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How Intelligent Finance Decodes Data

Here’s what you need to know to make the switch to intelligent finance technologies.

By Manoj Shroff | January 08, 2020 at 01:33 PM

The use of technologies such as artificial intelligence (AI), robotic process automation (RPA), advanced analytics, and machine learning is transforming treasury management. For example, when applied to cash management processes, these technologies can help a retailer better understand how a weather event might impact future sales so that it can adjust accordingly. Or when these technologies are applied to liquidity issues, they can help treasury find patterns in historical and transaction data, then synthesize that information to determine where and how to make improvements.

In combination, these technologies are revamping all kinds of processes that used to be painstakingly manual and error-prone, enabling treasury staff to focus on areas that require greater interpretation or judgment. In fact, Accenture research has found that 80 percent of the activities of the typical corporate finance team can be automated using these tools. Such automation facilitates improvements in compliance and control, productivity, and cost.

An intelligent finance infrastructure can bring great benefits to leaders who are juggling everything from bank statements to payroll processing to bank reconciliation. Put simply, automation—as facilitated by these technologies—takes the headache out of analyzing and optimizing a wide range of finance chores that can be quite labor-intensive if completed manually. When applied effectively, AI, RPA, and related technologies enable treasury and risk management teams to work faster, more accurately, and with less complexity.

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