The Role of Machine Learning in Big Data Fraud Protection

Speculation about what machines will be able to do for us in the future has been around for years. However, there isn’t nearly enough praise given to the machine learning platforms that are already revolutionizing the way our data is protected. Machine learning has grown to play a big role in big data fraud protection. This is good news for enterprises looking for next-level ways to safeguard against the sophisticated threats that exist today.

Where Does Machine Learning Fit in With Big Data Fraud Protection?

Machine learning is used to make predictions based on past behaviors and other forms of input. It is a process of finding patterns and making predictions based on the data that is available. A system that integrates machine learning has the ability to mine data, recognize patterns and weigh statistics in the blink of an eye to create a deliverable action. Enterprises that utilize machine learning for big data fraud protection have a digital, constraint-free investigator on the case every time an action is made within a network. It can be used to help an organization verify legitimate payments or to simply keep hacking threats outside of the gate.

Few enterprises have the manpower or capacity to build a custom fraud prevention system using machine learning. As such, many enterprises must seek out the help of third-party agencies when developing systems for fraud management. Platforms that help to safeguard data and detect fraud can be customized to fit any scale.

What Machine Learning Must Do for Users

The sophisticated nature of machine learning can make it an intimidating idea for many enterprises. However, it can be easily integrated into a user-friendly system that is a part of an enterprise’s moment-to-moment plan for defense. If an enterprise is considering adopting a platform that uses machine learning, they should make sure that it contains the following qualities:

  • Ease of use for a diverse group of users
  • Offers visual reports
  • Delivers quick insights
  • Does its job without human intervention
  • Allows for human intervention when necessary
  • Can be customized

Volume is a major contributor to why machine learning is such a crucial part of fraud prevention for today’s enterprises. The processing power of today’s systems necessitates a way to monitor and analyze every piece of information that channels through a system without actually manually monitoring and analyzing every piece of that information individually. Statistical modeling uses logic to determine whether or not something suspicious is going on within a network based on known patterns. Hackers are using methods and systems that are more sophisticated than ever before in their attempts to breach systems and make a profit. Machine learning offers a smart, intuitive and statistics-based method of fraud prevention that can protect an enterprise when a threat hits.