A novel fuzzy neural approach to data reconstruction and failure prediction
Abstract
Bank failure prediction is of great importance to a bank's clients, policy‐makers and regulators. Various traditional models have been employed to study bank failures. Unfortunately, their performances are unsatisfactory. In this paper, the pseudo‐outer product fuzzy neural network using the compositional rule of inference and singleton fuzzifier (POPFNN‐CRI(S))‐based bank failure prediction model is proposed. It employs computational bank failure analysis techniques coupled with reconstruction of missing financial data in financial covariates that are available from publicly available financial statements as inputs. The performance of the proposed model is assessed through the classification rate of 3636 US banks observed over a 21‐year period. The effects of missing data reconstruction are investigated. Copyright © 2009 John Wiley & Sons, Ltd.
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The neural network approach offers a more general model in bankruptcy prediction problems.
“According to Quek, et al. (2009, p.166), “the neural network approach offers a more general model in bankruptcy prediction problems.””
From A Neural Network Approach to Estimating the Allowance for Bad Debt (2011) · cites this paper as Quek, et al. (2009)
The artificial neural network approach does not assume any probability distribution or equal dispersion for its data.
“The ANN approach does not assume any probability distribution or equal dispersion for its data.”
From A Neural Network Approach to Estimating the Allowance for Bad Debt (2011) · cites this paper as Quek, et al. (2009)
While artificial neural networks provide more accurate results than traditional statistical models, they offer little rational explanatory capability.
“The authors acknowledge that while ANNs provide more accurate results than traditional statistical models, it offers little rational explanatory capabilities.”
From A Neural Network Approach to Estimating the Allowance for Bad Debt (2011) · cites this paper as Quek, et al. (2009)
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A Neural Network Approach to Estimating the Allowance for Bad Debt
Joyner, D. (2011) · VCU Libraries · doi:10.25772/h720-xy24 · Cited by 2 · see citing works
- Authors
- Quek, C., Zhou, R. W., & Lee, C. H.
- Affiliations
- Nanyang Technological University (SG)
- Southwestern University of Finance and Economics (CN)
- Corresponding author
- Quek, C.
- ORCID
- Venue
- Intelligent Systems in Accounting, Finance and Management
- Publisher
- Wiley
- Published
- 2009-01
- Volume
- 16
- Issue
- 1-2
- Pages
- 165-187
- ISSN
- 1055-615X (ISSN-L)
- 1550-1949
- 2160-0074
- OpenAlex
- W4240765060
- Cited by
- 15
- References
- 0
- Citations by year
- 2020: 1 · 2018: 1 · 2017: 3 · 2016: 5 · 2015: 1 · 2014: 1
- FWCI
- 3.57
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Intelligent systems in accounting, finance and management/Intelligent systems in accounting, finance & management (publishedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Accounting › Financial Distress and Bankruptcy Prediction
- Social Sciences › Economics, Econometrics and Finance › Finance › Banking stability, regulation, efficiency
- Physical Sciences › Computer Science › Artificial Intelligence › Fuzzy Logic and Control Systems
- Keywords
- bank failure prediction, fuzzy neural network, compositional rule of inference, missing data imputation, financial statements, bank classification
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