The risk of default is derived by analyzing the obligor's capacity to repay the debt in accordance with contractual terms.
Credit scores, such as FICO for consumers or bond ratings from S&P, Fitch or Moodys for corporations or governments, typically imply a certain probability of default.
One option is to use CDS implied PD's in conjunction with EDF (Expected Default Frequency) credit measures.
[8][9] This framework, involving the selective use of either PIT or TTC PDs for different purposes, has been successfully implemented in large UK banks with BASEL II AIRB status.
As a first step this framework makes use of Merton approach in which leverage and volatility (or their proxies) are used to create a PD model.
The term TTC applies to PDs that exhibit no such fluctuations, remaining fixed overall even as general credit conditions wax and wane.
The greater accuracy of PIT PDs makes them the preferred choice in such current, risk applications as pricing or portfolio management.
The above framework provides a method to quantify credit cycles, their systematic and random components and resulting PIT and TTC PDs.
This is accomplished for wholesale credit by summarizing, for each of several industries or regions, MKMV EDFs, Kamakura Default Probabilities (KDPs), or some other, comprehensive set of PIT PDs or DRs.
Depending on data availability and portfolio requirements, such indices can be created for various industries and regions with 20+ years covering multiple recessions.
The specific model formulation depends on the features important to each, distinguished class of counterparties and data constraints.
Most PD models output PDs that are of a hybrid nature:[13] they are neither perfectly Point-In-Time (PIT) nor through-the-cycle (TTC).
The simplest approach, taken by many banks, is to use external ratings agencies such as Standard and Poors, Fitch or Moody's Investors Service for estimating PDs from historical default experience.