Diffusion in a linear potential in the presence of position-dependent killing is used to mimic a default process. Different assumptions regarding transport coefficients, initial conditions, and elasticity of the killing measure lead to diverse models of bankruptcy.One "stylized fact" is fundamental for our consideration: empirically default is a rather rare event, especially in the investment grade categories of credit ratings. Hence, the action of killing may be considered as a small parameter. In a number of special cases we derive closed-form expressions for the entire term structure of the cumulative probability of default, its hazard rate and intensity. Comparison with historical data on global corporate defaults confirms applicability of the model-independent perturbation method for companies in the investment grade categories of credit ratings and allows for differentiation between "microscopic" models of bankruptcy in the high-yield categories. PACS numbers: 89.65Gh, 05.40.Jc, 05.90.+m 1. Introduction. Stochastic modeling of the time evolution of complex systems has a long history in natural and social sciences [ 1 2 ]. Remarkably, the first probabilistic formulation of the Brownian motion was related to valuation of stock options by Bachelier [ 3 ]. The price of an option is derived from the present price of the underlining equity and depends upon its stochastic evolution over time. Bachelier postulated that at any given time the future of 2 the stock price is entirely determined by its present value. This assumption is the same as the one used by Einstein in his derivation of the diffusion coefficient of Brownian particles in terms of microscopic fluctuations of their positions [ 4 ]. Now it is known as the Markov postulate. Both Bachelier and Einstein assumed that the time evolution of the system -the stock price and the location of a Brownian particle, respectively -follows the diffusion process. Further development of the Bachelier's model lead to realization that a better description of equity markets can be achieved under the assumption that the logarithm of the stock price is evolving in accordance with the generalized Wiener process with a non-zero drift (the geometric Brownian motion, see, e.g., [ 5 ]). This approximation lays in the foundation of the Black-Scholes-Merton framework, which is commonly used to price equity derivatives [ 6 ] and in the "structural" models of default [ 7 8 9 ]. Events on stock and credit markets are interrelated, complex, and fundamentally indeterminate. Nevertheless, similarly to natural sciences, an adequate representation of phenomena in financial economy may be obtained by using certain phenomenological constructs augmented by measurements of relevant "macroscopic" variables. For instance, in survival analysis and reliability theory the likelihood of destruction is characterized by the relevant time-dependent hazard rate function [ 10 11 ]. It determines the risk of failure as a function of time, conditional on not having happened previously. In essence, it desc...