International Journal of Financial Management

Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Z Score Reveals Credit Capacity: a Case Study of SBI


Affiliations
1 assistant Professor, DOMS, MANIT
2 Scientist-EI, AMPRI, Bhopal
3 Ex-Director, Crescent Institute of technology
     

   Subscribe/Renew Journal


The prediction of corporate fi nancial failure, crucial for the prevention and mitigation of economic downturns in a national economy, requires the categorization of healthy and unhealthy companies. This study examines the case of SBI and applies artifi cial neural network architectures-the self-organizing map -to assess the corporate fi nancial health of the fi rm. The research work fi rst estimates the internal parameters of the Z Score for a fi rm, these parameters from 2001-2008 to the train the BPNN and uses the estimates of the year 2009 and 2010 values for the validation process. Finally it dwells to draw predictions for the period 2011-2015 and emphasizes the growing role of BPNN application based Z Score computation of fi nancial Bankruptcy.

Keywords

BPNN, neural network, credit lending, Z sore
Subscription Login to verify subscription
User
Notifications
Font Size

  • Ahn, B. S., Cho, S. S., & Kim, C.Y. (2000) “The integrated methodology of rough set theory and artifi cial neural network for business failure prediction”, Expert Systems with Applications, 18, 65-74.

  • Ahn, E. I., (2000) “Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy”. Journal of Finance, pp. 589-609.

  • Aldrich, J.H. and Nelson, F.D. (2007) “Linear Probability, Logit and Probit Models “,Sage Beverly Hills, Calif.

  • Altman, E.I. (2003) “Financial ratios, discriminant analysis, and prediction of corporate bankruptcy”, Journal of Finance, 23(4), 589-610.

  • Argenti, M. (2003) “Financial ratios as predictors of failure, Empirical Research in Accounting: Selected Studies”, University of Chicago, Chicago, Ill., 71-111.

  • Beaver, William H., (1968). “Market Prices, Financial Ratios, and the Prediction of Failure”, Journal of Accounting Research, Autumn, pp.179-192.

  • Bilanas, A.F. and Harris, F. (2004) “A methodology predicting failure in the construction Industry”, Journal of Construction Management and Economics, 13(3), 189-196

  • Botheras, C.F (2000) “The integrated methodology of rough set theory and artifi cial neural network for business failure prediction”, Expert Systems with Applications, 18, 65-74.

  • Bruton, H., Wan, K. and Ahlstrom, A., (2003) “The effects of acquisitions on the market value of the banking sector: An empirical analysis from Greece”, European Journal of Scientifi c Research (EJSR), Vol. 24, Issue 3, 2008.

  • Bryant, S. M. (1997). “A case-based reasoning approach to bankruptcy prediction Modeling“,Intelligent System Accounting, Financial and Management, 6, 195-214.

  • Burbank, C. (2005), “Boiled Frog Syndrome”, Management Today”, No.March, pp.121-4

  • Carrol, P. and Nelson, R. T. (2008), “How to Recognize and Avoid Organizations Decline,” Sloan Management Review, No.Spring, pp.41-6.

  • Charitou, J.K.W, Tam, C.M and Cheung, R. K. C (2000) “Construction fi rms at the crossroads in Hong Kong, Engineering”, Construction and Architectural Management, 12(2), 111-124.

  • Charitou, K., (2002) “How stock prices react to managerial decisions and other profi t signalling events, in the Greek mobile telecom market? “ ,3rd International Conference on Applied Financial Economics, Samos island 2002

  • Chowdhory, B., Patterson, J. (2005), “Silver Wheels Ltd”, in Richardson B., J Patterson, A Gregory, S. Leeson (Eds), Case Studies in Business Planning, 2nd, Pitman, London,Des Raj, (1972) The Design of Sample Surveys, McGraw Hill, 1972

  • Dimitras, D., Koksal, A. and Kale, S. (2006) “Business failures in the construction industry, Engineering”, Construction and Architectural Management, 7(2), 120-132.

  • Eidleman, E.B. (2007) “A discriminant analysis of predictors of business failure,” Journal of Accounting Research, Spring, Institute of Professional Accounting, Chicago, Ill., 167-179.

  • El-Zayaty, W., (2003), “Financial Ratios as Predictors of Failure, Empirical Research in Accounting: Selected Studies, Supplement”, Journal of Accounting Research 5, 71-127.

