Once a customer is approved for credit, a critical point remains - how do you optimize offer uptake and repayment?
SAVVI FinTech clients typically offer multiple different options of term loans available to people who have been pre-approved for a credit offer. Presenting a laundry list of possibilities just leads to breakage and abandonment. Currently, it’s a guessing game for many FinTechs of which offer the customer is most likely to accept, and repay in a timely manner.
FinTech clients use SAVVI to decide the correct order of the term loan offers - ensuring the one that is both most likely to be accepted with the highest margin at the top. SAVVI then continues to learn as the client serves more term loan offers, tracking which were accepted and which were ignored, to further enhance the underlying Machine Learning powered decisioning.
Integrating was just super easy. It gave us ML functionality we needed quickly, without having to build it from scratch.