4 ways of getting more value from your AP transaction data using ML

There are several ways in which machine learning can be used to analyse accounts payable transaction data and extract valuable insights. In this post, I look at the ways that some clients have and are making the most of the transactional goldmine that exists within their document management and/or ECM landscape.

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TLDR: You can use your AP data for much more than you either think or are currently doing and by drafting in ML to help, you can get some astounding results.

BTW: In this article when I say “algorithm”, I am mainly using it as a summary term for a collection of algorithms and/or systemic processes and outputs to deliver an outcome.

Photo by Wesley Tingey on Unsplash

Let’s begin with honesty, we all know that Excel is still the king of financial analysis for SMEs because behind every beautiful chart there’s a finance manager or bean counter sweating the detail. It is probably still the most used tool for SMEs when it comes to digging into data or identifying trends etc. Sure, some businesses might make use of Microsoft BI or Pentaho etc but, there’s usually a very strict use case, a tight reporting deadline, some clear KPIs and a harassed…