Transforming Federal Lending Program Operations (Part 2 of 3)

Federal credit programs face increasing pressure to modernize aging systems, improve data quality, and meet evolving oversight expectations. Last week, in Episode 1 of this series, we examined why federal credit programs remain hindered by technical debt, outdated models, siloed data, and excessive reliance on manual processes, despite managing more than $5 trillion in loans. Those challenges create real costs: weaker oversight, slower policy response, and reduced public trust.

In Episode 2, our host Kate Lynch Machado, Director of Strategic Growth, continues the conversation with another panel of experts from Summit, Anthony Curcio (Senior Partner), Sarah Cunningham (Partner), and Albert Lee (Founding Partner).

They confront a key question in modernization: Can technology replace domain expertise, or is that expertise still essential for the next generation of federal credit systems?

The bottom line: Expertise is not optional; it’s essential. Modern tools can improve speed, transparency, and efficiency, but they cannot replace the contextual knowledge needed to design federal credit models, ensure compliance standards, or guide policymaking.

Bridging the Gap: The Role of Domain Expertise

What This Episode Covers

•    Why commercial FinTech tools cannot be adopted directly for federal modeling
•    How federal credit programs differ from private-sector lending
•    The role of experts in maintaining transparency, auditability, and public trust
•    Why common data plumbing can be standardized across credit programs
•    How cloud and AI can support—but not replace—expert judgment
•    What agencies need to balance automation with accountability

Modernization often assumes that private-sector analytics tools can transition seamlessly into a federal environment. As Anthony points out, commercial models focus on profit-driven lending, neglecting federal priorities like mission alignment, public trust, budget impacts, and OMB compliance. They cannot meet federal audit requirements, deliver explainable outputs, or integrate with the Credit Subsidy Calculator. Successful modernization requires blending the strengths of private-sector tools with the unique regulatory and policy context of federal credit.

The panel emphasizes that modernization should elevate expert insight, not eliminate it. Cloud infrastructure, automation, and AI can eliminate manual friction, reduce key-person dependency, and improve output consistency. However, interpreting borrower behavior, adjusting models for policy changes, and explaining results to OMB or Congress remain inherently human responsibilities.

This conversation sets the stage for Episode 3, where we’ll dive into the practical side of modernization—how agencies can adopt next-generation, cloud-enabled platforms and standardized data systems to cut technical debt, improve oversight, and build more adaptive and resilient credit operations.

Meet Summit’s Federal Credit Experts

Anthony Curcio, Senior Partner, has spent 20 years translating private-sector risk analytics for federal environments. As a seasoned leader in federal credit policy and budgeting, he is recognized for simplifying complex federal financial systems and has served as an underwriting instructor for multiple federal infrastructure programs.

Sarah Cunningham, Partner, is the former Chief of the Office of Management and Budget (OMB) credit team who oversaw the federal credit portfolio during the Great Recession and later served as the HUD Assistant Chief Financial Officer supporting its $3 trillion portfolio. She has led major credit program designs, modernizations, and policy innovations—including the second-generation OMB credit subsidy calculator, credit performance scorecards, and improved budgetary accounting—while continuing to advise a wide range of federal credit programs as a leading voice in credit policy.

Albert Lee, Founding Partner, is a PhD economist and seasoned modeler of mortgage, multifamily, farm, and student loan portfolios.