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Treasury Technology
Published  8 MIN READ

Taking Your TMS Beyond Treasury

The benefits of implementing a treasury management system (TMS) to optimise one’s treasury operation have been well-known for a number of years, but in recent times the traditional scope of the treasurer’s responsibilities and the tools at their disposal have broadened substantially. Not only can treasurers now use a TMS to eliminate manual, spreadsheet-based activities from their daily operation, they can now also add value to downstream finance processes. Accounts payable/receivable, bank reconciliations and accounting are all processes within the broader finance function that can be enhanced by applying the broader scope of treasury technology applications.

This article will explain some of the treasury and finance processes that benefit from the broader application of treasury technology applications. It will also describe how various benefits are achieved in practice without over-stressing the organisation’s operational and financial resources. 

Machine learning introduced into the payments and other treasury processes

Payment processing and execution is a critical function for most corporate treasury/finance departments. Failure to manage these activities effectively can directly impact your business’s cash management accuracy, reduce operational efficiencies and  increase the difficulty in complying with regulatory requirements as  well as  introducing the risk of fraud. These risks are further compounded in an organisation operating in multiple jurisdictions and currencies. Best practice treasury systems now not only provide increased transparency, payment workflow automation and payment transmission securely through various encryption protocols, but this functionality should now also be fully integrated with automated fraud detection and prevention capabilities.

Payment fraud detection goes beyond standardised controls such as the segregation of duties and approval limits. It introduces a layer of Artificial Intelligence (AI) within the payment process to allow users to set predefined detection rules and to use these rules to screen for suspicious payments –which would then require further attention without influencing other compliant transactions. It can also identify trends from historical payment information and recognise inconsistencies with these trends moving forward. Other examples of how this functionality mitigates fraudulent payments include: