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Heritage Financial Credit Union selects Scienaptic to bolster its credit decisioning and financial options

By Pavithra R

June 08, 2021

  • America
  • Heritage
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Heritage Financial Credit Union selects Scienaptic to bolster credit decisioning and financial options Scienaptic AI, an AI-powered credit underwriting company equipping financial institutions with sharper tools to improve credit decisions has announced that Heritage Financial Credit Union has chosen to implement its AI-powered platform to enhance its credit decisioning and strengthen financial options for its members.

“We are excited to partner with Heritage Financial, helping to empower the credit union’s credit decisioning and availability for its members. Scienaptic’s unique, adaptive AI will help enhance the institution’s credit strategies, increasing approvals and deepening member experience,” said Pankaj Jain, President of Scienaptic.

Founded in 1940, Heritage Financial Credit Union is a member-owned, not-for-profit financial institution serving in and around the Hudson Valley communities for over 80 years. As an organization, Heritage Financial CU is focused on the financial well-being of its members, offering best-in-class financial products and services as well as an online banking platform that allows their membership to bank from the comfort of their preferred digital device.

“Empowering and supporting the financial growth of our members, both current and prospective, is something we hold in high regard and anything we can do to help enhance their experience is vital. With Scienaptic, we can increase loan approval rates, reduce decision times and offer credit to more potential members, helping them to better achieve their financial goals,” said Michael Ciriello, President and CEO at Heritage Financial Credit Union.

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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