Convert Bank Statements to JSON

Bank statements show all the money going in and out of a bank account over a certain time period. They have detailed info about transactions for people and businesses.

Getting Data from Bank Statement PDFs

Konbert is really good at handling bank statement PDFs. We can accurately pull out and organize data from many different bank statement formats. This makes it much easier to analyze and manage your financial information.

Here are some things our bank statement extraction can do:

• Accurately identify transaction details like dates, descriptions, and amounts
• Smartly categorize income and expenses
• Pull out account summaries, including starting and ending balances
• Handle multiple account statements in one PDF
• Work with different statement layouts from various banks

People often use bank statement conversion for:

• Managing personal finances and budgeting
• Tracking expenses for taxes
• Financial analysis for small businesses and freelancers
• Automating bookkeeping and accounting
• Preparing financial reports for loans or mortgages

By changing your bank statement PDFs into easier formats like CSV or Excel, you can quickly bring your financial data into accounting software or personal finance tools for more analysis and management.

JSON (JavaScript Object Notation) is a lightweight data format that uses human-readable text to store and transmit data objects. It's widely used for data exchange between web applications and servers, API responses, configuration files, and data storage.

Technical Details

JSON represents data with key-value pairs in a nested structure. It supports strings, numbers, booleans, arrays, objects, and null values, making it flexible for various data types. JSON is language-independent but derived from JavaScript syntax, making it particularly popular in web development. JSON files use the .json extension and have a MIME type of application/json.

Advantages

• Supports complex, nested data structures
• Native support in JavaScript and most modern programming languages
• Self-describing and human-readable
• Compact compared to XML and other structured formats
• Language-independent and widely adopted as a standard
• Perfect for API responses and data transfer
• No special parsing tools needed - standard in most programming languages

Limitations

• Not ideal for tabular data analysis
• No support for comments or metadata
• Can be verbose for large datasets
• No schema validation built into the format itself
• Nested structures can be difficult to analyze in spreadsheet tools
• Converting to tabular formats requires flattening of nested objects