7 Steps to Prevent Fraud with Predictive Analytics
This content was presented at the 2023 Minitab Global Insights Conference and received rave reviews, and we think it will be valuable to a wider audience – our blog readers like you! The presenters were Dr. Stefano Polastri, CEO, CTO, data and software architect, analyst and Minitab trainer and Ivano Izzo, another man of many talents, Ivano is a senior statistical analyst, Minitab suite trainer, Six Sigma, and DFSS expert. Their organization, GMSL, began in 1994 and stands for “Grow, Manage, Simplify, Learn”. They have been a Minitab partner since 1997 and have been helping companies use Minitab Predictive Analytics for fraud prevention. We will explain more in this blog.
Predictive analytics as defined by GMSL
To give you a better idea of how GMSL utilizes predictive analytics, let’s first describe it in their terms. “Predictive analytics is a category of data analysis that aims to make predictions about future outcomes based on historical data and analysis techniques. Predictive analysis uses a variety of statistical techniques (including data mining, machine learning, and predictive modeling) to understand future events.”
Conquering the digital landscape
Today, companies are bombarded with data coming from every angle, whether produced by machines, sensors, users, or contained in ERP or databases. We are living amid a very data-centric culture
Only from data is it possible to derive information
Only with Information will we have the knowledge of our processes
Only with knowledge can we make decisions
The climb towards improvement is a data-driven process
Deciding what to do with the data and how to analyze it for the best and most useful results can be overwhelming. Of course, there are many tools on the market that help decipher and analyze data. Predictive analytics is a powerful method – in which machine learning meets traditional analytics to look for patterns in data and projects them forward to help businesses mitigate risks and capitalize on opportunities. In this use case we will describe how to use predictive analytics to detect fraudulent credit card transactions.
This seven-step methodology can be applied to any case to answer the simple question: what will the behavior of the future be? The secret of this methodology is to EXPERIMENT
The 7-step predictive analytics project methodology
Fraud detection is a set of processes and analyses that allow businesses to identify and prevent unauthorized financial activity. This can include fraudulent credit card transactions, identity theft, cyber hacking, insurance scams, and more. To transform the raw, unstructured data into tangible, actionable information, GMSL follows 7 key steps, and we will illustrate how each applies to the fraud detection mission.
Often, more than half of the time of a predictive analytics project is spent on data acquisition, preparation, and analysis!
Download this infographic to see this seven-step methodology that can be applied to any case to answer the simple question: what will the behavior of the future be? The secret of this methodology to EXPERIMENT.