Strategic risk modeling enables greater accuracy in financial forecasting, providing valuable insights into loan profitability. University Financial Associates (UFA) offers models and tools for reliable loan forecasts. Here is more information about types of credit risk modeling strategies:
Credit Risk Modeling
Evaluating credit risk allows lenders to determine whether a borrower is not likely to meet their loan terms. Modeling works by inputting borrower information into a processing engine, which converts the data into risk projections. The reporting tools translate the projections as actionable business data.
Using statistical and economic techniques during credit risk modeling creates accurate financial insights. These techniques include utilizing multiple factors, such as:
- Borrower credit data
- Product structure
- Collateral data
Borrower data is a factor in traditional modeling; it includes current financial information, such as cash flow, free assets, and past repayment patterns. This information enables lenders and investors to assess the likelihood of default and establish accurate loan prices based on credit risk. UFA offers our ForeScore™ suite as a set of modeling tools that analyze these factors to identify profitable loan terms.
Location-Based Modeling
Utilizing only historical borrower information for projections can impact their accuracy. Modeling strategies include utilizing location as a factor in risk modeling; this enhances precision. This allows lenders to analyze economic and demographic conditions that can impact the borrower’s ability to fulfill loan requirements. These conditions include local infrastructure investment, employment rates, schooling, and housing patterns.
Having information about the conditions for modeling allows lenders to assign geographic risk thresholds. Areas prone to flooding, fires, tornadoes, or other natural disasters can increase the risk that the borrower will experience home or car damage. Asset values are also dependent on disaster risks. Knowing high- and low-risk areas helps lenders to form geographic-dependent strategies, such as avoiding loans in specific areas. We offer ForeScore™ Zip Default and Zip Value tools to measure the impact on future economic conditions on loans and predict cash flows. The Zip Value also helps find differences in profits gained in different areas.
Stress Testing
Creating financial projections across different economic scenarios allows lenders to fully assess credit risk; this may include recession and high unemployment rates. Stress testing identifies value-at-risk metrics. Being prepared for various economic factors when setting loan terms allows lenders to limit their risks. Our ForeScore™ Risk Analyzer analyzes individual loans or loan pools by simulating a range of realistic economic scenarios. This tool outputs static cumulative losses and annual risk conditions, and this information can be used to create pool performance projections. This helps with mortgage and auto portfolios.
Learn More About Our Modeling Tools
Financial applications for our analyses include forecasting loan loss reserves, defining relationship values with borrowers, and calculating portfolio sales. Our ForeScore™ Loan Analyzer tool provides automated decisions and informative risk analysis, and the ForeScore™ Portfolio Analyzer tool analyzes portfolio risks and performance trends to facilitate performance improvement and rewards. We also offer access to indices and studies. Contact UFA to learn more about our ForeScore Suite and analytic services.