Financial early warning system for risk detection and prevention from financial crisis

Surveillance Technologies and Early Warning Systems: Data Mining Applications for Risk Detection

Volumn , Issue , 2010, Pages 76-108

  Ozgulbas, Nermin ^a   Koyuncugil, Ali Serhan ^b  

^a BASKENT UNIVERSITY   (Turkey)

^b Çankaya   (Turkey)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84856548144     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.4018/978-1-61692-865-0.ch005     Document Type: Chapter

References (99)

1. Abouzeedan, A., & Busler, M. (2004). Typology analysis of performance models of small and medium size enterprises (SMEs). Journal of International Entrepreneurship, 2(1-2), 155-177. doi:10.1023/B:JIEN.0000026911.03396.2d
2. Abumustafa, N. I. (2006). Development of an early warning model for currency crises in emerging economies: An empirical study among Middle Eastern countries. International Journal of Management, 23(3), 403.
3. ADBI Institute. (2010), Enterprise risk management during the global financial crisis: Sharing global experience. Presented at 2nd Annual Thought Leadership Conference, Bejing.
4. Altman, E. (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. The Journal of Finance, (September): 589-609. doi:10.2307/2978933
5. Altman, E. I., Haldeman, G., & Narayanan, P. (1977). Zeta Analysis: A new model to identify bancrupcy risk of corporations. Journal of Banking & Finance, (June): 29-54. doi:10.1016/0378-4266(77)90017-6
6. Arias, C. A., Martinez, A. C., & Gracia, J. (2003). Capital structure and sensitivity in SME definition: A panel data investigation. Retrieved December, 2009, from http://ssrn.com/abstract=549082.
7. Audretsch, D., van der Horst, R., Kwaak, T., & Thurik, R. (2009). First section of the annual report on EU small and medium-sized enterprises. Retrieved December, 2009, from http://ec.europa.eu/enterprise/policies/sme/files/craft/sme_perf_review/doc_08/spr08_anual_reporten.pdf
8. Barniv, R., & Hathorn, J. (1997). The merger or insolvency alternative in the insurance industry. The Journal of Risk and Insurance, 64(1), 89-113. doi:10.2307/253913
9. Beaver, W. (1966). Financial ratios as predictors of failure. Journal of Accounting Research, 4, 71-111. doi:10.2307/2490171
10. Beck, T., Kunt, A., & Peria, M. S. (2008). Bank financing for SMEs around the world, Policy Research Working Paper, 4785. Retrieved October, 2009 from, https://www.researchgate.net/publication/23970207_Bank_Financing_for_SMEs_around_the_World_Drivers_Obstacles_Business_Models_and_Lending_Practices
11. Berg, A., Borensztein, E., & Pattillo, C. (2004). Assessing early warning systems: How have they worked in practice? IMF Working Paper, March 2004. Retrieved October, 2009, from http://www.ksri.org/bbs/files/research02/wp0452.pdf
12. Berliet, J. (2008). Lessons from the financial crisis for directors and CEOs of insurance companies, risk management: The current financial crisis, lessons learned and future implications. Institute of ActuARies
13. Bhaird, C., & Lucey, B. (2006). Capital structure and the financing of SMEs: Empirical evidence from an Irish survey. Working Paper, Retrieved October, 2009, from http://www.cebr.dk/upload/ciaranmacanbhaird.pdf
14. Bhairdi, C., & Lucey, B. (2005). Determinants of the capital structure of SMEs: A seemingly unrelated regression approach. Small Business Economics. doi:10.1007/s11187-008-9162-6
15. Bitzenis, A., & Nito, E. (2005). Obstacles to entrepreneurship in a transition business environment: The case of Albania. Journal of Small Business and Enterprise Development, 12(4), 564-578. doi:10.1108/14626000510628234
16. Brockett, P. L., Golden, L. L., Jang, J., & Yang, C. (2006). A comparison of neural network, statistical methods and variable. The Journal of Risk and Insurance, 73(3), 397-419. doi:10.1111/j.15396975.2006.00181.x
17. Bukvic, V., & Bartlett, W. (2003). Financial barriers to SME growth in Slovenia. Economic and Business Review, 5(3), 161-181.
