Case studies

Transforming Insights Codvo's Fintech Data Journey with Snowflake

About the client

Our client is transforming the world of lease-to-own with transparent lease-purchase plans that flex to meet the needs of consumers who are overlooked by traditional credit.

With proprietary machine learning (ML) models, the client predicts consumer behavior more accurately than traditional credit scores. Thus, providing new paths to ownership for people and new customers for omnichannel retailers.


This project's scope was to utilize Snowflake and deliver business value using a targeted but extensive customer & product data set.

Data Engineering played a role in writing the ETL and building the integrations around the technology to feed data and make it available to consumers.

The plan was to build the Enterprise Data Warehouse System using snowflake, including ODS as  Data Lake, Fivetran as ETL plus DBT, and Data Orchestrations using snowflake inbuilt.

The primary objective was to complete data migration of critical customer and product data.

Business Challenge

Overcoming limitations from a Platform that can’t scale​.

The fintech company's previous data warehouse could not scale to the company's needs and was very limited in terms of security. So, they started looking for a more scalable and cost-effective solution.

Our Approach and Solution

A platform that can scale to meet current & future demands.

  • After evaluating various options, our consulting team proposed that snowflake would be the best solution for a new platform.
  • Client team saw the value in how storage had been decoupled from the compute resources. We knew this would provide a cost-effective way of scaling up as needed.
  • Snowflake deployed & Critical Data Migration from multiple sources like existing Data bases, Hubspot, Segments, Five9, etc done within 6 months.

Tech Stack

The tech stack used: Snowflake, Fivetran, Twilio segment, AWS S3.


Business Impact

With Snowflake’s platforms fully operational, tech team at client company quickly began the experience significant benefits.
Queries that took more than 20 minutes to complete are now being returned in less than 10 mins post data migration.
Hubspot data and Segment data, which were not utilized for making decisions, are now being utilized on other use cases like developing a customer propensity model.
Few more incoming source data will be migrated to snowflake, and company will start utilizing snowflake as EDW.