American Cycle Finance integrates Scienaptic’s AI-powered credit decisioning platform
By Pavithra R
Scienaptic AI, an AI-powered credit underwriting company equipping financial institutions with sharper tools to improve credit decisions has announced that American Cycle Finance (ACF) has successfully deployed its platform.
The implementation empowers ACF to assist its partner motorcycle dealers in selling more vehicles to customers with limited or no credit history through AI-driven credit decisions.
“Deploying Scienaptic’s AI-powered credit decisioning platform has resulted in significantly higher automation and credit approvals across portfolios. In one portfolio we are seeing 2X incremental approvals without any increase in risk. As we continue to use Scienaptic’s platform, we look forward to increased approvals and faster decisioning cycles for our customers,” said Ben Donnarumma, President of American Cycle Finance.
With a network of more than 450 motorcycle retailers across 24 states, ACF’s program equips dealers with fast, easy application processing and loan servicing for their motorcycle sales transactions. The integration of Scienaptic’s AI-powered credit decisioning platform makes ACF well positioned to offer enhanced, automated credit decisions to help increase credit availability for its customers.
“ACF is enhancing the buying experience by helping its partners reach more customers, overcoming existing or past credit challenges and get a second chance to finance the motorcycle of their dreams. With Scienaptic’s AI-powered credit decisioning platform, ACF can offer more credit approvals to customers who previously experienced credit turndowns or declines, despite their credit score. We are pleased to help ACF get more motorcycle enthusiasts on the road,” said Pankaj Jain, President of Scienaptic.
Founded in 2014, Scienaptic is on a mission to increase credit availability by transforming technology used in credit decisioning. Its platform Ether Underwrite is creating improvements in higher application approvals (15-40%) and lower credit losses (10-25%) with all the regulatory explainability. The firm uses alternate data, raw trade line-level bureau data and AI to help banks find new credit eligible segments of customers.
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