18. Canovas, G. H., & Solano, P. M. (2006). Banking relationships: Effect on debt terms for Spanish firms. Journal of Small Business Management, 44(3), 315-334. doi:10.1111/j.1540-627X.2006.00174.x
19. Chang, S., Chang, H., Lin, C., & Kao, S. (2003). The effect of organizational attributes on the adoption of data mining techniques in the financial service industry: An empirical study in Taiwan. International Journal of Management, 20(1), 497-503.
20. Commission Recommendation of 6 May 2003 Concerning the Definition of Micro, Small and Medium-sized Enterprises (2003/361/EC), L 124/36 2003. Official Journal of the European Union. Retrieved December, 2009, from http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2003:124:0036:0041:en:PDF
21. Danset, R. (1998). Comparison between the financial structures of SME versus large enterprises. Final Report for the DG II European Community.
22. Daskalakis, N., & Psillaki, M. (2005). The determinants of capital structure of the SMEs: Evidence from the Greek and the French firms. Paper presented at the XXIInd Symposium on Banking and Monetary Economics, Strasbourg.
23. Daskalakis, N., & Psillaki, M. (2008). Do countries or firm factors explain capital structure? Evidence from SMEs in France and Greece. Applied Financial Economics, 18(2), 87-97. doi:10.1080/09603100601018864
24. Davis, E. P., & Karim, D. (2008). Could early warning systems have helped to predict the subprime crisis? National Institute Economic Review, 206(1), 35-47. doi:10.1177/0027950108099841
25. Deakin, E. B. (1972). A discriminat analysis of predictors of business failure. Journal of Accounting Research, 10(1), 167-179. doi:10.2307/2490225
26. Derby, B. L. (2003). Data mining for improper payments. The Journal of Government Financial Management, 52(1), 10-13.
27. Edison, H. J. (2003). Do indicators of financial crises work? An evaluation of an early earning system. International Journal of Finance & Economics, 8(1), 11-53. doi:10.1002/ijfe.197
28. Eklund, T., Back, B., Vanharanta, H., & Visa, A. (2003). Using the self- organizing map as a visualization tool in financial benchmarking. Information Visualization, 2(3), 171-181. doi:10.1057/palgrave.ivs.9500048
29. El-Shazly, A. (2006). Early warning of currency crises: An econometric analysis for Egypt. The Middle East Business and Economic Review, 18(1), 34-48.
30. EU. Europen Commission. (2003). 2003 Observatory of European SMEs: SMEs in Europe. Technical Paper No.7.
31. European Association of Craft. Small and Medium-Sized Enterprises (UEAPME). (2009). European SME Finance Survey. Retrieved October, 2009, from http://www.ueapme.com/IMG/pdf/090728_SME-finance_survey.pdf
32. Fayyad, G., Piatetsky-Shapiro, P., & Symth, P. (1996). From data mining to knowledge discovery in databases. AI Magazine, 17(3), 37-54.
33. Frawley, W., Piatetsky-Shapiro, G., & Matheus, C. (1992). Knowledge discovery in databases: An overview. AI Magazine, (Fall): 213-228.
34. Hand, D., Mannila, H., & Smyth, P. (2001). Principles of data mining. Cambridge, MA: MIT Press.
35. Hodorogel, R. G. (2009). The economic crisis and its effects on SMEs. Theoretical and Applied Economics, 5(34), 79-89.
36. Inegbenebor, A. U. (2006). Financing small and medium industries in Nigeria-case study of the small and medium industries equity investment scheme: Emprical research finding. Journal of Financial Management and Analysis, 19(1), 71-80.
37. Jacobs, L. J., & Kuper, G. H. (2004). Indicators of financial crises do work! An early-warning system for six Asian countries. CCSO Working Paper 13. Department of Economics, University of Groningen, the Netherlands.
