COVID-19 REPORTING USING TRANSACTIONAL TAGGING & MACHINE LEARNING

About the event

This session will walk you through how our COVID-19 reporting system uses transactional tagging and machine learning to provide suggestions that are 99% accurate* and allows for the COVID-19 reporting job to be completed in under an hour**.

Transactional Tagging is the concept of adding detail to transactions that can be seen by anyone investigating that same transaction. The transaction could be anything from an invoice to a journal or just anything with a unique identifier. The concept isn’t limited to finance systems but it’s where I’ve focused my implementation of this concept.

Machine learning is a subset of artificial intelligence and it includes the use of statistical techniques to allow a computer to learn how to do a task better without being explicitly programmed differently over time. I’ve used this in conjunction with transactional tagging to make COVID-19 Reporting easier by allowing the system itself to give me suggestions as to what to tag a particular transaction as.

I will show you how every element works from the intuition to the final product and it’ll be followed up with a Q&A session so you can ask me anything about it.

* 99% accurate as of June 2021 but was only as low as 70% when the process was first set up

** under an hour as of June 2021 but it largely helps that transaction numbers have fallen recently and that I’m very used to all the transactions that show up and what to expect nowadays – before the system was in place, this was a full-time month-end job

When
TUESDAY, SEPTEMBER 28, 2021 - 10:00 TO 12:00



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