Case Study 20: Credit Score Card

For a Fintech Company

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  • The Client is on of the biggest online payment gateways & the Client has about 20 million customers.
  • More than half a million transaction per day are done through the platform, It serves more than 10,000 merchants.
  • The client wanted to extend temporary credit facility to some customers for ease of transactions.
  • There is no customer demographic data for credit scoring, the transactional data is huge and unstructured.
  • G-Square helped build rules on top on transaction and web-behavioural data for credit scoring.
  • Benchmarking was done on actual default/delayed payment data.
  • The rules were automated using big-data tools.
  • Machine learning was used to automatically update the rules on an ongoing basis.
  • A ML driven Buy now and Pay later model was built & handed over to the client where Specific customers could be given or not given the temporary credit facility based on the model
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