In this interview with TTVCo-founder, Benjamin Berger, we look at how the current payment solutions can be integrated using AI to reduce frauds and improve clients’ satisfaction.
Benjamin said “Every year, citizens of the European Union make 122 billion digital payments using payment cards, bank-transfer apps, e-wallets, mobile wallets and other payment methods. Without AI, there is no way the payments industry could process so many transactions so quickly and keep fraud and error rates down to an acceptable minimum. Implementing AI into our system in not only necessary but a fixed requirement.”
WhyAI is necessary
The massive volume of digitalpayments is both a help and a hindrance to spotting fraud. On the one hand, it strains existing fraud-detection systems to the limits. On the other hand, it provides developers of artificial intelligence with the data they need to train their algorithms.
A traditional rule-based fraud-detection system might consider a range of variables, for instancelocation, the type of merchant, the amount being spent and so on. Thus, if a user spends more than usual, with an unfamiliar merchant in a previously unvisited location, this will probably end up being flagged as a possibly fraudulent transaction. It’s why your card sometime ends up frozen when you goa bit nuts on holiday and spend too much on skiing gear.
How AI is used in payments
Using AI, usually, machine learning, can significantly improve fraud detection and reduce false positives. For example, a payments AI might look at a whole range of factors and assign a risk score to each. A merchant with a good track record might have a low-risk score, say 15%, but an unfamiliar IP address, time zone or location might attract higher risk scores. This process can be repeated for hundreds of factors, with the final average score determining whether the transaction passes the merchant’s threshold for being flagged up as fraudulent.
It’s possible in this way to analyze vast quantities of data to build a much more sophisticated picture of what “normal” looks like. Because it’s not limited to working within set rules, an AI can analyze this larger body of data to look for unexpected commonalities between both fraudulent and non-fraudulent transactions.
Through the adoption of AI in TTVE-payment solution, besides the operational benefits of being able to processtransactions in real time which is not possible previously if manual checkswere required, but it also reduces fraud occurrences as AI has the capabilities to detect and identify anomalies within the existing trends and flagged-out these anomalies as fraudulent transactions.
