Did you spend lots of time to classify your accounting entries?
From our interactions with customers, we have realised that accountants spend a lot of time to classify accounting entries and assign them to the right accounting codes. Besides these, they also need to classify some of these entries to the right projects for reporting purposes. With machine learning and natural language processing, this classification can be done easily.
How can do is this be done:
First, you can export out the accounting entries from your accounting system. This can be the description of the entries and the accounting code. Since you have done this check already, you can take this as the “training data” to train a model. We can then use this model to classify future entries and put them in the right accounting codes.
As some text classification system, you may want to remove some of the noise from the accounting entries description. This can be done using a “regular expression”. The regular expression is a way to clean data.
Once the data sets (accounting entries ) are cleaned (pre-processed), we can let a cognitive automation tool like Gleematic to train a model.
Once this model is trained, we can look at their result and accuracy.
To deploy a model, you can do it easily using Gleematic’s built-in robotics process automation to interface with your existing accounting software. This can also be applied to project costs in finance, there are many times, we need to classify the accounting entries into the right project cost. Most of these are in the description, so you will need NLP (Natural Language Processing) to process to classify them correctly.
So what are the benefits:
Written by: Christopher Lim