Cognitive Automation for Account Receivable Automation in A Logistics Company

Description of Problem:

There were various manual tasks in the Accounting Department of the Client’s company. The staff needs a month to transfer data from excel files to their accounting software.

1. Accounts Receivable Processing

There are three types of accounts receivable documents: Statement Document, Credit Memo, and Official Receipt.

  • The staff needs to manually transfer thousands of partners’ ordering data from excel files to their accounting software.
  • The staff needs to manually check whether the partner has any accounts receivable documents.

2. Overdue Reminder

There are two types of overdue reminder templates. Type 1, means the partner has one month overdue. Type 2, means the partner has two months overdue.

  • The staff needs to manually transfer hundreds of partners’ accounts receivable data from excel files to their accounting software.
  • The staff needs to manually send overdue reminders to partners using the Type 1 and Type 2 templates.

How Gleematic software helps:

  1. Gleematic is able to enter thousands of partners’ data to accounting software 24/7. The data entry tasks that usually take weeks or even months to be done, Gleematic is able to do it in just 3-4 days.
  2. With Machine Learning, Gleematic is able to classify the data into several types of labels. Then automatically send out overdue reminder emails using Type 1 and Type 2 templates.
  3. Gleematic then sends back the report of labeled excel files and overdue reminder attachments to the Accounting Department.

Challenges:

  1. The accounts receivable amount of each partner may vary. The ones with a long list of accounts need more time to be done. We managed to set a time limit to prevent errors.
  2. The client uses very hierarchical file management for it some sub-companies folders. We managed to use some logics to prevent errors.

Benefits:

  • Shorter Time of completion: Gleematic cognitive automation works up to 5 times faster than humans.
  • High Accuracy: Almost 100% accurate. There would be no human-errors of missing data, uploading wrongly, or having duplicated files in the archival process.
  • FTE Saving: ~3 to 4 FTEs
  • Saves precious hours of humans: As the human-users would only have to monitor the robot’s progress, he/she can spend most of his/her time on other more important things.
  • Reduced stress on staff: As the staff (humans) need not attend to this mundane and repetitive yet detailed work, they would have less stress and be more motivated to do other value-added jobs.  

Description of Client:

The client is a major automotive distributor company with various kinds of products.

Industry: 

Logistics