AI fraud detection systems have revolutionised how companies handled fraud monitoring.
AI Fraud protection can be used by utilising the latest in artificial intelligence and machine learning to help aid the factors that lead to fraud detection and prevention in record time. There are a myriad of different companies from casinos to banks all engaging in this practice to help maintain the integrity of the product or service which they are providing. There was a time when there weren’t AI systems in the space. There was no machine learning, and manual fraud prevention systems relied on set patterns that required considerable mathematical knowledge and they were restricted to only analyzing restricted fraud patterns.
The AI Fraud Detection system helps to complete data analysis within a matter of milliseconds and detects complex patterns in the most efficient way, which can be difficult for a manual fraud analyst to detect.
Most larger companies will swear by AI fraud monitoring because it is vitally important in speeding up and increasing accuracy for fraud analysts. Fraud alerts are calculated in a quick and easy to analyse way. It also helps to identify patterns and this allows fraud analysts to find financial frauds based on more standard indicators of crimes.
If your business is competing in high technology industries today, you have to be constantly vigilant to stay within the rules of policies and regulations that protect key technologies from being exploited, which our fraud monitoring systems will do for you. Our AI systems will help to keep your company in compliance with these business policies and rules and help to further enable your fraud protection.
Our machine learning systems grow as the data being compiled does. There are reports of large numbers, that can amount to as much as statistically half, of legitimate fraud cases that are found by banks and financial institutions after having been flagged by an AI Fraud detection system.
Fraud can be flagged by having a constant analysis of data which is flowing through a client’s server. There are a number of ways that this can be done, and in the case of most AI Fraud detection services they can analyse patterns relating to what constitutes common practice for user activity. .
After it has detected fraud based on the patterns that it understands, the software can notify a manual fraud detector of any deviations from what constitutes standard activity and they can review the findings.
After having been privy to this review, the person who is monitoring manually can accept or reject the alert that is offered after having made a judgement decision, which will signal to the machine learning model that its determination of fraud from the metrics which it has used is correct or not. This ultimately allows it to begin to better understand what qualifies as true fraud.