PD Models

A Probability of Default Model (PD Model) is?any formal quantification framework that enables the calculation of a Probability of Default risk measure on the basis of quantitative and qualitative information.

PD is the risk that the borrower will be unable or unwilling to repay its debt in full or on time. The risk of default is derived by analyzing the obligor's capacity to repay the debt in accordance with contractual terms. PD is generally associated with financial characteristics such as inadequate cash flow to service debt, declining revenues or operating margins, high leverage, declining or marginal liquidity, and the inability to successfully implement a business plan. In addition to these quantifiable factors, the borrower's willingness to repay also must be evaluated.

OFS Loan Loss Forecasting and Provisioning PD Modelling accurately predicts the number of defaults by omitting optimism or conservatism. Adjustments are made on regulatory capital models to remove inherent conservatism. Estimated PDs are point-in-time. These are adjusted, where necessary, to reflect the effects of the current economic conditions. The PD estimates are recalibrated based on the current representative sample regularly. PD is calculated using a sufficient sample size and historical loss data covers at least one full credit cycle.

PD model segments consider drivers in respect of borrower risk, transaction risk, and delinquency status. The PD models are representative of the portfolio segments. The data used for calibration is consistent with the IFRS 9 default definition throughout. Techniques used to determine lifetime PD measures do not introduce bias into the calculation. Future projected macroeconomic factors are used in the computation of lifetime PD's. The risk of default is higher when the expected life of the instrument considering cumulative probability is longer.

The LLFP application calculates Cumulative PD and Final Marginal PD using a conditional probability logic. The PD calculation can be performed as mentioned in the following processes:

·????????Calculation of Marginal PD whenever Cumulative PD is provided as a download using a Conditional Probability Logic.

·????????Computation of the Factor - Lambda, Geometric factor, or Arithmetic factor, depending on the Interpolation technique, using the given formula.

·????????Computation of Intermediate Cumulative PD using the given formula.

·????????Computation of Intermediate Marginal PD using the conditional probability approach, for each block of time.

·????????Computation of Final Cumulative PD by using the conditional probability approach, cumulating across periods till the max maturity bucket. This value is used for the Cash Flow approach.

·????????Computation of Final Intermediate PD by subtracting each cumulative PD with the preceding Cumulative PD. This value is used for the Forward Exposure approach.