Companies must carry out a comprehensive scrutiny of their KYC and their online and offline footprint in order to recognise certain merchants and not enable them to collect payments on their website.
Fremont, CA: Digital payment companies deal with two primary forms of transactional fraud: fraud committed by a digital payment collection retailer, and fraud committed by someone using compromised credentials or digital payment cards.
Let us individually look at them to see how AI and ML can be leveraged to identify and stop fraud:
Merchants' Frauds Committed
Fraudulent merchants are those who, instead of delivering a service or shipping a product, receive payments electronically from innocent customers, but then do not fulfil the promise after receiving the payment, often even in full. In order to save customers from the problems of running after these retailers, filing complaints or demanding charges, it is important for a digital payment company not to accept such payments.
Companies must carry out a comprehensive scrutiny of their KYC and their online and offline footprint in order to recognise certain merchants and not enable them to collect payments on their website. By using computer vision and pattern matching algorithms, AI can prove to be instrumental in verifying the validity of its KYC documents automatically. AI also makes it possible to detect adverse trends on the internet footprint of the retailer, like social media, an effective way of detecting suspect merchants.
The other side of online payment fraud is the use of compromised credentials, such as stolen cards, stolen passwords, hacks of cell phones, phishing and scams of phone calls. In these cases, despite providing the goods or services to the fraudster, it is the merchants who suffer and often have to refund the money back to the original cardholder.This could generate mistrust with payment companies and, thus, companies need to implement state-of-the-art AI technology to recognise and stop malicious attempts at such transaction attempts.