Extracting Data from Bank Statements with Intelligent Document Processing

Solution onboarding is a critical element in ensuring quick time to value and speedy success. Since we are using machine learning systems, we’ll define an ML-tuning approach to train the solution.Solution onboarding is a critical element in ensuring quick time to value and speedy success. Since we are using machine learning systems, we’ll define an ML-tuning approach to train the solution.Solution onboarding is a critical element in ensuring quick time to value and speedy success. Since we are using machine learning systems, we’ll define an ML-tuning approach to train the solution.

What are bank statements?

A bank statement is a monthly financial document that provides a summary of the account holder’s activity. Bank statements are generally prepared by the bank for the account holder at the end of each month. Bank statements can be found online via online banking or be obtained from a branch of the bank. They are also commonly known as account statements or transaction summary statements.

What can you infer from bank statements?

Bank statements hold the data that tracks an individual's or business's cash flow. It is used to predict spending potential, document expenditure, assess income or profit, and maintain records of all transactions. A bank statement contains information about an individual’s financial health and credit reliability which is essential for all lending decisions.

What are the challenges in extracting data from bank statements?

Our client, a world leader in withholding tax recovery services, has periodic cycles throughout the year when they receive thousands of high-variation documents that need to be identified, sorted, and routed. As they depended on manual processing for this, each document took about an hour to be processed.By using Infrrd IDP for bank statement data extraction, financial companies will be able to make faster and data-driven lending decisions. Our platform provides granular-level access to the data in bank statements such as validating the recency of the statements, identifying transaction categories, and deriving values based on pre-set conditions.