Introduction
Nalashaa partnered with a global provider of business process outsourcing solutions in the healthcare sector to enhance their AR Correspondence process. The objective was to automate and streamline the handling of daily requests, improving efficiency and reducing errors.
Client Challenge
The client's AR Correspondence process involved various actions such as adding or removing insurance, updating patient details, and more, performed manually in their GPMs web application. This manual process was time-consuming, error-prone and required significant effort from the customer support team.
Solution
Nalashaa's team developed a customized RPA solution to replicate the tasks performed by the customer support team
Authentication and Record Retrieval
The BOT logged into the Touch portal, fetched assigned records, and identified the relevant transactions in the GPMs server.
Action Execution
Based on the action codes provided, the BOT performed various tasks such as moving balances, updating insurance details, and adding comments to transactions.
Exception Handling
The BOT identified and managed both business and application exceptions, ensuring smooth execution of the process.
Benefits
Elimination of Manual Tasks
Freed up the customer support team from repetitive manual tasks, allowing them to focus on more strategic activities.
Increased Productivity
By automating the AR Correspondence process, productivity was significantly enhanced, enabling faster response times and improved customer service.
Reduced Errors
Automation minimized errors inherent in manual processes, ensuring accuracy and compliance with regulations.
Faster Delivery
The BOT completed tasks swiftly and consistently, resulting in faster processing and resolution of AR requests.
Cost Reduction
Deploying the solution led to substantial cost savings by replacing manual efforts with efficient automation.
Benefits
Resource Allocation
Only three FTEs were required to support the automated AR Correspondence process.
Transaction Volume
The BOT processed an average of 90 transactions per day, significantly reducing the workload on the support team.
Time Efficiency
Each transaction, which previously took 15 minutes manually, was completed in just 3 minutes by the BOT.
Technology Stack
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