Numerica Credit Union selects Scienaptic AI to enhance AI credit decisioning
By Pavithra R
Scienaptic AI, a leading global AI-powered credit decision platform provider has announced that Numerica Credit Union has selected the firm’s AI-powered platform to enhance its overall credit decisioning for several of its lending products and services, including consumer and commercial underwriting, CLI for credit cards, preapprovals, best credit product recommendations for members and credit risk assessment for the institution’s treasury services.
“Numerica’s core purpose is to enhance the lives of our members, fulfill their dreams and enrich our local communities. Scienaptic’s platform will support our mission and deliver automated decisions across commercial and consumer underwriting, allowing us to serve more members when they need us most. The platform will help us increase loan approval rates and extend more credit to current and potential members while advancing their financial well-being,” said Ken Plank, Chief Lending Officer at Numerica.
Established in 1937, Numerica Credit Union was initially founded to support railway workers and employees of other transportation systems and shippers. For over 80 years, the credit union has evolved and expanded, and currently, it is serving more than 160,000 members across central and eastern Washington and northern Idaho. The institution offers a full line of financial products and services, including mortgages and business products to help their members and communities live well financially.
“We are very excited to be working with the team at Numerica, helping to empower its credit decisioning for its members. Scienaptic’s adaptive AI will help bolster the institution’s reach and speed for its credit approvals, enhancing member experience, all without increasing risk,” 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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