Most of people are familiar with Payment Fraud for online transaction. In general, online fraud refers to illegal transactions made on the internet. The fraudster could be a hacker who steal other people identification and information to make payment or simply just a user who do not pay the bill at the end of the month. However, when talking about online fraud, everyone usually think about fraudulent activities with credit card, not a lot of people have understanding about Fraud in Mobile Payment industry.
Compared to credit card, mobile payment tends to have lower risk and higher user satisfaction but it does not mean we do not have to deal with Fraud. It happens more often with post-paid phone accounts when users make larger amount of purchase and refuse to pay at the end of month but it also can happen with pre-paid accounts when user’s phone accidentally got stolen for instance. An interesting case of pre-paid account risk is when user use credit card to top-up their balance but do not pay the card bill at the end of month. In this case, it is not easy to identify the risk, pre-paid supposed to be safe methods for paying.
We also have the term ‘family-fraud’ refers to case children steal their parent phone to make payment. It raises the controversy since it is undeniable that partly fault belongs to the parents who do not protect their property from their kids but at the same time, several countries have strict regulations banning purchase making by junior under 18 therefore merchant or payment provider still have to bear the consequences.
It lead us to the question that how should we minimize the risk of mobile payment . It could be answered by several steps as followed:
- Monitoring and alerts
- Risk rules set up
- Machine learning to study user behaviours
- Blacklist user / phone number
The very first important thing needed to be done is monitor transaction frequently, compared to historical data to identify if we have any unusual patterns. Since fraudulent activities should be blocked before it happens, risk rules need to be set up (For example, a rule blocking payment purchase for amount more than 200 USD in Botswana can be considered if it is unusual pattern to spend that much money with mobile phone account in that country). It could be called as a shield to protect merchant from getting hurt. At Digital Virgo , we call it DCB Shields – which will be presented later for its functionalities.
In 2019 when artificial intelligence and machine learning are becoming big trend in every industry, mobile payment is not an exception. Manual monitoring and rule setting are becoming time and cost-consuming and not efficient. Based on historical data, our algorithm will help to predict the risky level of the user in order to prevent illegal transaction in advance.
Last but not least, all fraudulent users will be blacklist and stored information in the system for future protection.
To sum up, it is not easy to handle the whole process of fraud management especially when it costs a lot of time, efforts and resources therefore , one of the famous solution that many e-commerce, streaming services or game publishers go for is relying on the reliable payment partners who have experience and expertise to handle it. If you are looking for an end-to-end solution which not only helps you generate revenue but also protect you well from potential loss in Mobile world, DVPass could be a very good match.