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Online Fraud Prevention Analysis

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.

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Online Fraud Prevention Analysis

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  1. ONLINE FRAUD PREVENTION AND ANALYSIS

  2. ONLINE FRAUD PREVENTION: 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.

  3. POSSIBLE POINTS WHERE FRAUD COULD BE PREVENTED: 1. 2. 3. 4. Predictive Analysis Experienced Fraud Analysts Customer Care and support Monitor Transactions and Reconcile Bank Accounts Daily

  4. 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. 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. 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.

  5. 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.

  6. Contact Us US Head Office 10300 49th Street N Suite 427 Clearwater, Florida 33762 UK Head Office 160 City Road Kemp HouseLondon EC1V 2NX +1 (888) 622 - 6875 +1 (844) 465 - 4723 info@merchantstronghold.com www.merchantstronghold.com

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