The Inflow into the Non-Performing Loans Ratio as a Measure of Credit Risk: Analysis and Application in the Chilean Case

Andres Sanger T.

doi:10.4067/S0718-88702012000100002

Authors

Andres Sanger T. Banco Central de Chile

DOI:

https://doi.org/10.4067/S0718-88702012000100002

Keywords:

Credit risk, credit, loan accounting, general statistics, out-ofsample forecasts

Abstract

This paper proposes the inflow into non-performing loans (INPL) ratio, defined as the change in the stock of non-performing loans adjusted by write-offs and standardized by loans, as the main measure to be used for modelling the credit risk of the Chilean banking system. In particular, the paper identifies certain statistical and conceptual advantages of this measure with respect to loan loss provisions (LLP), which support this idea. First, the INPL ratio by type of credit has a greater time span than LLP. Second, the forward-looking nature of LLP –one of its main advantages over the INPL ratio– is applicable only from 2004 onward due to various changes in Chilean reporting standards. Third, LLP is discretionary because provisioning is made on the basis of relative risk aversion of banks. Fourth, the INPL ratio produces smoother series than LLP for consumer and mortgage loans. In addition, the dynamic structure observed in both time series does not differ significantly. The econometric model estimated for the period January 1997 to June 2010 shows that the INPL ratio has statistically significant relations with macroeconomic aggregates such as the annual output growth, the short and long term interest rates, the annual inflation rate, the peso-dollar exchange rate, and non expected credit growth. Finally, the out-of-sample forecasts indicate differences between the actual and projected INPL ratios that are economically significant only in the case of mortgage credit. For the remaining portfolios, the evolution of this ratio during the period of July 2008 to June 2010 does not differ significantly from that predicted by the econometric model.

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