R-G Federal Credit Union cuts indirect auto loan losses 33% with Scienaptic AI credit decisioning

R-G Federal Credit Union, chartered in 1957 to serve military and civilian personnel at Richards-Gebaur Air Force Base, has since expanded its membership across multiple Missouri counties—including Jackson, Cass, Johnson, and Bates. Its indirect auto lending carried loss exposure.

R-G FCU deployed the credit decisioning platform of Scienaptic AI, a company founded in 2014 with a mission of financial inclusion, to automate underwriting across its consumer lending portfolios. The platform integrates more data into decision-making and uses advanced machine learning algorithms, supplemented by rigorous risk and fair lending monitoring processes. Scienaptic says this lets financial institutions reach more borrowers, including underbanked and underserved individuals. The deployment was announced as live in March 2026, covering consumer lending including the indirect auto channel.

Following go-live, R-G FCU achieved measurable improvements across both loss performance and operational throughput:

• 33% reduction in losses on indirect auto loans
• Up to 68% of consumer lending decisions now handled automatically
• Faster loan approvals
• Compliance and fair lending standards maintained

President and CEO Steve Deere noted the platform enabled greater speed and consistency without compromising prudent risk management.

• AI credit decisioning can reduce indirect auto loan losses meaningfully while speeding approvals—automation and risk discipline can be complementary.
• Credit unions with community or military heritage can adopt AI underwriting while preserving member-first values; fairness monitoring built into the platform is essential to maintaining that trust.