38. Jones, F. (1987). Current techniques in bankruptcy prediction. Journal of Accounting Literature, 6, 131-164.
39. Karim, D. (2006). Comparing early warning systems for banking crises. Unpublished doctoral dissertation, Brunel University, UK.
40. Katz, M. (2006). Multivariable Analysis: A Practical Guide for Clinicians. New York: ChurchillLivingstone. doi:10.1017/CBO9780511616761
41. Klapper, L., Allende, V. S., & Zaidi, R. (2006). A firm level analysis of small and medium size enterprise financing in Poland. World Bank Policy Research Working Paper No: 3983.
42. Kloptchenko, A., Eklund, T., Karlsson, J., Back, B., Vanhatanta, H., & Visa, A. (2004). Combining data and text mining techniques for analysing financial reports. Intelligent Systems in Accounting Finance and Management, 12(1), 29-41. doi:10.1002/isaf.239
43. Koyuncugil, A. S. (2006). Fuzzy Data Mining and its application to capital markets. Unpublished doctoral dissertation, Ankara University, Ankara.
44. Koyuncugil, A. S., & Ozgulbas, N. (2006a). Financial profiling of SMEs: An application by Data Mining. The European Applied Business Research (EABR). Conference, Clute Institute for Academic Research.
45. Koyuncugil, A. S., & Ozgulbas, N. (2006b). Is there a specific measure for financial performance of SMEs? The Business Review, Cambridge, 5(2), 314-319.
46. rd Congress of SMEs and Productivity. Istanbul: KOSGEB and Istanbul Kultur University.
47. th Congress of SMEs and Productivity, Istanbul.
48. Koyuncugil, A. S., & Ozgulbas, N. (2007b). Detecting financial early warning signs in Istanbul Stock Exchange by data mining. International Journal of Business Research, VII(3), Koyuncugil, A. S., & Ozgulbas, N. (2008a). Strengths and weaknesses of SMEs listed in ISE: A CHAID Decision Tree application. Journal of Dokuz Eylul University. Faculty of Economics and Administrative Sciences, 23(1), 1-22.
49. Koyuncugil, A. S., & Ozgulbas, N. (2008b). Early warning system for SMEs as a financial risk detector. H. Rahman (Ed), Data mining applications for empowering knowledge societies (pp. 221-240). Hershey, PA: Idea Group Inc. Global.
50. Koyuncugil, A. S., & Ozgulbas, N. (2009a). Measuring and hedging operational risk by data mining. Paper presented in the World Summit on Economic-Financial Crisis and International Business, Washington, DC.
51. Koyuncugil, A. S., & Ozgulbas, N. (2009b). An intelligent financial early warning System model based on data mining for SMEs. International Conference on Future Computer and Communication, Kuala Lumpur, Malaysia.
52. Kumar, N., Krovi, R., & Rajagopalan, B. (1997). Financial decision support with hybrid genetic and neural based modeling tools. European Journal of Operational Research, 103, 339-349. doi:10.1016/S0377-2217(97)00124-0
53. Kyong, J. O., Tae, Y. K., Chiho, K., & Suk, J. L. (2006). Using neural networks to tune the fluctuation of daily financial condition indicator for financial crisis forecasting. In Advances in Artificial Intelligence. doi: 10.1007/11941439_65 Volume 4304/2006
54. Laitinen, K., & Chong, H. G. (1998). Early warning system for crisis in SMEs: Preliminary evidence from Finland and the UK. Journal of Small Business and Enterprise Development, 6(1), 89-102. doi:10.1108/EUM0000000006665
55. Larsen, K., & Bjerkeland, K. M. (2005). Are unexpected loan losses for small enterprises than for large enterprises? Norges Bank Economic Bulletin, 76(3), 126-133.
