“Estimation of Probability of Defaults (PD) for Low Default Portfolios: An Actuarial Approach”

Global financial crises like the one recently experienced, affected both large and small institutions. Today, when there is heightened need for enhanced risk management tools, there are entities that are unable to employ sophisticated mechanisms due to limited data availability. Moreover, from the Basel II and Basel III point of view, Internal Ratings Based Approach requires that institutions have some reliable estimates of probabilities of default for each rating grade. Taking the work of previous researches a step further, this paper intends to propose a new dynamic mechanism to the risk management industry for calculating probabilities of default (PD). Through this, we calculate the realized probability of defaults and Bayesian estimates in the initial phase and then using these estimates as inputs for the core model, we generate Implied Probability of Default (PD) through actuarial estimation tools and different probability distributions. This mechanism is specialized to work best for Low Default Portfolios (LDPs). Furthermore, scenario testing is adopted to validate the model against any model specific bias.