Challenge
Challenge

Due to high returns,the client had to incur heavy operational costs. The client realised the need for a solution for reducing the return frauds as these leakages were significantly impacting the bottomline.

Solution
Solution

Flipkart’s Fraud manager, using multiple data points and its AI/ML algorithms was able to predict potential orders in advance and help business prevent RTO/ RVP leakage

Result
Result

By acting on the potential RTOs and RVPs frauds with fraud manager, the business was able to add 3% of the growth in their bottomline as additional margins

  1. Situation
    How to reduce Return Fraud for better margins?

    In an industry, centred around customer’s needs, order cancellation, free return policy, exchange policy, cash on delivery (COD) and refunds help to gain customer’s trust and to increase brand affinity. But, return orders can significantly increase the costs. There can be multiple reasons which can contribute to RTO, RVP cost like impulse buying by customers,non-delivery of product because of incorrect address and contact details,unsatisfied customer with the product or damaged return product by customer.

    The fashion category was experiencing an increase in the number of orders but at the same time it  was facing a leakage from gross margins to net margins. This loss of profit margin was due to the Return to Origin (RTO) and Reverse Pickup (RVP) frauds which led to loss of working capital, blocked inventory and zero returns on cost incurred for the shipment and delivery till the customer's doorstep. Approximately RTO and RVP cost constituted around 40-50% of the total cost of operations. The category Manager understood the need for leveraging technology and analytics to reduce the supply chain cost to achieve higher margins

  2. Solution
    Predicting return leakages by evaluating Consumer behavior

    In order to achieve supply chain efficiency and cost reduction, Flipkart Fraud Manager helped the client to evaluate customer behavior and predict the probability of frauds. The solution gathered multiple data points like browsing pattern, product features, geo-location features, account features and many more to identify potential RTO/RVP and high risk profiles. This helped the client to formulate policies for frequent defaulters like No COD option, verification of the details with the customer before the shipment etc. This was done with minimum loss of revenue leading to significant impact in bottomline

  3. Impact

    The Fraud Manager assisted the client to take timely actions against fraudulent transactions which helped in reduction of return frauds for their Fashion category business.The category saw an increase in their bottomline due to savings from predictive intelligence.

    • Net Revenue Addition
      3%
      Net Revenue Addition

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