We helped a leading U.S. transportation-focused FinTech company automate its complex invoice approval process, improving decision accuracy, reducing manual review, and enabling faster, more reliable processing.
Challenge
The invoice approval process at a U.S.-based transportation-focused FinTech company was highly manual. With a team of 70 operations staff manually reviewing approximately 10,000 client invoices daily, the process relied on nuanced, experience-based decisions that were difficult to automate. Key challenges included managing client-specific variations, preventing fraud, reducing costly “offsets” (post-processing adjustments), and minimizing processing time and operational costs. We had to prove that the automation could beat what a human could do.
Approach
We implemented an automated solution using Camunda, an open-source process orchestration platform. This solution integrated with the company’s BI database and a third-party machine learning tool to extract and validate data from invoices. Custom-built decision logic evaluated over 20 parameters per invoice, using factors like credit scores and historical data to drive automated approvals. ADO (Azure DevOps) Logic Apps monitored and reprocessed invoices as needed, enhancing accuracy and efficiency in real time.
We began with a pragmatic and gradual approach, continuously identifying the next segment of invoices to automate. The automation process either auto-approves invoices or routes them to a dedicated team for review of a specific item.
Value Delivered
The automation significantly improved efficiency and accuracy. Automated approvals reduced manual workload, identified additional fraud, and lowering the offset rate by 67%. Data-driven approvals minimized risks and costs, allowed humans to focus their time on more valuable activities as 65% of invoices were approved through the new automation process. In addition, the modular architecture allowed for scalability and future enhancements.
