Cognitive Automation
for Accounts Receivable

Reduces running costs and errors simultaneously.

Description of Problem

There were various manual tasks in the Accounting Department of the Client’s company. The staff was spending may hours (almost) every day to transfer data from various types of files to their accounting software.

Accounts Receivable Processing

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

  • The staff needs to manually transfer hundreds 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.

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.

Client Overview:

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

Industry:

Logistics

Processes Type:

Accounts Receivable Processing

How Gleematic Helps

Gleematic is able to enter hundreds of partners’ data to accounting software round the clock. The data entry tasks that usually takes about two weeks every month to complete is done by Gleematic is able to do it in just 3-4 days.

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.

Gleematic then sends back the report of labeled excel files and overdue reminder attachments to the Accounting Department.

Results

neuromorphic-computing

Degree of Robotization: 75% Effort Automated

financial-statement

ROI: 3 Months

Human Error Rate Reduced

tester

Manual Effort Reduction to 75%

real-time

Faster Processing Time: Reduction of 65%

workflow

More Standardization

information-technology

High-Quality Improvement

working-hours

No More Repetitive Administration

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