Introduction 

A subprime lending company desired to refactor their on-prem data into a SaaS based solution. 7 years' worth of data and 27 databases. Modified existing ETL processes and down stream applications for efficiency. New paradigm shift with separation of storage from computation. Aggregated insights to provide better intelligence for underwriting.

Problem Statement

The lender faced significant challenges due to fragmented borrower data, manual credit evaluation workflows, and prolonged underwriting cycles driven by legacy systems that were not designed to ingest and normalize multi-regional data, perform real-time credit assessments, or integrate seamlessly with digital and partner ecosystems. These limitations led to higher operational costs, reduced scalability and availability, and slower time-to-decision. The organization needed a secure, cloud-ready, and modular loan origination platform to unify disparate data sources, automate credit scoring, modernize end-to-end loan workflows, reduce Total Cost of Ownership (TCO), enable rapid partner integration, and ensure full compliance with regulatory and financial standards. 

• Manual dependency across borrower onboarding and underwriting.

• Siloed data sources across regions.

• Limited accuracy in traditional loan-approval models.

• Legacy infrastructure unable to support new digital loan journeys.

• Customer Traceability

• Dynamic Reporting

• Cross Selling Tools

• Storage & Compute Separation

• Data feed For Underwriting

• Event-driven paradigm

Technological Framework:

Why this setup?

Snowflake's separation of storage and compute enables instant scalability and cost efficiency, while AzureML and Tableau deliver predictive analytics and executive-level dashboards over a unified customer view.

Why this setup?

Azure Event Grid enables real-time, event-driven data propagation for near-instant underwriting feeds, while Azure Insights provides end-to-end observability of all data pipeline activities.

Why this setup?

Event-driven integration with downstream applications ensures underwriting teams always have access to the most current customer data, enabling faster and more accurate lending decisions.

Takeaway

Zapcom transformed a fragmented, 27-database on-premise estate into a unified Snowflake-powered data warehouse, achieving 60% infrastructure cost reduction, 23% improvement in repayments, and a complete cross-product customer view.