FRAUD SCORES
A dynamic scoring model that quantifies the risk of fraudulent behaviour at onboarding and login.
A dynamic scoring model that quantifies the risk of fraudulent behaviour at onboarding and login.
The choice of 150+ financial companies, banks and fintech unicorns
Fraud Scores analyse behavioural and device data to assess whether new users exhibit patterns similar to known fraudulent cases (e.g., identity fraud, bonus abuse, loyalty points abuse).
Enhanced credit decisioning even for thin-file and unbanked applicants
Higher approval rates with reduced default risk
Improved model performance with complementary risk insights
Testimonials
Better scores based on alternative data to complement your existing risk models and underwriting processes
Regional Partners
Flow is a credit management company that is transforming the business of unsecured consumer finance through AI technologies and ethical practices in the APAC region.
Integration Type:
Mobile SDK
Solutions Used:
Tomasz Borowski
CEO
"BAs the CEO of a credit management company, I was looking for the right software solution to support our business operations whilst also promoting ethical and responsible debt collection in underserved Asian economies. Credolab helped us with a powerful scorecard that allowed us to prioritise collection efforts....”
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BNPL
Integration Type:
Mobile SDK
Solutions Used:
Juan Carlos Esquer Ramos
CEO
"As the CEO of ZazPay, navigating the dynamic landscape of financial services in Mexico has been both exhilarating and challenging. When we decided to revamp our internal models and streamline our underwriting processes, we knew we needed a partner who could deliver tangible results....”
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Decision Engines
Integration Type:
Mobile SDK
Solutions Used:
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