AntWorks Case Studies Airline Company Streamlines Invoice Processing with AI

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	Airline Company Streamlines Invoice Processing with AI AntWorks

Airline Company Streamlines Invoice Processing with AI

AntWorks

Technology Category	Analytics & Modeling - Machine Learning Networks & Connectivity - RFID
Applicable Industries	Equipment & Machinery Transportation
Use Cases	Time Sensitive Networking Traffic Monitoring
Services	Data Science Services System Integration
Challenge	The customer, a leading low-cost airline in East Asia, was grappling with the challenge of processing approximately 2,000 invoices each month, each ranging from 100 to 200 pages in length. The invoices, coming from over a thousand suppliers, arrived in a wide array of formats. The task of manually extracting data from each invoice and processing it into the airline's BPM system was repetitive and time-consuming. The addition of new destinations only increased the volume of suppliers and invoices, further complicating the process. The airline's pre-existing OCR platform struggled with the variability of the invoice formats and required constant intervention. The frequent changes to these documents made a template-based automation approach difficult. The company was in need of an AI-based solution that didn't require data science expertise. Read More
About Customer	The customer is one of East Asia’s leading low-cost airlines, serving medium and long-haul routes. The airline is committed to making travel and the new experiences it offers accessible to all. As the airline continues to expand, adding new destinations, the volume of suppliers and invoices to be processed increases. The airline was in need of a solution that could handle the increasing volume and variability of invoices, and streamline the data extraction and processing into its BPM system. Read More
Solution	The airline adopted Cognitive Machine Reading (CMR), a blend of AI, Machine Learning, and pattern recognition. CMR captures invoices from Service Now, a service ticketing tool, and emulates human data processing methods to extract key data elements. It categorizes invoices and provides curated data for downstream systems. Built-in workflows route data to designated systems according to business rules. CMR automatically flags missing or unreadable information as exceptions and routes tasks to the right person. Each manual intervention improves the system’s accuracy. Multiple reports are available for further analysis, providing a comprehensive solution to the airline's invoice processing challenges. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Machine Learning

Networks & Connectivity - RFID

Applicable Industries

Equipment & Machinery

Transportation

Use Cases

Time Sensitive Networking

Traffic Monitoring

Services

Data Science Services

System Integration

Challenge

The customer, a leading low-cost airline in East Asia, was grappling with the challenge of processing approximately 2,000 invoices each month, each ranging from 100 to 200 pages in length. The invoices, coming from over a thousand suppliers, arrived in a wide array of formats. The task of manually extracting data from each invoice and processing it into the airline's BPM system was repetitive and time-consuming. The addition of new destinations only increased the volume of suppliers and invoices, further complicating the process. The airline's pre-existing OCR platform struggled with the variability of the invoice formats and required constant intervention. The frequent changes to these documents made a template-based automation approach difficult. The company was in need of an AI-based solution that didn't require data science expertise.

About Customer

The customer is one of East Asia’s leading low-cost airlines, serving medium and long-haul routes. The airline is committed to making travel and the new experiences it offers accessible to all. As the airline continues to expand, adding new destinations, the volume of suppliers and invoices to be processed increases. The airline was in need of a solution that could handle the increasing volume and variability of invoices, and streamline the data extraction and processing into its BPM system.

Solution

The airline adopted Cognitive Machine Reading (CMR), a blend of AI, Machine Learning, and pattern recognition. CMR captures invoices from Service Now, a service ticketing tool, and emulates human data processing methods to extract key data elements. It categorizes invoices and provides curated data for downstream systems. Built-in workflows route data to designated systems according to business rules. CMR automatically flags missing or unreadable information as exceptions and routes tasks to the right person. Each manual intervention improves the system’s accuracy. Multiple reports are available for further analysis, providing a comprehensive solution to the airline's invoice processing challenges.

Impact #1	The implementation of CMR led to significant improvements in the airline's invoice processing operations. The system's ability to flag missing or unreadable information as exceptions and route tasks to the right person reduced the time spent handling exceptions. The increase in conversion accuracy rate led to fewer hours spent on exception handling, and workforce productivity grew, ensuring the correct payments were made. The transformation project underpins the company’s sustainability, ensuring processes remain efficient as it grows. The airline continues to use AntWorks’ technology to create a highly collaborative, efficient, and integrated enterprise.

Impact #1

The implementation of CMR led to significant improvements in the airline's invoice processing operations. The system's ability to flag missing or unreadable information as exceptions and route tasks to the right person reduced the time spent handling exceptions. The increase in conversion accuracy rate led to fewer hours spent on exception handling, and workforce productivity grew, ensuring the correct payments were made. The transformation project underpins the company’s sustainability, ensuring processes remain efficient as it grows. The airline continues to use AntWorks’ technology to create a highly collaborative, efficient, and integrated enterprise.

Benefit #1	The airline experienced an increase of over 85% in their conversion accuracy rate.
Benefit #2	The overall invoice processing time was reduced by 33%.
Benefit #3	The total effort to create a bill in the airline’s system was reduced by 50%.

Benefit #1

The airline experienced an increase of over 85% in their conversion accuracy rate.

Benefit #2

The overall invoice processing time was reduced by 33%.

Benefit #3

The total effort to create a bill in the airline’s system was reduced by 50%.

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Overview

Airline Company Streamlines Invoice Processing with AI

Operational Impact

Quantitative Benefit