One of the newest members of the Azure AI portfolio, Form Recognizer, applies advanced machine learning to accurately extract text, key-value pairs, and tables from documents. With just a few samples, it tailors its understanding to supplied documents, both on-premises and in the cloud.
Introducing the new pre-built receipt capability
Form Recognizer focuses on making it simpler for companies to utilize the information hiding latent in business documents such as forms. Now we are making it easier to handle one the most commonplace documents in a business, receipts, “out of the box.” Form Recognizer’s new pre-built receipt API identifies and extracts key information on sales receipts, such as the time and date of the transaction, merchant information, the amounts of taxes, totals, and more, with no training required.
Streamlining expense reporting
Business expense reporting can be cumbersome for everyone involved in the process. Manually filling out and approving expense reports is a significant time sink for both employees and managers. Aside from productivity lost to expense reporting, there are also pain points around auditing expense reports. A solution to automatically extract merchant and transaction information from receipts can significantly reduce the manual effort of reporting and auditing expenses.
Given the proliferation of mobile cameras, modern expense reports often contain images of receipts that are faded, crumpled up, or taken in suboptimal lighting conditions. Existing receipt solutions often target high quality scanned images and are not robust enough to handle such real-world conditions.
Enhance your expense reporting process using the pre-built capability
Form Recognizer eases common pain points in expense reporting, delivering real value back to business. By using the receipt API to extract merchant and transaction information from receipts, developers can unlock new experiences in the workforce. And since the pre-built model for receipts works off the shelf without training, it reduces the speed to deployment.
For employees, expense applications leveraging Form Recognizer can pre-populate expense reports with key information extracted from receipts. This saves employees time in managing expenses and travel that they can focus on their core roles. For central teams like finance within a company, it also helps expense auditing by using the key data extracted from receipts for verification. The optical character recognition (OCR) technology behind the service can handle receipts that are captured in a wide variety of conditions, including smartphone cameras, reducing the amount of manual searching and reading of transaction documents required by auditors.
Our customer: Microsoft’s internal finance operations
The pre-built receipt functionality of Form Recognizer has already been deployed by Microsoft’s internal expense reporting tool, MSExpense, to help auditors identify potential anomalies. Using the data extracted, receipts are sorted into low, medium, or high risk of potential anomalies. This enables the auditing team to focus on high risk receipts and reduce the number of potential anomalies that go unchecked.
MSExpense also plans to leverage receipt data extraction and risk scoring to modernize the expense reporting process. Instead of identifying risky expenses during auditing, such automated processing can flag potential issues earlier in the process during the reporting or approval of the expenses. This reduces the turnaround time for processing the expense and any reimbursement.
“The pre-built receipt feature of Form Recognizer enables our application not only to scale from sampling 5 percent of receipts to 100 percent, but more importantly to streamline employee expense report experience by auto-populating/creating expense transactions, creating happy path to payment, receipt data insights to approver managers, giving employees time back to be used in value-add activities for our company. The service was simple to integrate and start seeing value.“
—Luciana Siciliano, Microsoft FinOps (MSExpense)
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