Machine learning increasingly is being used to discover fraud schemes. With this type of artificial intelligence (AI), the technology learns or improves in accuracy through experience, rather than through additional programming. If you already use AI in your business, you are probably somewhat familiar with how machine learning works. But here is a quick overview of its application in fraud detection.
New Approaches Needed
More and more, businesses rely on digitization to deliver the goods and services their customers want. Unfortunately, digitization also makes it easier both for cybercriminals and stakeholders, such as employees, vendors, and customers, to steal. Preventing fraud in the digital age requires new approaches.
Machine learning is one such approach. Traditional rules-based fraud detection software flags transactions — such as purchase orders of a certain type or over a certain amount — that are suspicious according to static rules. On the other hand, fraud detection software that includes machine learning uses large sets of historical data to ‘learn,’ or create algorithms about the patterns associated with new fraud schemes, enabling it to detect fraud in the future.
Step By Step
For a machine to learn, its users must follow certain procedures. After the software is enabled to capture historical transaction data — and the more data, the better — the company using it reviews the data to ensure it presents an accurate picture of transactions. The software then applies algorithms to identify potentially suspicious items. This process creates the first fraud detection model. The software analyzes the same set of data repeatedly and produces new models for the company to review. The company provides feedback on each model to help the software develop better algorithms.
Through this process, the model learns what constitutes fraud and the number of false positives should drop significantly. In the end, the company selects the most accurate fraud detection model to put into production.
If you have the technical capabilities, you may be able to develop a customized machine learning program for fraud detection in-house. We can help if you do not. Contact us.