AI Credit Decisioning Platform Planned for CUs

The new CUSO is a partnership with Corridor Platforms, a fintech firm founded by CEO Manish Gupta. Gupta is a 30-year financial services veteran who previously served as an EVP at American Express, where he led the company's global migration to big data and machine learning platforms for analytics and decisioning. His co-founder and Corridor's Chairman, Ash Gupta, also brings 40 years of experience from American Express, where he drove the transition to big data and AI. Teachers Federal Credit Union brings significant scale to the venture as one of the largest credit unions in the U.S. Headquartered in New York, it manages over $9.9 billion in assets and serves more than 472,000 members across all 50 states. This provides a substantial foundation and real-world testbed for the new AI platform. The initiative aims to solve a core challenge for credit unions: competing with fintechs and large banks that use advanced technology for instant loan approvals. Many credit unions rely on manual underwriting or older, rule-based systems, which are slower and less adept at evaluating members with non-traditional financial profiles. The Precision CUSO platform is designed to give credit unions control over their own AI-driven lending models. It allows each institution to use its own member data to build and refine custom underwriting strategies, rather than outsourcing this core capability to a third-party vendor. The platform's focus extends beyond just initial underwriting to cover the entire member lifecycle, including marketing and portfolio management. It is built to integrate with a credit union's existing systems to fill technology gaps and includes built-in, NCUA-aligned governance and compliance features to manage model risk. Precision CUSO projects that its technology can lead to a 75% automation rate for decisions, a 25% increase in approval rates, a 15% reduction in credit losses, and a 30% cut in operational costs for participating credit unions.