Maintain full control and visibility over your risk management system

Combining your platforms’ risk knowledge with a machine’s means your system can learn and adapt to fraud situations as it goes and makes managing risk scalable. Known as supervised machine learning, this approach uses labeled data, payment authorization details, and other data points to make a decision. 

It’s important to note, though, that machine learning is only as good as its base data:

• Common challenges include a lack of visibility into how machine learning makes decisions.
• It can also mean an increase in operational work setting up risk rules.

That’s why it’s important to ensure your PSP continuously trains the machine with things like access to comprehensive shopper and transaction data, a long history of risk management, and international coverage.