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Case Study: Stratyfy’s AI Enables Better Credit Decisions and Portfolio Growth

June 17, 2024 | Originally published on The Fintech Times


Leveraging Equifax credit data, Stratyfy developed predictive models and strategies to show how its approach compares to traditional decisioning methods in the US.

According to the study, Stratyfy’s approach can identify nearly twice as many pre-qualified loan applicants compared to traditional methods, while also reducing the overall rate of bad loans. This indicates a potential for financial institutions to attract more creditworthy customers, increase profitability, and decrease financial risk. Additionally, it suggests that more borrowers could gain access to affordable credit.

“At Stratyfy, we believe that accurate, interpretable AI in financial services should be a baseline – and that data is a force for good,” said Laura Kornhauser, CEO and co-founder of Stratyfy. “Today’s findings indicate that we can successfully improve credit decisioning using AI that benefits both lenders and borrowers alike. By expanding access to advanced machine learning at financial institutions, we can help more lenders grow their bottom lines, while ensuring regulatory compliance and driving financial inclusion.”

Key results from the Stratyfy – Equifax partnership:
  • Stratyfy identified nearly twice as many pre-qualified loan applicants compared to traditional decisioning methods, and achieved an 11% decrease in the bad rate among qualified consumers compared to average credit decisioning methodologies
  • 7-point increase in average VantageScore (credit score) for qualified consumers with Stratyfy
  • 4% increase in average monthly income among qualified consumers, as a result of implementing Stratyfy

Stratyfy enables lenders to set their own thresholds for approvals and customize their strategies to specific risk factors, bringing greater flexibility and control to financial institutions in their qualification policies and criteria.

It also offers visibility in decisioning, allowing lenders to clearly explain any predictions, such as ‘bad’ loan performance, to customers, regulators, and other stakeholders based on clear, interpretable rules. Finally, Stratyfy pairs data-driven insights with human expertise, allowing lenders to incorporate information like market conditions and emerging risk factors into its models.

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