Pending Transaction Augmentation for Expense Tracking
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Solution Overview
Problem
Current systems for tracking employee expenses are error-prone due to the inability to electronically append information to transactions in real-time, leading to lost receipts, memory lapses, and unreliable optical character recognition, resulting in increased overhead costs and disruptions.
Innovation Solution
A method and system for pending transaction augmentation that includes receiving transaction authorization, requesting and storing purchase information, analyzing receipt image data using OCR, and automatically attaching this information to corresponding posted transactions, allowing real-time data capture and association with financial account transactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If employees manually append receipt information to transactions days or weeks after the expense, then the system can capture transaction data, but the process becomes error-prone and time-consuming due to faded memories and lost receipts
Solution Approach 1:
The system performs preliminary action by capturing receipt images and appending them to pending transactions in real-time at the point of sale, before the transaction is finalized or days later when memory fades. The receipt capture occurs immediately when the employee presents the receipt, eliminating the time delay and associated errors.
Solution Approach 2:
The system provides feedback by automatically detecting pending transactions and prompting employees to attach receipts at the moment of transaction occurrence. This real-time feedback loop ensures immediate capture of expense information while it is fresh, preventing the errors associated with delayed manual entry.
2Extent of automation
If the system uses optical character recognition to match receipts to settled transactions, then automatic matching is achieved, but reliability drops below 85% due to difficult deciphering of handwriting, old paper, and idiosyncratic formatting
Solution Approach 1:
The system performs preliminary action by capturing receipt images at the time of the transaction and attaching them to pending transactions before settlement. This eliminates the need for later OCR-based matching of settled transactions, as the receipt is already associated with the correct transaction in real-time.
Solution Approach 2:
The system uses an intermediary approach by introducing a pending transaction database as a bridge between real-time transactions and final settlement. Receipts are captured and stored with pending transactions, which then automatically link to settled transactions through the pending transaction record, bypassing unreliable OCR matching entirely.
3Reliability
If pending transactions are not connected with posted transactions, then real-time transaction checking is maintained, but identifying pairs of pending and posted transactions becomes complex and error-prone
Solution Approach 1:
The system performs preliminary action by capturing receipt information and attaching it to the pending transaction record at the time of purchase. This creates a complete transaction profile upfront, eliminating the need for complex post-settlement matching and reducing errors in identifying corresponding transactions.
Solution Approach 2:
The system provides feedback by automatically detecting when a pending transaction settles and prompting the employee to attach the receipt at that moment. This real-time feedback mechanism simplifies the matching process by ensuring the receipt is attached to the correct pending transaction before settlement, eliminating post-settlement matching complexity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This solution reduces errors and overhead costs by enabling real-time transaction augmentation, improving the accuracy of expense tracking and reimbursement processes, and minimizing disruptions by linking receipt data directly to corresponding transactions.
Implementation Method 1
analyzing receipt image data using optical character recognition
Data Source
AI summary
A method including: receiving an indication of a transaction authorization of a pending transaction, the transaction authorization being requested using a financial account associated with a user; outputting for transmission, to a user device associated with the user, a request for purchase information corresponding to the pending transaction; receiving, from the user device, receipt image data corresponding to a receipt related the pending transaction; storing data indicative of the receipt in correspondence with the pending transaction; determining, based on analyzing a plurality of posted transactions of the financial account, a first posted transaction corresponding to the pending transaction; and storing the data indicative of the receipt in correspondence with the first posted transaction.