Extended Testing as Service Team

Introduction

A 5 billion dollar clinical research market leader in Ireland.

Background

Client faced challenges in maintaining a dedicated in-house testing team to meet the demands of their growing project portfolio.

Problem Statement

  • Testing Scalability
  • Growing accusations needed lot of consolidation of core systems.

  • Quality Assurance Alignment
  • One of the key challenges was aligning the quality assurance practices with the internal quality standards.

  • Communication and Feedback Loop
  • Establishing effective communication channels and a seamless feedback loop between the internal and multi-vendor development teams.

  • Test Data Management
  • Managing test data, including generating realistic test data, ensuring data privacy, and maintaining data integrity.

Solution

CodeBoard Tech established a robust testing strategy by implementing a structured and collaborative approach. We ensured alignment of quality assurance practices, facilitated effective communication and feedback loops, invested in replicating complex test environments, implemented stringent test data management processes, and established seamless coordination with the development team. This comprehensive solution enabled smooth collaboration, efficient bug tracking, timely issue resolution, and adherence to data security requirements, ultimately leading to improved testing efficiency and enhanced software quality.

Benefits

  • Enhanced Accuracy
  • Reduces the likelihood of human errors and improves underwriting accuracy.

  • Improved Efficiency
  • Automated time-consuming manual tasks, such as data gathering and analysis, allowing underwriters to focus on higher-value decision-making. This streamlines the underwriting process, leading to faster turn around times and increased operational efficiency.

  • Consistency and Standardization
  • Standardized risk assessments and pricing, leading to fairer and more transparent underwriting outcomes.

  • Scalability and Handling Complex Data
  • Processed complex scenarios and analyzed diverse data sources, such as non-traditional data points, enabling more robust risk evaluations.

  • Adaptability to Changing Risk Landscapes
  • Incorporated emerging data sources, track market trends, and update risk models in real-time, ensuring underwriters have the most up-to-date information for accurate risk prediction.

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