Client Overview
A prominent US-based alternative asset management firm was seeking to modernize and streamline the onboarding and data management process for its loan servicers. With a growing number of service relationships and increasing data volumes, the firm needed a unified, high-performance data infrastructure to enable faster onboarding, reduce operational inefficiencies, and support better decision-making.
Problem Statement
The client’s existing data architecture presented several challenges:
- Inconsistent file naming conventions and lack of a centralized data dictionary made processing and ingestion inefficient.
- Repetitive data entries and duplication led to poor query performance and excessive storage usage.
- Non-standardized schemas across servicers caused fragmentation and hindered smooth onboarding and reporting workflows.
These issues resulted in delayed insights, high manual intervention, and a lack of scalable infrastructure to onboard new servicers efficiently.
Solution Provided
Decimal Point Analytics introduced a future-ready data architecture built on** Databricks**, replacing the legacy SQL-based environment. Key solution highlights included:
- Standardized file templates across 12 loan servicers, ensuring consistency from data ingestion onward.
- Normalized schemas for US and UK servicers integrated into a unified Silver Layer—enabling structured, accurate data flow across systems.
- Deployment of a centralized, ACID-compliant data warehouse using Delta Lake for reliable, durable data storage.
- Utilization of Databricks' Spark engine to deliver real-time data processing and significantly enhance query execution speeds.
This architecture provided a strong foundation for machine learning and analytics integration while improving overall operational efficiency.
Outcome
The new data framework resulted in measurable business outcomes:
Improved storage efficiency by minimizing column count in the Silver Layer
Significantly faster data processing and retrieval
Reliable, centralized data structure for governance and analysis
Seamless onboarding workflows for both new and existing servicers
The transformation supported the firm’s growth by reducing complexity, enabling faster insight delivery, and creating a scalable operational backbone.
Key Takeaway
Migrating to a Databricks-powered architecture enabled the client to eliminate data silos, standardize onboarding, and support real-time analytics—all without expanding operational load. The solution delivered both immediate efficiencies and long-term scalability.
Is your organization facing delays in onboarding or struggling with inconsistent data processes?
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