Helping USDA Better Gauge the Impact of New Policies
By implementing advanced analytical techniques, USDA Rural Development (RD) can quantify the key drivers of risk in its portfolio, estimate risks and subsidy costs at the loan-level, and better gauge the risk and mission impact of new policies.
Client: U.S. Department of Agriculture (USDA)
Challenge: USDA Rural Development (USDA RD) manages a multi-billion dollar Business and Industry (B&I) Loan Guarantee Program. Faced with substantial increases in program demand spurred by the American Recovery and Reinvestment Act, USDA RD set a goal to enhance its risk management and budgeting capabilities, including more accurate credit subsidy rate calculations. USDA RD recognized that strengthening these areas would help them more accurately forecast portfolio performance, protect against excessive credit losses, and effectively use its finite credit budget.
USDA RD hired FI to analyze its historical portfolio performance, develop new models of loan default and prepayment, incorporate these models into USDA’s credit subsidy budgeting and financial reporting processes, and facilitate the models through Office of Management and Budget (OMB) review and approval.
FI Solution: FI’s key deliverable was a series of econometric models that predict default and prepayment on USDA RD business loan guarantees at the loan-level.
FI began by conducting a detailed analysis of B&I program regulations, operating procedures, and policy history. We obtained historical transaction and position data from USDA RD’s systems, assessed it for quality using a series of automated tests, and converted raw data into datasets structured to support analysis. We used these datasets to estimate econometric equations that correlate default and prepayment activity with macroeconomic conditions, and with loan, borrower, and lender characteristics. After testing more than one hundred alternative equations, we selected final equations that balance efficiency and explanatory power.
From our experience supporting Federal credit agencies, we understood the inter-organizational dynamics of implementing model changes. As USDA RD’s adoption of the model is subject to approval by OMB, we sought to engage OMB early in the process and solicit their input on major methodological decisions. Also, as modeling results feed into USDA RD’s financial statement audit, we ensured that we maintained an audit trail, effective documentation, and a transparent analytical approach.
FI Impact: FI helped USDA RD gain new insights and capabilities to manage its multi-billion dollar business loan guarantee portfolio. USDA better understands program performance and risk drivers, and can make better-informed policy decisions in support of its mission.