Revive Previously Rejected Loan Applicants
Benefit: Reduce high rejection rates and increase ROI
Why re-evaluate rejected accounts? Because it’s possible that earlier stages in the data waterfall overlooked indications of an applicant’s creditworthiness. By tuning analytics for a “save” strategy, it’s possible to discover these signals of creditworthiness and offer loans to previously rejected applicants ready to become profitable accounts.
Low in the Data Waterfall
Lenders can apply real-time, AI-powered insights to re-analyze rejected applicants for overlooked indications of creditworthiness, allowing them to accept more creditworthy borrowers without investing in additional leads or outbound sales and marketing initiatives. Bottom of the waterfall risk models can also be fine-tuned to suit your particular business goals, profitability model, and budget. In addition, the best models provide easy-to-use APIs, so that building new scores at any location in a waterfall can be done quickly and easily.
AI Lift™ Save applies proprietary AI techniques like machine learning to analyze rejected financial applications for overlooked indications of creditworthiness, enabling companies to say “yes” to profitable applicants they would otherwise have rejected.
Open more profitable accounts.
Using AI Lift, lenders can identify significant numbers of rejected accounts that can be converted to profitable accounts.
Lenders who have implemented AI Lift and opened accounts they would have otherwise rejected have achieved an ROI of 30:1.