Artificial intelligence technologies deliver tangible results in complex risk situations when the data does not fit clearly into structured rows and columns.
In the past, risk managers identified fraud by analyzing large amounts of structured data against set rules but this led to too many false positives that took hours to sort out. Now, AI models analyze large amounts of both structured and unstructured data for better, faster results.
AI algorithms identify unusual activity hidden in complex patterns without generating many false positives. Machine learning, a subset of AI, learns how to perform these tasks better over time.
At the start, analysts teach the models to improve over time with preparation sets. However, the programs take in enough data to improve on their own over time. Similar to the human thought process, machine learning algorithms take in data, process them, and compare the results. Unlike a human, however, ML algorithms do all this in a heartbeat.
Once the model has amassed enough data and experience to properly separate and extract anomalies from its data on customer behavior, it can start to make real-time decisions, like blocking or flagging transactions for further review.
NuDetect is an award-winning company. Their AI model combines the power of four integrated layers of security to verify users based on their behavior. NuDetect prevents fraud and protects online environments in real time.
DataVisor is another award-winning fraud detection company using AI. DataVisor merges progressive AI with ML technologies to highlight suspicious patterns.
Buguroo works on behavioral biometrics, malware detection, and device assessment to detect online fraud. With its unique approach, Buguroo has made its name as a leader in the fields of online fraud detection and cybersecurity.