As an e-commerce merchant, there should be some preparation done for things like funding, stocks, products, etc. But at the same time, precaution for the expenses like lost products, shipping charges, chargeback fees, and the probable loss of the merchant account.
Case investigations, customer phone support, and damage to a merchant’s reputation also contribute to the cost of fraud. The latter could possibly be more damaging.
Possible points where fraud could be prevented:
Predictive Analysis: There is a vast use of data nowadays, which can be used to detect fraud patterns to determine future probabilities and trends. Although predictive analytics won’t reveal what type of fraud is about to take place but it will certainly point the possibility of fraud.
Experienced Fraud Analysts: The customer care and a team of fraud analysts can be a ticket to reduction and prevention of fraud. Fraud analysts play a critical role in a fraud detection solution, seeing behind the scenes. Customer Care and support: Customer care and support play an important role as they are in direct contact with the customer and can detect the possible reasons of fraud.
Monitor Transactions and Reconcile Bank Accounts Daily: You must know about your biggest spenders and their buying patterns. Monitor your accounts and transactions for red flags like inconsistent billing and shipping information, as well as the physical location of your customers. Use tools to track customer IP addresses and alert you to any addresses from countries known as a base for fraudsters.
By putting the right tools and processes in place, you can reduce the chances of fraud.
BEHAVIORAL ANALYSIS:
With businesses looking to reduce fraud and keeping up with emerging trends in fraud methods, new ways of detecting and preventing fraud are being developed. One of these is the Behavioral Analysis.
Behavioral Analysis relies on something, which is inherent in a user: how they behave. What a user does may be a better indicator than who say they are, this question is mostly challenged by authentication.
This is analyzed by shopping habits; our shopping habits reveal our unique behavior. For example; how you shop, what is the monthly spending budget of your spending, etc.
SIMPLE STEPS OF BEHAVIORAL ANALYSIS TO DETECT FRAUD:
Gather lots of information to form a template of the user’s behavior and get prepared for the customer’s response. Also, make sure to train the team against such frauds. Set a rate or a threshold according to your customer’s response translating from normal to fraudulent. This is generally in percentages that a transaction is fraudulent (for example, 90%) When a user is encountered, a probability of the transaction being fraudulent is calculated based on the behavior. If the percentage is above the threshold (90% in the example), the user is blocked from the transaction.
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