Case Study: Scratchpay achieves 100%+ throughput improvement and automates data preparation with Hevo Data

Scratchpay Saved Time and Efforts by Automating their Data Preparation Process Using Hevo

Scratchpay, a Los Angeles–based FinTech that provides medical payment plans, faced an ad hoc “dark era” of aperiodic data dumps and manual processing that caused errors and delays—a critical problem since the credit risk team depends on timely, accurate data to build consumer risk models. After evaluating options, Scratchpay selected Hevo Data’s Unified Data Platform (no-code data pipelines) for its broad integrations, ease of use, and Python support.

Hevo Data built automated pipelines that consolidate multiple source systems into Google BigQuery and surface clean data to business users via Google Sheets and Data Studio (with Python integration for on‑the‑fly model retraining). The implementation doubled throughput (>100% improvement), eliminated manual pipelining, drastically reduced data errors, saved engineering hours each week, and enabled faster, deeper analytics across the company.

Scratchpay

Chris Lockhart

Data Science Manager