  The e-commerce share in the global retail spend is showing a steady increase
over the years indicating an evident shift of consumer attention from bricks
and mortar to clicks in retail sector. In recent years, online marketplaces
have become one of the key contributors to this growth. As the business model
matures, the number and types of frauds getting reported in the area is also
growing on a daily basis. Fraudulent e-commerce buyers and their transactions
are being studied in detail and multiple strategies to control and prevent them
are discussed. Another area of fraud happening in marketplaces are on the
seller side and is called merchant fraud. Goods/services offered and sold at
cheap rates, but never shipped is a simple example of this type of fraud. This
paper attempts to suggest a framework to detect such fraudulent sellers with
the help of machine learning techniques. The model leverages the historic data
from the marketplace and detect any possible fraudulent behaviours from sellers
and alert to the marketplace.