56. Lee, K. C., Han, I., & Kwon, Y. (1996). Hybrid neural network models for bankruntcy predictions. Decision Support Systems, 18, 63-73. doi:10.1016/0167-9236(96)00018-8
57. Lee, S. J., & Siau, K. (2001). A review of data mining techniques. Industrial Management & Data Systems, 101(1), 41-46. doi:10.1108/02635570110365989
58. Lopez, A. S. (2007). Improving access to credit of SME's in Puerto Rico: Exploring variables to Forceast small business loan events. Retrieved October, 2009, from http://selene.uab.es/depeconomia-empresa/Jornadas/Papers/4-12-2007/Alizabeth_Sanchez.pdf
59. Maher, M., & Andersson, T. (2000). Corporate governance: Effects on firm performance and economic growth, convergence and diversity of corporate governance regimes and capital markets. London: Oxford University Press.
60. Meyer, P. A., & Pifer, H. W. (1970). Prediction of bank failures. The Journal of Finance, 25(4), 853-886. doi:10.2307/2325421
61. Mohnen, A., & Nasev, J. (2005). Growth of small and medium-sized firms in Germany. Retrieved October, 2009, from http://ssrn.com/abstract=852785
62. Monk, E., & Wagner, B. (2006). Concepts in Enterprise Resource Planning (2nd ed.). Boston: Thomson Course Technology.
63. Nazem, S., & Shin, B. (1999). Data mining: New arsenal for strategic decision making. Journal of Database Management, 10(1), 39-42.
64. Nguyen, D. K., & Ramachandran, N. (2006). Capital structure in small and medium sized enterprises: The case of Vietnem. ASEAN Economic Bulletin, 23(2), 192-208. doi:10.1355/AE23-2D
65. Nomenclature statistique des activités économiques dans la Communauté européenne (NACE). (n.d.). Retrived October, 2009, from http://epp.eurostat.ec.europa.eu/statistics_explained/index.php/SMEs.
66. OECD. (2005). SME and Entrepreneurship Outlook. Centre for Entrepreneurship, SMEs and Local Development OECD.
67. OECD. (2009a). Policy responses to the economic crisis: Investing in innovation for long-term growth. Retrieved December 2009, from http://www.oecd.org/dataoecd/59/45/42983414.pdf.
68. OECD. (2009b). The observatory of European SMEs, 2007 observatory survey. Retrieved from http://ec.europa.eu/enterprise/policies/sme/facts-figures-analysis/sme-observatory/index_en.htm#h2-2007-observatory-survey
69. OECD. (2009c). The impact of the global crisis on SME and entrepreneurship financing and policy Responses. Retrieved December 2009, from http://www.oecd.org/dataoecd/40/34/43183090.pdf
70. Ogiujiba, K. K., Ohuche, F. K., & Adenuga, A. O. (2004). Credit availability to small and medium scale enterprises in Nigeria: Importance of new capital base for banks. Retrieved October, 2009, from http://129.3.20.41/eps/mac/papers/0411/0411002.pdf
71. th National Finance Symposium, Izmir.
72. Ozgulbas, N., Koyuncugil, A. S., & Yilmaz, F. (2006). Identifying the effect of firm size on financial performance of SMEs. The Business Review, Cambridge, 5(2), 162-167.
73. Pantalone, C., & Platt, M. (1987). Predicting failures of savings and loan associations. AREUEA Journal, 15, 46-64.
74. Paranque, B. (1995). Equity and rate of return: Are small manufacturing firms handicapped by their own success? Paper presented at the meeting International Council for Small Business 40th World Conference, Sydney.
75. Requejo, M. (2002). SME vs. large enterprise leverage: Determinants and structural relations. Retrieved October, 2009, from http://ssrn.com/abstract=302400 or doi: 10.2139/ssrn.302400
76. Ross, S., Westerfield, R., & Jaffe, J. (2008). Corporate finance (8th ed.). New York: McGraw Hill Ryerson Limited.
77. Salas, V., & Saurina, J. (2002). Credit risk in two institutional regimes: Spanish commercial and savings banks. Journal of Financial Services Research, 22(3), 203-224. doi:10.1023/A:1019781109676
78. Sanchez, A., & Marin, G. S. (2005). Strategic orientation, management characteristics, and performance: A study of Spanish SMEs. Journal of Small Business Management, 43(3), 287-309.
