AI-Assisted Document Data Extraction at a Bank

The Challenge

Operations, finance, legal and back-office teams at the bank worked with a wide range of documents, including contracts, forms, applications, requests and other operational paperwork. Before a document could move on, someone had to read it and pick out the critical fields, key information and important clauses by hand.

This manual extraction took time and created a risk of error each time details were entered into the next stage of the process. The extracted information was also not always captured in a standard, comparable format, which made it harder to work with the results consistently and slowed the handover to the next step.

The Solution

With cognipeer Studio, our team configured an AI-assisted document extraction workflow for the bank’s operational processes. Users uploaded the relevant document, and the solution identified the required fields, main information or critical clauses it contained, depending on the type of document and what the next step needed. The same approach applied across the document types the teams handled, from contracts to forms and applications.

Rather than leaving users to re-enter these details by hand, the workflow presented them in a structured format, so that documents of the same kind produced output in the same shape. The result was prepared for the next step in the operational process, with the team that uploaded the document taking it forward from there.

Implementation

1. Defined what to extract. We set out the required fields, main information and critical clauses for the document types the teams handled, from contracts and forms to applications and requests.
2. Configured document upload and interpretation. Users could upload a document directly, and the AI workflow identified the relevant information within it, whether specific fields, main details or critical clauses.
3. Standardised the output. Extracted information was returned in a consistent, structured format so that results from different documents could be compared.
4. Prepared the handover. Structured output was made ready for the next step in the operational process, with users deciding how to take it forward.

Business Impact

Document handling became more structured, from the moment a file was uploaded to the point its information was ready for the next process step. Teams spent less effort re-entering details from documents and worked from output that followed the same format each time, making it easier to compare one document with another.

• Faster document processing for the teams handling contracts, forms, applications and requests.
• Less manual data entry when moving information into the next step.
• More standard output across documents of the same type.
• More comparable results that were easier to review side by side.

Technology Behind the Solution