As businesses handle increasing volumes of financial transactions, errors and inefficiencies in payment processing remain a concern. Many companies still rely on outdated methods, resulting in financial losses. FlexTecs has expanded its payment discrepancy detection tool, FlexTrap, to address these challenges. The updated platform now includes supplier statement reconciliation, aiming to improve financial accuracy and reduce revenue leakage. This enhancement is designed to help enterprises automate payment validation and optimize their financial processes.
FlexTecs had previously introduced FlexTrap as a tool focused on preventing payment errors. Over time, similar solutions have been developed by other companies, emphasizing automation and artificial intelligence in accounts payable (AP) operations. These advancements align with industry trends where businesses are shifting towards automated reconciliation systems to minimize financial risks. The latest upgrade to FlexTrap reflects the increasing demand for comprehensive payment accuracy tools, particularly as companies continue to experience inefficiencies in manual AP processes.
What Are the New Features in FlexTrap?
The upgraded FlexTrap now operates as a fully extensible platform, featuring supplier statement reconciliation. This addition allows companies to automate transaction validation with their suppliers, reducing manual errors and improving efficiency. By incorporating AI-powered automation, the platform helps enterprises detect financial discrepancies before they escalate into significant issues.
FlexTecs CEO Tom Cook highlighted the importance of payment accuracy, stating:
“Companies lose millions annually to errors, inefficiencies and financial risks, making payment accuracy and reconciliation more critical than ever. By expanding FlexTrap’s capabilities beyond payment error prevention, we’re giving enterprises a scalable, future-ready solution to proactively safeguard profits.”
How Are Businesses Responding to FlexTrap’s Expansion?
Companies that handle large-scale transactions have shown interest in the enhanced capabilities of FlexTrap. Tidewater, a global offshore support vessel operator, has integrated the platform into its financial operations. Jeff Ng, director of shared services at Tidewater, stated:
“FlexTrap is a game-changer for Tidewater’s global AP team. It helps us catch duplicate payments before they happen, reduces errors and financial leakage across our operations. Specifically, the ability to customize validation checks to fit our internal policies makes a big difference, and the real-time alerts keep us ahead of potential issues. FlexTrap has become an essential tool in keeping our payment processes accurate and efficient.”
Many businesses are still reliant on traditional AP processing methods, which can contribute to financial inefficiencies. A report by PYMNTS Intelligence and Finexio indicated that nearly 38% of payments are processed manually, and half of invoices received by enterprises are in paper form. With the volume of B2B transactions expected to grow, companies are looking for solutions that enhance automation and efficiency in financial management.
Large enterprises, particularly those with revenue between $10 billion and $20 billion, often use multiple AP systems, which can create operational inefficiencies. According to industry reports, 60% of these enterprises rely on at least five different AP systems, increasing the risk of errors and delays. The expansion of FlexTrap is positioned as a response to these challenges, providing businesses with tools to streamline their financial processes and improve payment accuracy.
For businesses managing thousands of invoices monthly, automation in payment reconciliation is becoming essential. As more companies seek to integrate AI-powered financial solutions, platforms like FlexTrap offer a method to reduce errors and financial risks. The growing reliance on automated AP systems suggests that enterprises will continue to prioritize tools that enhance payment accuracy and operational efficiency.
