In the fast-paced world of mortgage lending, speed and accuracy are crucial. To support their underwriters, Vontive transformed written rules for loan eligibility from a Google Doc into SQL queries for evaluation in a Postgres database. However, while functional, this setup struggled to scale with business growth, resulting in slow, cumbersome processing times. Executing just a handful of loan eligibility rules could take up to 27 seconds–far too long for user-friendly interactions.
In this session, we’ll explore how Vontive reimagined its underwriting operations using Materialize. By offloading complex SQL queries from Postgres to Materialize, Vontive reduced eligibility check times from 27 seconds to under a second. This not only sped up decision-making but also removed limitations on the number of SQL-based underwriting rules, allowing underwriters to process more loans with greater accuracy and confidence. Additionally, this shift enabled the team to implement more automated checks throughout the underwriting process, catching errors earlier and further streamlining operations. Engineering needs were minimal, since DBT supports both cloud-based Postgres and Materialize. Whether you’re in financial services or any data-driven industry, this session offers valuable insights into leveraging fast-changing data for high-stakes decision-making with confidence.