How we use NLP in Fraud Detection?

One of the biggest challenges is to understand where and when Fraud may occur. It’s very important that you have a deep knowlodge about your data and information, to have an understanding of what the specific piece of content is saying to you, and start understanding how it might relate to fraud, obviously, so you can be aware when a Fraud sign shows up. For this reason, we discuss NLP in Fraud Detection today.

Natural Language Processing (NLP) with the help of Machine Learning is a current win-win combination used to detect fraud and misinterpreted information.

To prevent fraud to happen it will help you build up a sort of dictionary or a set of keywords or outcomes largely based on certain patterns in text and in content, you might come to believe that there’s a signal for fraud, it’s not for sure that there’s fraud there at that point, but there’s a signal that fraud may be present in the future.

If you could build a model with all sorts of information that you know can be related to fraud, that would help you be more aware because you already know. The idea with NLP is to improve that model aligned with your growth to prevent Fraud to happen.

Fraud has many forms – ranging from fake news spread on social media and doctored images/videos to manipulating hateful ideas. Even instilling fear with numerous hoax calls about social security blockades; and how you can be deported if you do not pay the fine immediately over the call.

Let’s cut through the jargon, myths and nebulous world of data, machine learning and AI. Each week we’ll be unpacking topics related to the world of data and AI with the awarding winning founders of 1000ML. Whether you’re in the data world already or looking to learn more about it, this podcast is for you.