79. Sarno, D. (2005). Liquidity constraint on the production of firms in Southern Italy. Small Business Economics, 25(2), 133-146. doi:10.1007/s11187-003-6452-x
80. Shirakawa, M. (2009). Coping with financial crisis - Japan's experiences and current global financial crisis. BIS Review, 23.
81. Sogorb-Mira, F. (2001). On capital structure in the small and medium enterprises: The Spanish case. working paper series, Instituto de Estudios Europeos - Universidad San Pablo CEU, Madrid. Retrieved October, 2009, from http://ssrn.com/abstract=277090 or DOI: 10.2139/ssrn.277090.
82. Sogorb-Mira, F. (2005). How SME uniqueness affects capital structure: Evidence from A 1994-1998 Spanish data panel. Small Business Economics, 25(5), 447-457. doi:10.1007/s11187-004-6486-8
83. Sormani, A. (2005). Debt causes problems for SMEs. European Venture Capital & Capital Equity Journal, 1, 1.
84. SPSS. (2001). AnswerTree 3.0 User's Guide. Chicago: SPSS Inc.
85. Taffler, R. J., & Tisshaw, H. (1977). Going, going, gone-four factors which factors which predict. Accountancy, (March), 50-54.
86. Tagoe, N., Nyarko, E., & Amarh, E. A. (2005). Financial challenges facing urban SMEs under financial sector liberalization in Ghana. Journal of Small Business Management, 43(3), 331-343.
87. Tam, K. Y., & Kiang, M. Y. (1992). Managerial applications of neural networks: The case of bank failure predictions. Decision Sciences, 38, 926-948.
88. Teruel, P. J. G., & Solano, P. M. (2007). Effects of working capital management on SME profitability. International Journal of Managerial Finance, 3(2), 164-177. doi:10.1108/17439130710738718
89. The Hankyoreh. (2009). The financial crisis and South Korea one year after. Retrieved October, 2009, from http://english.hani.co.kr/arti/eng-lish_edition/e_business/376783.html
90. Thearling, K. (2004). Data mining and analytic technologies. Retrieved October, 2009, from hhtp://www.thearling.com/
91. Tsuruta. D., & Xu, P. (2005). Capital structure and survival of financial distressed SMEs in Japan. Retrieved April, 2009, From (2005). http://www.rieti.go.jp/users/uesugi-iichiro/cf-workshop/pdf/tsuruta-xu.pdf
92. Turkish Statistic Institute (TSI). (2002). General industrial enterprise census, April 2006. Retrieved April, 2009, from hhtp://www.die.gov.tr/TURK-ISH/SONIST/GSIS/gsisII141003.pdf
93. Wahyu, I., & Swadaya, B. (2009). Impact the financial crisis for SMEs in Indonesia. Paper presented at the Regional Conference on the Impact of Financial Crisis on Vulnerable Sectors: Civil Society Voices and ASEAN, Jakarta.
94. Warner, J. (1977). Bankruptcy costs: some evidence. The Journal of Finance, 32, 337-347. doi:10.2307/2326766
95. World Bank. (WB). (2009a). The financial crisis: Implications for developing countries. Retrieved December, 2009, from http://econ.worldbank.org/WBSITE/EXTERNAL/EXTDEC/0,contentMDK:21974412~isCURL:Y~pagePK:64165401~piPK:64165026~theSitePK:469372,00.html
96. World Bank. (WB). (2009b). Survey: Eastern European businesses report long-term impact of financial crisis. Retrieved December, 2009, from http://www.enterprisesurveys.org/Finan-cialCrisis/
97. Yang, B., Ling, X. L., Hai, J., & Jing, X. (2001). An early warning system for loan risk assessment using artificial neural Networks. KnowledgeBased Systems, 14(5-6), 303-306. doi:10.1016/S0950-7051(01)00110-1
98. Zavgren, C. (1985). Assessing the vulnerability to failure of American industrial firms: A logistics analysis. Journal of Accounting Research, 22, 59-82.
99. Zmijewski, M. E. (1984). Methodological issues related to the estimation of financial distress prediction models. Journal of Accounting Research, (Supplement), 59-82. doi:10.2307/2490859