Risk Assessment of Non-Performing Loans (NPL) Using System Failure Analysis

This paper answers two research questions: what is the appropriate modeling tool for NPL study? and whether the NPL rates in Thailand show improving or deteriorating trend? NPL is of interests to management decision makers because it serves as an indicator for assessing risk in commercial loans. The methodologies employed in this research are the hazard function: under Weibull and survivor function: . Conventional time series models, such as AR, MA, ARIMA and ARIMAV are not adequate to deal with short term risk assessment due to restrictive assumptions in autoregressive modeling and the requirement of longer observation period. This research fills the gap in the literature left by conventional time series modeling. NPL data of ten industries in Thailand for a period of eight operating quarters from 2013 to 2014 were used. It was found that four industries manifest  indicating an increasing trend of failure and six industries showing . The finding has p-value of 0.004. Viewed as system failure, Thailand’s NPL failure reliability is using mean NPL as predictor. This research proposes system failure analysis method as an alternative to time series modeling for short-term risk assessment in NPL studies.