Five Machine Learning Applications for the Back Office

Enterprise-level systems can be handled in new ways to save time and money



While consumer-facing applications of machine learning have gotten a lot of attention (Netflix, Uber, and Amazon), the back office deserves some recognition. Enterprise-level systems that run the business—think finance, robo-advisors, accounting, operations, human resources, and procurement—tend to be large, complex, and process-centric. But, they also use and produce large amounts of both structured and unstructured data that can be handled in new ways to save time and money.

Machine learning combined with solution-specific software can dramatically improve the speed, accuracy, and effectiveness of back-office operations and help organizations reimagine how back-office work gets done.

A current trend among mid and large organizations is to implement Robotic Process Automation (RPA) in the back office to minimize manual tasks and achieve efficiencies. While there are specific use cases that make RPA an appropriate technology, there are significant differences with a machine learning approach.

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Source: CPA Practice Advisor

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