With the advance of internet technologies in recent years, online shopping is becoming a popular trend to make purchases compared to the traditional ways. There are many excellent benefits to both the consumers and business conducting online businesses. However, it could also cause great damage to the business due to the increasing number of fraudulent online transactions. In order to improve the online shopping experience, there are great needs to reduce and prevent the fraudulent activities. This paper aims to discuss how the data mining and statistical algorithms can help to identify the fraudulent transactions' characteristics and prevent the fraudulent transactions in real-time.