processes with automated electronic comparison systems. The system uses computer-based algorithms to automatically compare usage data against billing records, identifying discrepancies with high reliability while reducing the complexity associated with manual human analysis and intervention.
4Loss of time
If automated discrepancy identification is implemented, then loss of time is reduced, but device complexity increases
Solution Approach 1:
The system performs preliminary actions by continuously monitoring and pre-comparing usage data as it is received, rather than waiting for manual initiation of reconciliation processes. This preliminary automated comparison quickly identifies discrepancies in near-real-time, reducing detection time while managing complexity through event-driven processing that activates only when relevant data is available.
Data Source
AI summary
The present invention is directed toward networks and more particularly to a method and system for providing information related to reconciliation billing in such networks. In one more embodiments, the computer implemented method for identifying discrepancies in billable events includes receiving application usage information regarding the one or more billable activities for one or more devices from an application provider core by a billing and analytic system; receiving cloud service usage information regarding the one or more billable activities for the one or more devices from a cloud operator providing cloud services by a billing and analytic system; comparing the received application usage information and the received cloud service usage information for one or more discrepancies in relation to one or more billable activities by a reconciliation engine; and reporting one or more identified discrepancies in accordance with the one or more billable activities.