Business owners these days need to watch out for fraud and other illicit or unapproved activities. If your company has a significant online presence, these events can hurt your bottom line.
Certain technologies can help you identify fraud and other problem behaviors. UML is one of those. Today, we’ll break down what UML is a little bit, and we’ll also give some specific examples of what it can do for you.
What Exactly is UML?
UML stands for unsupervised machine learning, and it is one of the AI fraud solutions on which modern companies rely. Machine learning is a particular artificial intelligence type.
It uses algorithms. They learn from existing data, using it as applied knowledge when they get new-data access.
When we talk about unsupervised machine learning, what we mean is a machine learning technique that works without needing labeled input data. In other words, it’s machine learning that infers a specific function to describe the hidden structures of some “unlabeled” input data points.
If you have a large unlabeled data amount, you can use UML to discover patterns within it that the naked eye probably cannot detect. If you want to see an unknown or new pattern, this is how you do it.
The Most Common UML Approaches
Most businesses that use this UML technology are those that want to detect anomalies. They use it to find outliers. There are UML-enabled graph or clustering analysis techniques that study the connectivity and relationships among input data sets and subsets.
If you have advanced UML technology that uses graph analysis algorithms and clustering techniques, it’s much more likely that you can detect various kinds of fraud. Usually, the UML will analyze data point connectivity and distance that represent account activities.
To put it another way, when you’ve got individuals who are doing online business with a bank or some other entity, they should display diverse behavior patterns. If you have a large user group, it’s improbable that they would all follow the same pattern.
If the UML detects several individuals following the same interaction patterns, that’s probably fraud. A single instance of a behavior or characteristic will not be suspicious. If you have an entire group acting the same way, then as a business, you can focus on those individuals as perpetrating fraudulent behavior of some kind.
Why is UML So Useful?
Whenever you have an online business entity with whom people interact, there is fraud potential. Companies need to come out with new tech to stop fraud because hackers are always creating new ways to try and bypass it.
Unsupervised machine learning can analyze real-time data. It needs no prior legacy knowledge. Essentially, that means you can let it go to work on any program where money changes hands, and it can quickly identify any suspicious activity.
It’s a safeguard that is not at all labor-intensive, at least not for the humans that control it. You can set it up and watch it go, with little prompting on your part. It is self-tuning, and it can have a lasting financial impact, especially if you’re trying to identify and combat new or emerging fraud types.
What Are a Few Specific Ways You Can Use It?
If you own a bank or some other online business, you can use UML technology in several ways. You can use it for application fraud. As a financial institution, you can analyze a whole application network and detect any hidden connections that your naked eye would never pick out.
You can use a UML algorithm for transaction fraud detection. The tech can pick out fraudulent accounts before the perpetrator who set them up can withdraw any money. If you’re monitoring your UML system, you can immediately flag and disable any suspicious accounts until you conduct a more thorough investigation.
You can also use this tech to block bot attacks. You can analyze user history with it to pick out suspicious activity across millions of accounts at once. If a bot-powered attack is in progress that can cripple your computer network, the UML algorithm can stop it in real-time.
You can also use UML technology to block money laundering and promotion abuse. It’s for all these reasons that you should look into getting it for your financial institution or other business as soon as possible. If you don’t have it yet, you leave yourself open to new, innovative hacker attacks and other potentially devastating fraud activity.