A bank statement is an official document that records transaction history of a bank account, including deposits, withdrawals, transfers, and payments. However, manually processing these large datasets can be time-consuming and error-prone, which is why automated bank statement extraction is very much needed to ensure accuracy and timeliness.
Bank statement extraction leverages OCR (Optical Character Recognition) technology to help you collect data faster. It extracts hundred transactions from bank statements only in minutes—work that would take a human hours to do manually. By automatically capturing data, bank statement extraction generates machine-readable datasets that are easier for businesses to process and utilize.
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We can’t talk about bank statement extraction without mentioning OCR. This technology drives the process of examining data in bank statements. It enables the recognition and structuring of financial data from various bank statement formats, such as PDFs, images, or scanned documents. Here’s a summarized flow of how it works:
- Data Capture: OCR scans the uploaded bank statement and extracts all relevant details, from account information to transaction records.
- Data Labeling & Categorization: Each extracted data point is assigned and categorized into relevant fields, resulting in structured data ready for further use.
- Data Integration: Seamless integration of the processed data into existing systems, enabling a smooth and automated workflow.
Use case examples
Given its detailed financial records, bank statements are often used in various business fields. Whether for financial reconciliation in accounting, income verification in the real estate, or risk assessment during loan underwriting. A wide range of bank statement processing shows how bank statement extraction can be implemented across business use cases.
- Financial reconciliation
Financial reconciliation is the accounting process of matching transactions between two data sources, such as general ledger and bank statements. Bank statement extraction plays a crucial role in this process by accelerating data retrieval and minimizing error. Companies can efficiently access accurate data records of bank statements to confirm vendor payments, monitor cash flow, and maintain compliance.
In addition to payslips, bank statements are typically required as supporting documents when applying for a property rental or mortgage program. With automated bank statement extraction, verify a potential tenant’s income and evaluate their financial ability to meet payment obligations more effectively. OCR supercharges this data extraction process to provide you readily available datasets to analyze.
- Loan underwriting
Ensuring the applicant’s financial condition based on bank statements is a crucial part in loan underwriting. Automating bank statement data extraction can help lenders streamline this underwriting process, reduce the risk of missing critical financial information, while also flagging potential fraud. Lenders can save time with automation, focusing on more complex decision-making factors that impact loan approvals.
How to choose the right bank statement extraction for your business
To support optimal and accurate bank statement processing, it is essential to choose the right data extraction solution. There are several key factors to consider when choosing data extraction automation:
- Adaptability to various bank statement formats
- User-friendly interface
- Fast and flexible implementation
- High accuracy level
- Strong data security
Fintelite AI-powered OCR+ is the complete solution for your bank statement processing. Instantly extract data, detect fraud, and analyze financial trends with AI-driven precision. Fintelite transforms unstructured bank data into meaningful financial insights for better decision-making—not in hours, but automatically in minutes. Sounds like what you’ve been looking for? Contact us and book a demo to see how Fintelite AI automates bank statement processing 10x faster.
