Saved $20M in ill-gained referral bonuses while maintaining high customer acquisition rates

REFERRAL FRAUD

Customer fraudulent referrals accounted for a significant portion of company revenue at a large transportation and logistics company.  Utilizing machine learning algorithms we were able to detect and mitigate fraudulent referral transactions while maintaining high customer acquisition rates. 

THE PROBLEM

Customer fraudulent referrals accounted for a large portion of company revenue at a large transportation and logistics company. Bad actors use and abuse referral codes to game free and discounted products. This simultaneously damages the bottom line and customer engagement with the product. 

THE SOLUTION

Using Machine learning algorithms we were able to detect and mitigate attempted fraudulent referral transactions.

THE RESULTS

SAVED MONEY & INCREASED THE BOTTOM LINE

REDUCED NEGATIVE IMPACT ON GOOD CUSTOMERS BY MORE ACCURATELY PREDICTING THE BAD

IMPROVED OVERALL HEALTH OF THE PLATFORM

Using data and machine learning we increased short and long-term profits as well as improved the reputation of the company.

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