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Case Studies
Optimizing Data Reconciliation Processes for a Car Service Marketplace
AUTOMOTIVE SERVICING — DATA OPERATIONS Automotive

Optimizing Data Reconciliation Processes for a Car Service Marketplace

Our customer is a marketplace for car servicing, connecting individuals, fleets, and small businesses to repair shops and garages. With partners operating on different systems and sending month-end statements in inconsistent formats, reconciling that data against internal records was a persistent, error-prone challenge. We partnered with the marketplace to standardize and automate the month-end reconciliation process, cutting manual effort and sharply improving accuracy.

Overview

Key Highlights

Problem Statement

Needed to standardize the reconciliation process for month-end statements arriving from partners in inconsistent formats.

Approach

Built an automated process flow using Python scripting to reduce reconciliation time and improve accuracy, while cutting manual effort.

Results

Delivered a 100% improvement in month-end reconciliation data accuracy.

Project Overview

Details & Results

Problem Statement
  • Customer’s partners (repair shops, garages) work on different systems and send month-end statements in different formats 
  • Month-end reconciliation of the data with internal data, closure of books, estimation, and preparation of remittance statements was a key challenge 
Solution

We worked closely with the stakeholders, understood the process, and created a team to efficiently implement it with high accuracy and within prescribed timelines. 

  • Automated different parts of the process using Python scripts to reduce time and improve accuracy 
Outcomes
  • Process Standardization: Delivered consistent, systematic implementation of the month-end reconciliation process 
  • Accuracy: Achieved a 100% improvement in month-end reconciliation data, minimizing errors and rework 
  • Efficiency: Significantly reduced overall cycle time through process automation 
  • Reduced Manual Effort: Cut manual reconciliation work through automated process flows 
  • Team Growth: Expanded from a single resource to a 4-person team working across different process and value streams 

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