Using Machine Learning and Robotic Process Automation to Improve Regulatory Compliance While Reducing Staffing Time Spent by 95%

Case Study

Using Machine Learning and Robotic Process Automation to Improve Regulatory Compliance While Reducing Staffing Time Spent by 95%

Overview

The logistics industry has increasingly faced stricter environmental sanctions and regulations imposed by both federal and local governments. The costs associated with compliance management and evolving business processes have made it difficult for logistics providers to maximize profits.

Challenge

The client needed to automate a manual process that prevented the shipment of materials federally prohibited for transport. The manual process involved a dedicated FTE cross-referencing and reformatting two cumbersome spreadsheets to identify the requested information and generate a Daily Material Receipt Report.

Solution

NITCO implemented preemptive measures within the client’s existing business processes by designing and developing an enterprise solution using Robotic Process Automation (RPA) combined with machine learning algorithms.

Benefits

  • 100% accuracy in data identification
  • Increased business compliance with federal and local regulations
  • Reduction in human error, maximizing profits
  • 95% FTE savings (3 FTEs spending 30 minutes manually per FTE reduced to 5 minutes total with automation)
USA

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040-45437626

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