Automation of payments reconciliation – need for organizational change

Many organizations especially in the B2B payments space still use antiquated manual payment reconciliation methods. This lack of automation consumes manual labor and increases probability of human errors and reduces reconciliation efficiency, not to mention associated loss of revenue or collections and other compliance issues.

There are a number of commercial products available that can help automate payments reconciliation using business rules and other meta-data. Usually these products provide case management features to ensure that paid or received entries that don’t get matched automatically using the business rules can be handled through manual escalation workflows. They also provide the ability to configure thresholds to adjust the margin of error so that amount differences within the threshold can be considered as “auto matched”.

I notice an interesting linkage between this simple technology feature (thresholds for auto match) and the culture of organizations. Typically, organizations that handle payment reconciliations manually tend to focus on all discrepancies however big or small. Ingrained in this habit, when they adopt commercial products for reconciliation automation, they have a tendency to look for absolute matches or to set the threshold in the product very low. This is quite natural and understandable.

Operational managers need to keep a heuristic estimate of the acceptable threshold for their organization based on the average size of their payments and receipts, average daily cash inflows and outflows, and average volume of daily transactions. This estimate is usually the amount below which spending manual labor to reconcile a discrepancy usually leads to wasted effort or a point of diminishing returns. Over time, as the commercial product gets adopted and teething problems are ironed out, operational managers need to monitor the comfort level of users and coach them to slowly increase the threshold limit to the heuristic limit they had computed apriori in their heads.

This often overlooked optimization step can make a big difference in the ROI of the commercial solution and operational efficiency of reconciliations. It is also quite possible that operational managers may need to adjust their estimate of “acceptable thresholds” based on what they learn from the installation of the commercial product and its impact on the volume of daily manual vs automatic reconciliations.

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