Convert PDF Bank Statements to Excel

Prithiv Sassisegarane

Published in

NanoNets

4 min readMay 28, 2021

Originally published at https://nanonets.com on May 28, 2021.

Why Convert Bank Statements to Excel

In the current era where almost all business transactions are digitized, it is important to convert bank statements to Excel, csv or other structured file formats. Such digitization is vital for producing reports, presentations, archiving of records, and making data in these documents machine-readable.

Most bank transactions are now online, and this includes the issuance and receipts of bank statements by banking customers. From passbook entries and printouts of monthly statements, we have moved to online statements that are sent to the recipient’s email inbox or downloadable from bank websites after appropriate verifications.

Emailed or downloaded bank statements are often in the form of password-protected PDF documents. These documents serve best as a repository of transactions; extracting or editing the data is extremely cumbersome. Organizations often look to convert such documents to editable formats like Excel, csv etc. for downstream integration into ERP software.

Converting a PDF bank statement to Excel or converting a PDF to csv can be complicated and time-consuming. This is to be expected because bank statements are designed to be tamper-proof. A simple copy-paste from PDF documents will not work. This process gets more hectic when dealing with printed bank statements; as they will additionally need to be scanned! Renaming PDF files based on content is another time-consuming task that businesses face!

Optical Character Recognition (OCR) software, like Nanonets, can convert images, PDFs and other non-editable files into structured editable formats (Excel, csv etc.) — check out this cool image to Excel tool.

Various OCR software are available today with varying levels of sophistication. The simplest OCR tools simply extract the data/text with no attention to the original presentation/order of data. Advanced AI-based OCR software like Nanonets can recognize text, data, tables, graphs and such other elements in documents and only extract relevant data.

Nanonets’ PDF scraper OCR is particularly useful for converting bank statements into machine-readable structured data formats such as excel files (cvs, XML, JSON etc.). Such structured data can be conveniently included and processed in automated workflows. Automated processing & management of bank statements can streamline a company’s financial operations and avoid delays or errors.

How to Convert Bank Statements to Excel with Nanonets

Converting PDF bank statements to Excel or CSV is pretty straightforward with Nanonets. Nanonets offers 2 methods to convert PDF documents to Excel:

Custom Nanonets OCR Model

If your use case isn’t covered by any of Nanonets’ pre-trained OCR models, build a custom OCR model that suits your specific data extraction requirements. Build, train & deploy a custom OCR for any document type across a range of languages in just under 25 minutes.

Here are the detailed steps to create a custom OCR model to convert bank statements from PDF to Excel:

Login to Nanonets & select “Create Your Own” to build a custom OCR model
Upload sample PDF bank statements to serve as a training set for Nanonets’ algorithms
Annotate the PDF bank statements to train Nanonets’ algorithms to identify the important/relevant transactions in the sample bank statements
Build the custom OCR model — Nanonets leverages deep learning to build various OCR models and tests them against each other to pick the most accurate one
Test & verify — Add a couple of real bank statements to check whether the custom OCR model works well
Export — If the transactions/data have been recognized, extracted and presented correctly, then export the file — download the data extracted from the PDF statements as an Excel, csv, JSON or XML output

Here’s a quick demo on how to build a custom OCR model with Nanonets. Although this example focuses on passports as the document of interest, the steps apply to bank statements as well:

Nanonets API

If you’re looking to train/build your own application to convert PDF bank statements to Excel, check out the Nanonets API. The Nanonets API documentation provides readymade code samples in Shell, Ruby, Golang, Java, C# and Python, as well as detailed API specs for different endpoints.

Details of the process may be obtained here.

Benefits of Converting Bank Statements with Nanonets

Nanonets is ideally placed to convert PDF bank statements into Excel sheets. Its AI-based OCR can convert scanned/PDF statements into structured formats like Excel, XML, csv, JSON, and more.

This helps transform human-readable PDF statements into structured machine-readable digital data.

Here are some specific advantages of using Nanonets to convert bank statements to csv or Excel:

Flexibility: Nanonets’ deep learning algorithms can easily handle handwritten text, multiple languages, images with low resolution, images with new or cursive fonts and varying sizes, images with shadowy text, tilted text, random unstructured text, image noise, blurred images and many more common data constraints.
Customizability: The use of proprietary/custom data to train Nanonets’ OCR models helps meet specific business requirements. Bank statement formats differ based on the bank and the type of account.
Adaptability to changes: The possibility to easily re-train existing models with new data allows Nanonets’ OCR models to adapt to unforeseen changes.
Detection of tables: Automatic detection of tables including structured row-column information is particularly useful for bank statement digitization.
No post-processing needed: the extraction of relevant data and their automatic sorting into intelligently structured fields minimizes manual post-processing.
Works with non-English or multiple languages. This feature is important for multinational operators who work across national borders.
Ease of use, batch processing of multiple documents and seamless 2-way integration with multiple accounting software.