Minimizing time-consuming tasks using OCR based on ML and AI

Case study / Optimization / Management / Planning / Monitoring / Digital transformation / Banks

Building workflow to minimize time-consuming tasks by applying optical character recognition (OCR) technology based on machine learning (ML) and artificial intelligence (AI).

One of the most time-consuming tasks for bankers undoubtedly will be reporting. For opening an account, for dealing with insurance or with a loan, supporting documents are always to be created.

Good news: solutions to fight hours of reporting exist! One of them is Young App automation platform.

Today, applying the best practices of OCR, ML, and AI technologies, companies could improve their effectiveness by minimizing time-consuming tasks.

Challenge

  • Quickly extract and aggregate large volumes of data.

Solution

  • Install connectors allowing to read account statements or invoices by applying OCR, ML, and AI.

  • Implement connectors to automate bank transactions.

Used connectors

Amazon S3
Amazon S3
ROSSUM
ROSSUM
CSV
CSV

Workflow

(1) Save documents to Amazon S3.

(2) Extract data with ROSSUM’s OCR.

(3) Export data to CSV format.

Results

The workflow quickly extracts data by applying OCR, and by this, significantly saving bankers’ time. From now, no need to spend hours reading and re-typing or copy-pasting information from administrative documents.

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