Credit and Loss Models

Our credit and loss models are a key component of our comprehensive CECL solution.

RiskSpan Models

  • RMBS Credit Model
  • Agency Prepayment Model
  • GSE Credit Model
  • Reverse Mortgage Model
  • CMBS Credit Model
  • Auto (ABS) Model

RiskSpan’s proprietary credit and loss models provide traders, research analysts, portfolio managers, and risk managers with an unprecedented view into expected asset performance. RiskSpan’s credit models simultaneously assess multiple risk factors across multiple portfolios, leveraging fully integrated and customized data in real time.

At the security or portfolio level, this modeling capability supports the analysis of risk associated with a portfolio in a changing market while performing enterprise-wide, market-leading analytics for intra day and end-of-day processes.

RiskSpan’s credit and loss modelers also advise accounting departments in the development of Allowance for Loan and Lease Losses (ALLL) models related to many portfolio types. These models support loss estimates compliant with the new CECL standard. Asset types include forward and reverse residential mortgages, commercial mortgages, auto loans, and student loans. Modelers leverage their expertise in SAS, Microsoft Excel, VBA, Intex, and other tools to forecast loan cash flows based on projected credit losses.

RiskSpan professionals fully document the model, describing inputs, calculations, outputs, and critical assumptions used in the model’s creation and during production runs of the models. Clearly written user manuals include succinct instructions on a model’s use.

In addition to developing custom credit and loss models for clients, RiskSpan’s modeling professionals are proficient with commercially available models, such as LoanPerformance RiskModel®, and frequently advise clients on effectively calibrating these models’ projections based on a portfolio’s makeup and historical experience

Prepay Models

RiskSpan’s prepayment modeling and analytics solutions enable clients to quickly transform security-level data into information-based decisions by seamlessly accessing the drivers of prepayment risk and uncovering prepayment trends. A flexible user interface supports intuitive analysis of the prepayment data. The solution enables users to visualize data with integrated graphing capabilities, which deliver actionable reporting in real time.

The intuitive model enables agile decision making by delivering prepayment information based on:

  • Refinancing incentive curves
  • Servicer performance comparisons
  • Key characteristics and composition of outstanding securities
  • User-defined cohort-level performance and trends.

The solution is configured to analyze prepayment data from any source, including unsurpassed access to current and historical data on Ginnie Mae, Fannie Mae, and Freddie Mac securities. The database contains all monthly data published by the agencies back to 1995, including factors, geographic breakdowns, and supplemental disclosure information.