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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