Case Studies

BNPL Innovator Balances Customer Experience And Fraud Prevention With Machine Learning

Read this case study to learn how an innovative fintech lender in the point of sale finance industry:

  • Achieved a 41% reduction in hurt ratio, a measure of false positives.
  • Detected 320+ fraud rings in 6 months of transactions, some of them related to over $80k in losses per syndicated attack.
  • Gained a 5x estimated review efficiency improvement.

Complimentary Case Study

An innovative American financial technology company that pioneered the point of sale finance industry by providing a fast, transparent, and inclusive loans to consumers decided it was time to rethink its fraud prevention strategy. 

Fraudsters were using synthetic identities to mass register new fake accounts and then requesting loans that were never paid back. Additionally, high rates of account takeovers and promotion/benefit abuse indicated that the client had outgrown its insourced fraud model.

Instead of just adding authentication measures and increasing friction for its customers, this company decided to solve the well-known industry tradeoff between customer experience and fraud prevention with machine learning.
BNPL Case Study - Raising the Bar for Customer Experience and Reducing Fraud with Machine Learning 2
About DataVisor

DataVisor is the world’s leading fraud and risk management platform that enables organizations to respond to fast-evolving fraud attacks and mitigate risks as they happen in real time. Its comprehensive solution suite combines patented machine learning technology with native device intelligence and a powerful decision engine to provide protection for the entire customer lifecycle across industries and use cases. DataVisor is recognized as an industry leader and has been adopted by many Fortune 500 companies across the globe.