Bills of Lading processing for a Commercial Bank

1

Business Analyst

20

Documents

4

days

98.46%

Accuracy

CHALLENGE Overview

Commodity traders and logistics providers process hundreds of Bills of Lading on a daily basis. Often it is done manually, which is prone to human errors.​

Previous attempts to automate the extraction of data from semi-structured documents had failed to meet the levels of accuracy required. ​

Working with a legacy vendor achieved only 70% accuracy after 4 months, 5000 documents, and the work of 4 data scientists.​

Client

Tier 1 Commercial Bank

Goal

Create a trained model to accurately extract data using a small number of sample documents.

WHAT WE DID

The client provided 20 data samples across 5 data variations and asked AYR to train a robust model to extract 12 fields.

  • AYR automates this classification process, leveraging capabilities such as human-in-the-loop (HITL) capability to send exceptions for specialists for review to improve future models.
  • The solution enables greater accuracy and improves employee productivity, unlocking more time to focus on higher value activities.

IMPACT