The Role of Financial, Macroeconomic, and Non-financial Information in Bank Loan Default Timing Prediction

We assess the use of bank loan information in predicting the timing to default. We use unique data on defaults in small and medium enterprises maintained by the Central Bank of Portugal which includes financial accounting and macroeconomic indicators, as well as non-financial information. The findin...

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Bibliographic Details
Published in:The European accounting review 2013-12, Vol.22 (4), p.739-763
Main Authors: Bhimani, Alnoor, Gulamhussen, Mohamed Azzim, Lopes, Samuel da Rocha
Format: Article
Language:English
Subjects:
Accounting
Bank loans
Banking industry
Central banks
Default
Financial accounting
Forecasts
GDP
Gross Domestic Product
Information science
Macroeconomics
Portugal
Small & medium sized enterprises-SME
Small and medium sized enterprises
Studies
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Summary:We assess the use of bank loan information in predicting the timing to default. We use unique data on defaults in small and medium enterprises maintained by the Central Bank of Portugal which includes financial accounting and macroeconomic indicators, as well as non-financial information. The findings are indicative of the incremental predictive ability of non-financial information over and above macroeconomic and financial accounting information in the baseline, industry, and in- and out-of-sample models. Specifically, total credit secured by firms is, as expected, negatively and significantly related to default. Gross domestic product is negatively and significantly related to default, and benchmark market rate is positively and significantly associated with default. The findings also reveal that firms which are operated by partners, which have stronger financial support from partners, and which possess operational assets exhibit lower hazards of default. The study indicates that non-financial information and macroeconomic indicators assessed alongside financial accounting data can significantly improve the forecasting performance of default models.
ISSN:0963-8180
1468-4497
DOI:10.1080/09638180.2013.770967