- Stratyfy developed predictive models and strategies to show how its Probabilistic Rules Engine.
- A potential for financial institutions to attract more creditworthy customers, increase profitability, and decrease financial risk.
OUR TAKE
Successfully improve credit decision-making with AI, which benefits both lenders and borrowers. By expanding financial institutions’ access to advanced machine learning, more lenders can be helped increase profits while ensuring regulatory compliance and driving financial inclusion.
–Revel Cheng, BTW reporter
Stratyfy, a women-led fintech company, has revealed that its advanced AI technology can significantly enhance credit decisioning processes for small to midsize banks.
What happened
Leveraging Equifax credit data, Stratyfy developed predictive models and strategies to show how its Probabilistic Rules Engine (PRE) compares to traditional decisioning methods in the US.
According to its 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.”
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Why it’s important
Stratyfy’s PRE identified nearly twice as many pre-qualified loan applicants compared to traditional decisioning methods, and achieved an 11 per cent decrease in the bad rate among qualified consumers compared to average credit decisioning methodologies. Seven-point increase in average VantageScore (credit score) for qualified consumers with PRE. Four per cent increase in average monthly income among qualified consumers, as a result of implementing PRE.
Stratyfy’s PRE enables lenders to set their own thresholds for approvals and customise their strategies to specific risk factors, bringing greater flexibility and control to financial institutions in their qualification policies and criteria.
It 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’s PRE pairs data-driven insights with human expertise, allowing lenders to incorporate information like market conditions and emerging risk factors into its models.
