Streamlining Data

Case study


A publicly traded company in the insurance industry faced a significant challenge in efficiently processing a high volume of various insurance forms. The company struggled with manual data entry, quality, delays, and lack of scalability. They had recently implemented automation, employing AI to perform the bulk of the entry. But some of the data being extracted from the source documents had errors and using their existing teams to review the data was proving costly and ineffective. To address these challenges and improve operational efficiency, they partnered with EMAYA.

Client Objectives
  • Streamline the data processing workflow.
  • Reduce errors and improve data accuracy.
  • Accelerate processing to improve customer satisfaction.
  • Enhance overall operational efficiency and cost-effectiveness.
Fluctuating Data Volume

The company dealt with 30% to 40% swings in the volume of insurance documents daily, leading to bottlenecks in the verification of the data for claims, customer onboarding, etc. leading to slower processing times.

Data Accuracy

Although automation had been fully implemented some data needed to be entered manually. The client’s existing teams had issues maintaining quality and the inaccuracies led to claim processing errors, customer dissatisfaction, and financial losses.

Resource Constraints

Allocating in-house resources for data processing was also not cost-effective and hindered the scalability of operations.


Delays in claims processing led to longer wait times for customers, affecting their experience and perception of the company.

EMAYA's Solutions

EMAYA collaborated closely with the client to develop a tailored solution to address their specific data processing challenges.

  • Data Validation
  • Through automated validation algorithms and manual quality checks, EMAYA ensured the accuracy and completeness of extracted data before it was entered into the client’s systems.

  • Scalability
  • EMAYA provided a flexible and scalable solution that could handle fluctuating volumes of document data without compromising on accuracy or speed. For teams of 5 or more, EMAYA assigns one or more dedicated bench resources, an unbilled agent used to provide coverage in case there are attendance events (sick days, vacations etc.). These bench resources can also be utilized for other tasks such as QA auditing or to assist their teams when there is high volume.

  • Process Optimization
  • EMAYA helped redesign the data processing workflow to minimize bottlenecks, reduce redundant tasks, and streamline the overall claims processing cycle. An emphasis was put on quality and a target of 99.9% accuracy was set for all claims during the post-processing quality checks.

    The Results
  • Enhanced Data Accuracy
  • With automated data extraction and manual validation, the accuracy of processed data improved to over 99%, reducing errors and customer disputes.

  • Reduction in Claims Processing times
  • The time taken to process insurance claims was reduced by 20%, leading to faster claim settlements and improved customer satisfaction.

  • Operational Efficiency
  • By working with EMAYA, the client was able to allocate its in-house resources more strategically, focusing on higher-value tasks.

  • Scalability
  • EMAYA's solution accommodated fluctuations in document volume, allowing the client to handle peak periods without compromising on accuracy or efficiency. By utilizing bench resources on days when their volume was high, processing times decreased for projects and reduced the overall cost per claim for the client.

  • Cost Savings
  • The streamlined process and reduced error rates resulted in cost savings related to customer disputes.