Benefits of Machine Learning in Combatting Fraud Attacks
The main benefit businesses identified in using machine learning to tackle fraud is through real-time detection measures, which was cited by 54% of respondents. Models can identify and flag anything suspicious much faster than a traditional system can.
Similarly, 52% of respondents say that better customer experience with less security friction is another key benefit. Machine learning allows businesses to make faster security decisions, and it allows them to carry out passive fraud checks regularly.
51% of respondents also noted an improved accuracy in their detection of fraud when adopting machine learning, especially when compared with rules-based systems alone. As models can be continually retrained and improved, businesses can be sure that the system won’t miss any new threats.
When adopting machine learning into a security stack, the report claims the most important element is having sufficient, high-quality data available, in order for the system to be as effective as possible.
