Automated Fee Refund Calculation System
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Solution Overview
Problem
Inconsistent and resource-intensive fee refund policies in financial institutions due to employee discretion, leading to inefficiencies and 'refund shopping' by customers.
Innovation Solution
A computer server system that calculates and outputs fee refund suggestions based on centralized account and customer information, including banking history and customer relationship types, ensuring uniformity and consistency in refund decisions across different branches.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If fee refund decisions are left to employee discretion, then customer service flexibility is improved, but policy consistency and resource efficiency deteriorate
Solution Approach 1:
The system segments the refund decision-making process into two parts: automated eligibility assessment based on predefined criteria, and final approval authority. This segmentation maintains policy consistency through automation while preserving employee discretion for final decisions, resolving the contradiction between flexibility and consistency.
Solution Approach 2:
The patent introduces an intermediary automated system that acts as a mediator between policy rules and employee decisions. This intermediary evaluates refund requests against predefined criteria and provides recommendations, ensuring policy consistency while allowing employees to make final judgments, thus maintaining both consistency and flexibility.
2Reliability
If employee training on refund policy is intensified, then policy understanding is improved, but training costs and time investment increase
Solution Approach 1:
The system enables self-service through automated policy interpretation and application. Employees no longer need extensive training to understand complex refund policies because the system automatically applies predefined criteria to each request, providing clear guidance and reducing the time investment required for training while maintaining reliable policy understanding.
3Measurement precision
If employees are given access to comprehensive customer information, then refund decision accuracy is improved, but system complexity and resource requirements increase
Solution Approach 1:
The patent extracts and isolates only the specific customer information and criteria relevant to refund decisions from the broader customer database. By taking out only the necessary data elements needed for accurate refund assessment, the system achieves precise decision-making without requiring access to or management of comprehensive customer information, thus reducing system complexity.
4Device complexity
If manual refund processing is used, then system simplicity is maintained, but productivity and resource efficiency deteriorate
Solution Approach 1:
The patent implements a dynamic hybrid system that adapts its processing mode based on request characteristics. Routine refund requests are automatically processed to maintain high productivity, while complex cases are routed to employees for manual review. This dynamic approach optimizes processing speed without requiring complete system complexity, achieving productivity improvements while maintaining operational simplicity.
Data Source
AI summary
A business may uniformly calculate and offer a fee refund to customers requesting refunds for fees charged to the customers' accounts. Rather than relying on individual employee discretion, a server may use account information and customer information to generate the fee refund amount to be offered to the customer. The calculated refund amount may be based on a variety of considerations including, but not limited to, the amount the account is overdrawn, the profitability of the account, the number of occurrences of charged fees, and/or other factors such as family relationships to other bank customers. Additionally, a fee refund offer may be stored and referred to when the customer subsequently requests a refund.