REAL-WORLD SUCCESS

Optical Character Recognition (OCR) Implications for
Financial Services Case Study

Introduction

OCR can play a pivotal role in most industries and is incredibly impactful within financial services, where efficient data management and analysis are paramount. Key enhancements of OCR within financial services may include:

  • Efficiency: Improve operational efficiency and faster transaction processing times.
  • Accuracy: Streamline data integrity and compliance with regulatory requirements, reducing the likelihood of costly mistakes.
  • Visibility: Leverage unstructured data to improve fraud detection, customer insights, and analytics.

In this brief case study, we will explore our client's challenges and results from a recent project, showcasing OCR's impact.

Problem/Goal

The client had a vast collection of historical records originally processed using now outdated 2005 OCR technology. Facing difficulties with text recognition quality, which significantly impacted the accuracy and accessibility of their archives, they sought experts' assistance. Their goal was to enhance the OCR quality while reducing the processing time and cost, which were quite high.

Solution

Our team at StandardData chose to implement an advanced, open-source OCR model, drastically improving the text recognition quality. This model effectively transformed previously unreadable records into clear, searchable text. Additionally, using open-source OCR provided more flexibility than compared to a proprietary model that may become obsolete in the near future. We migrated their system to Amazon Web Services (AWS) to improve processing efficiency, utilizing a serverless architecture. This allowed us to distribute the processing across hundreds and even thousands of machines, working in parallel, which significantly accelerated the OCR process.

In conclusion, OCR technology offers a range of benefits, specifically within the financial services industry, which can result in increased efficiency, improved compliance, enhanced data analysis, and better integration. As institutions continue to embrace digital transformation, OCR technology will play an increasingly vital role in driving innovation and competitiveness in the sector.

Results

10X improvement in OCR quality:
Successfully converted previously unreadable records into fully legible text.
94% reduction in cost:
Reduced from $300 per batch to $20 per batch of records.
99% speed improvement:
Improved batch processing time from 3 weeks to 1 hour.