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Build vs. Buy: The Hidden Costs of DIY Loan Data Infrastructure

20 February 2025

For both issuers and investors, loan data infrastructure is the backbone of their operations. Whether you're an issuer managing credit facilities and securitizations or an investor evaluating loan pools and tracking portfolio performance, the ability to seamlessly process, analyze, and report on loan data is essential.

As origination and deal volume grows, so do the demands for accurate, timely, and standardized reporting—which is why issuers and investors alike need a system that scales effortlessly, eliminates inefficiencies, and provides visibility into loan performance.

Yet, many firms attempt to build their own infrastructure instead of leveraging an existing, purpose-built solution like dv01. While building in-house seems like a cost-effective and customizable approach, the reality is that building and maintaining internal loan data infrastructure is costly, inefficient, and diverts resources away from core business priorities.

The Real Costs of Building In-House

1. Development Takes Time—And Time is Money

For Issuers: Loan data management isn’t just about storage—it requires sophisticated ingestion, validation, modeling, and reporting for credit facilities, securitizations, and private credit transactions.
For Investors: Investors must aggregate and normalize data from multiple originators and servicers before they can even begin to analyze portfolio performance.
Why dv01: Custom-built infrastructure requires significant engineering and data science resources. Building a system from scratch can take years, delaying efficiencies and adding strain to internal teams. With dv01, we handle the entire data cleansing process—ensuring loan data is standardized, validated, and ready for analysis—and we make it readily accessible via our web app with embedded tooling, SFTP, or seamless integration with BigQuery, API, Snowflake, S3, and other data lakes and databases.

2. Ongoing Maintenance Drains Resources

For Issuers: Loan data reporting isn’t static—new deal structures, servicer data formats, and regulatory requirements create a constant need for updates.
For Investors: Investors require ongoing portfolio surveillance and performance tracking—but a DIY system means constantly maintaining data pipelines, validation frameworks, and analytics tools.
Why dv01: Every hour spent debugging a homegrown tool is time taken away from closing deals, optimizing financing, and other strategic decision making. dv01’s automated infrastructure ingests, normalizes, and validates loan-level data in real-time, so firms can focus on strategy, not system upkeep.

3. Data Validation and Standardization Isn’t Easy

For Issuers: Without a robust system in place, issuers risk errors in performance reporting, delays in transaction execution, and compliance headaches.
For Investors: Investors require loan-level visibility to evaluate risk and performance—but disparate data formats, missing fields, and inconsistent reporting make analysis difficult.
Why dv01: Cleaning, standardizing, and validating loan-level data is one of the most challenging aspects of infrastructure development. ddv01 understands the nuances of structured products, ensuring loan data is complete, accurate, and analysis-ready—without the manual lift.

4. Scalability Becomes a Bottleneck

For Issuers: As portfolios and deal volume grow, homegrown tools often fail to keep up with data standardization, performance reporting, and investor transparency needs.
For Investors: As investment portfolios expand, homegrown tools often fail to integrate new data sources, support multi-asset analysis, or provide scalable risk modeling.
Why dv01: Many firms start with a basic internal system that works—until it doesn’t. dv01’s infrastructure is built to scale, seamlessly handling increased deal flow, multiple asset types, and growing investor demands.

5. Opportunity Cost: What Could You Be Doing Instead?

For Issuers: Instead of allocating engineering resources to fixing reporting inefficiencies, issuers could be optimizing financing structures, securing better investor terms, and expanding deal flow.
For Investors: Instead of spending time cleaning, reconciling, and validating raw data, investors could be refining credit strategies, improving risk assessment, and identifying market opportunities
Why dv01: TThe best issuers and investors don’t compete on tech—they compete on execution. dv01 allows firms to focus on growth, capital optimization, and investment strategy—while we handle the infrastructure.

The Smarter Approach: Purpose-Built Loan-Level Data Infrastructure

Instead of sinking time and capital into building a solution from scratch, issuers and investors can leverage dv01’s end-to-end loan data infrastructure—powering everything from data ingestion and management to performance tracking and investor reporting.

Loan Performance Monitoring: Track performance at the loan level in real-time, whether loans sit on a balance sheet, in a facility, sold or securitized.
Automated Data Standardization: No more scrambling to clean servicer data or reconcile reports.
Transaction and Investor Reporting: Whether it’s a securitization or private credit transaction, dv01 delivers standardized, high-quality reports investors and lenders can trust.
Credit Facility Optimization: Gain full visibility into borrowing capacity and asset performance across warehouse lines.
Market Benchmarking: Compare loan performance against industry peers with historical and live market data.

Final Thoughts

The question shouldn’t just be, “Can we build this?” but “Should we?” The hidden costs of DIY infrastructure often outweigh the perceived benefits, slowing down operations and adding unnecessary complexity.

By choosing dv01’s purpose-built infrastructure, firms can focus on execution rather than technology maintenance—gaining a competitive edge in financing, investment strategy, and market transparency.