How PayJoy accelerated approvals and reduced portfolio risk with AltScore.
The consumer credit fintech in Ecuador integrated alternative data into their machine learning models, evaluating profiles with no credit history in 35 seconds.
Schedule a demoConsumer credit in emerging markets.
PayJoy is a fintech that enables customers in emerging markets to access smartphones and financed products. In Ecuador, a large portion of their customer base has no formal credit history — making it impossible to evaluate them with traditional models.
Traditional models that couldn't see the real customer.
PayJoy needed to originate more credit without increasing their exposure. But conventional models left out the people who needed it most.
Key points:
- Customers with no formal credit history that traditional models couldn't evaluate.
- Qualified profiles automatically classified as high risk, limiting approvals.
- Greater fraud exposure without sufficient data to segment accurately.
- Business profitability and sustainability compromised by decisions based on incomplete information.
From invisible profiles to approvals in seconds.
PayJoy implemented AltScore to enhance their scoring models. By complementing traditional data with information applicable to 99% of the population, they were able to evaluate applications in seconds and segment with greater precision — even customers without formal financial history.
The result is a fairer, more meritocratic process that fosters financial inclusion, reduces origination friction, and lays the foundation for scalable growth.
More inclusion, less risk and fraud.
Evaluated with alternative data in real time.
More precise models to evaluate real risk.
Lower exposure without sacrificing approvals.
Want results like these?
Talk to our team and discover how AltScore can transform your operation.