Data Entry Automation

OCR extracts key details from invoices, such as vendor name, invoice number, date, and total amount. Comprehensive tools like ABBYY FlexiCapture and SAP Concur streamline accounts payable workflows by integrating OCR with accounting software, reducing processing time and human errors. 

OCR also can be used to input the information in images directly to AI such as ChatGpt, which simplifies the process of using AI in many cases. Employees can also upload receipts using mobile apps like Expensify or QuickBooks Online, where OCR extracts and categorizes expenses automatically. This eliminates the need for manual data entry and speeds up reimbursement approvals. 

OCR extracts financial data from bank statements and credit card transactions, reducing reconciliation time. Auditors use OCR to scan and analyze financial statements, contracts, and legal agreements, making it easier to search for relevant terms. 

Benefits of OCR in Accounting Reduces manual data entry errors and improves accuracy. Saves time by automating document processing and reconciliation. Enhances compliance and audit efficiency by enabling digital record-keeping and easy data retrieval. Seamlessly integrates with accounting software, reducing administrative workload. By leveraging OCR, accountants can automate repetitive tasks, improve accuracy, and focus on higher-value financial analysis and advisory roles. 

Here are some real-life examples of how AI converts unstructured date into structured data in accounting. 

Invoice Processing and Accounts Payable Automation

• Unstructured Data: Paper invoices, scanned PDFs, emails with invoice attachments.

• AI Processing: OCR extracts key details (invoice number, vendor name, date, amount) and NLP identifies invoice categories.

• Structured Output: A digital table with vendor details, due dates, and amounts, ready for integration with accounting software.

Tax Document Digitization & Compliance Checks

• Unstructured Data: Tax forms (W-2s, 1099s), regulatory documents, case law PDFs.

• AI Processing: Machine learning models classify tax forms, extract relevant figures, and check compliance with IRS rules.

• Structured Output: A structured tax filing dataset linking taxpayer details to applicable deductions.

3. Bank Statement Reconciliation

• Unstructured Data: PDF bank statements with transaction details in text format.

• AI Processing: OCR extracts transaction details, AI categorizes expenses, and cross-checks with accounting records.

• Structured Output: A structured financial ledger with categorized transactions, linked to corresponding business expenses.