The Development and Implementation of a Loan Classification Database System
Автор: Eludire A. A.
Журнал: International Journal of Information Technology and Computer Science(IJITCS) @ijitcs
Статья в выпуске: 2 Vol. 8, 2016 года.
Бесплатный доступ
This work documents the development and implementation of a commercial bank's loan classification database system. It employed multiple discriminant analysis models to assess the relationship between relevant loan variables and existing bad loan problem. It also made use of mathematical model to replicate the Examiner's classification process to classify loans in a more objective and sober way. Classification of loan is grouping of loans in accordance to their likelihood of ultimate recovery from borrowers. Banking business is one of the most highly levered businesses especially on loan accounts. It is likely to collapse in case of a slight deterioration in quality of loans. Six important factors (propriety of use of funds borrowed; operation of Borrower's overdraft account; cooperation with the Bank, collateral and number of days the loan is past due) were identified and grouped as variables in determining the quality of loan portfolio. The developed classification model shows that there exists a linear relation between loan classification and the six variables considered. Four classification functions were developed and implemented in Microsoft Access database to assist in effective classification. The implementation of a database system makes it easy to store relevant classification information and revert to them whenever needed for comparative analysis on quarterly, half-yearly and annual basis.
Bank, Loan, Collateral, Classification, Provision, Loss, Database
Короткий адрес: https://sciup.org/15012431
IDR: 15012431
Список литературы The Development and Implementation of a Loan Classification Database System
- Banker, (December, 1992) "Nemesis strikes the Nordics" p.20 - 23.
- Banker, (January, 1995) "Japan: Pain in store" p. 44.
- Nigeria's Bank Firings, Audits and Related EFCC Activities, August 18th, 2009 http://www.informationnigeria.org/tag/central-bank-of-nigeria
- EFCC boss says it has recovered N103 billion from bank debtors, Information Nigeria Sep 29, 2009 http://www.informationnigeria.org /2009/09/efcc-boss-says-it-has-recovered-n103.html#ixzz0vyfuLTJi
- Edward I. Altman, “Financial Ratios, Discriminant Analysis, and the Prediction of Corporate Bankruptcy,” Journal of Finance, September 1968, pp. 589–609.
- Edward I. Altman, Robert G. Haldeman and P. Narayanan, “Zeta Analysis: A New Model to Identify Bankruptcy Risk of Corporations,” Journal of Banking and Finance, June 1977, pp. 29–54.
- Edward I. Altman, John Hartzell and Matthew Peck, “Emerging Market Corporate Bonds, A Scoring System,” Emerging Corporate Bond Research: Emerging Markets, Salomon Brothers, May 15, 1995.
- Marais, M.L, J.M. Pattel and M.A. Wolfson (1984), "the experimental Design of Classification Models: An Application of Recursive Partitioning and Boot strapping to Commercial Bank Loan Classification". Journal of Accounting Research Vol. XVII, No. 2, p. 227 - 240.
- Sinkey, J. F (1989) “Commercial Bank Financial Management in Financial Services", 3rd Ed, Macmillan Publishing Company. New York.
- Giovanni Majnon and Alain Laurin Bank Loan Classification and Provisioning Practices in Selected Developed and Emerging Countries March 2003 Pages: 64 Available online: http://elibrary.worldbank.org/doi/book/10.1596/978-0-8213-5397-4
- T. E. McKee and M. Greenstein, “Predicting bankruptcy using recursive partitioning and a realistically proportioned data set,” J. Forecasting, vol. 19, pp. 219–230, 2000
- Cavallo, M. and G. Majnoni (2002), “Do Banks Provision for Bad Loans in Good Times? Empirical Evidence and Policy Implications,” In R. Levich, G. Majnoni and C. Reinhart (Eds.), Ratings, Rating Agencies and the Global Financial System, Boston, Dordrecht and London: Kluwer Academic Publishers.
- Phil Brierley and NeuSolutions Ltd, (2005) The Tiberius Development Toolkit, http://www.philbrierley.com/ 2005
- Franz A. G http://www.neuroxl.com /white_ paper_ neural_networks.htm
- Olutayo V.A. and Eludire A.A. (2014), “Traffic Accident Analysis Using Decision Trees and Neural Networks,” I.J. Information Technology and Computer Science, 2014, 02, 22-28
- J. Ohlson, “Financial ratios and the probabilistic prediction of bankruptcy,” J. Accounting Res., vol. 18, pp. 109–131, 1980.
- I. Olmeda and E. Fernandez, “Hybrid classifiers for financial multi-criteria decision making: The case of bankruptcy prediction,” Computational Economics, vol. 10, pp. 317–335, 1997.
- Greenwald, M. B. and J. F. Sinkey Jr. (1988), “Bank Loan-Loss Provisions and the Income-Smoothing Hypothesis: An Empirical Analysis, 1976–1984,” Journal of Financial Services Research 1, 301–318.
- A. Silberschatz, H. F. Korth, S. Sudarsham Database Systems Concepts, 5th Edition, McGraw-Hill, Hightstown, NJ, 2005.
- Eludire A. A. Ayinde M. O and Adetoso J. A. (2010) The Conceptual Design of a Bank Loan Management System. Proceedings of 5th International Conference on Application of Information Communication Technologies to Teaching, Research and Administration (AICTTRA 2010), University of Jos, 138-144.
- Statistical Package for the Social Sciences http://www.ehow.com/about_5459472_spss-software.html
- http://www.ehow.com/how_6920248_do-analysis-spss-version-16_0.html
- Microsoft Corporation, A guide to system design in Visual Basic, MS Press, 2003.
- Microsoft Corporation, Microsoft Access 2003 Users Guide, MS Press, 2003
- Hong Kong Monetary Authority Loan Classification System http://www.hkma.gov.hk / gdbook / eng/ l / loan classificat_sys.shtml.
- http://www.fdic.gov/regulations / resources /director/college/ny/materials/2012-loans.pdf