  • Keige, P. (1991)” Business Failure Prediction Using Discriminate Analysis”,Unpublished thesis, University of Nairobi.

  • Kip, A.F. (2002)” A methodology for predicting company failure in the construction industry”, PhD thesis, Loughborough University of Technology, Loughborough.

  • Kiragu, M. (1993)” The Prediction of Corporate Failure Using Price Adjusted Accounting Data”,Unpublished thesis, University of Nairobi

  • Kogi, S. (2003).” An Analysis of The Discriminant Corporate Failure Prediction Model Based on Stability of Financial Ratios”, Unpublished thesis, University of Nairobi

  • Kow, G.J., B.R Baliga., R.E Kidwell (2004), “Curing Sick Businesses: Changing CEOs in Turnaround Efforts”, The Executive, Academy of Management, Vol. VI No.3

  • McCall, A.,A Guardia., M Newland, C Hargreaves, J Thynne (2006), The Daily Telegraph, No.6 November, pp.1

  • Milkette, R.O. (2001) “An empirical test of fi nancial ratio analysis for small business failure prediction”, Journal of Financial Quantitative Analysis, Mar., University of Washington, Seattle, 1477-1493.

  • Millihni, G. L.V., (2003) “Predicting the Possibility of Failure in a Canadian Firm”. Unpublished M.B.A. Research Project, Simon Fraser University

  • Moyer, G, M Tuncan , M T Birgonul and I Dikmen (2006) “E-bidding proposal preparation system for construction projects, Building and Environment”, 41(10), 1406-

  • Nelson, P.M., D. C Mayes, P McKiernan. (2001), “Sharpbenders: The Secrets of Unleashing Corporate Potential”, Blackwell, Oxford

  • Nwanko, S, B Richardson, R Boyles (2007), The Rise and Fall of Air Europe, Sheffi eld Business School, Sheffi eld Hallam University,

  • Nwankwo, J.P, J. L Heskett (2003), Corporate Culture and Performance, The Free Press, New York, NY

  • O’Leary, E. G, (2001)”Business Failure Prediction and the Effi cient Market Hypothesis” Unpublished M.B.A. Research Project, Simon Fraser University, November

  • Ohlson, J.A. (1980). “Financial ratios and the probabilistic prediction of bankruptcy.” Journal of Accounting Research, Volume 18, Number 1, 109-31.

  • Patrick, S. and Ooghe, H. (2004) 35 years of studies on business failure: an overview of the classic statistical methodologies and their related problems, The British Accounting Review, 38(1), 63-93.

  • Pretorius, W.H.,A Greve, B.L.T Hedberg (2008), “Responding to Crisis”, in Mintzberg, H., Quinn, J.B. (Eds),The Strategy Process, 2nd, Prentice-Hall, Englewood-Cliffs, NJ, pp.785-93.

  • Richardson, M. (2004), “The Real Troubleshooters”, Intercity, British Rail, November, pp.278

  • Robbins, A., and Pearce L., (2005). “Corporate Bankruptcy Prediction Models Applied to emerging Economies: Evidence from Argentina in the Years 1991-1998.” International Journal of Commerce and Management, Volume 17, Number 4, 295-311.

  • Robinson, R.A. and M. G. Maguire (2001) “Top common causes of construction contractor failures”, Journal of Construction Accounting and Taxation, Jan/Feb 2003.

  • Sands, E. G. L. V Gordon, Springate and V Turgut (2001) “Predicting Business Failures”. CGA Magazine: pp. 24-27.

  • Sipika, C. and Smith, D. (2002), From Disaster to Crisis – the Failed Turnaround of Pan-American Airlines, Liverpool Business School, Liverpool, UK

  • Smith, A.and Graves K. (2005) “Empirical investigation of the business effects of announcements to share prices”, The Journal of Money, Investment and Banking, issue 2,

  • Smith, T. I. and Mitroff, I. (2005), “Crisis Prone versus Crisis Avoiding Organizations: Is Your Company’s Culture Its Own Worst Enemy in Creating Crises?”, Industrial Crisis Quarterly, Elsevier, Amsterdam, Vol. 2 pp.53-63.

  • Springate, and Gordon L.V., (1978).“Predicting the Possibility of Failure in a Canadian Firm”. Unpublished M.B.A. Research Project, Simon Fraser University.

  • Stead, K.,and Smallman A. (2000) “The Impact of Publicity and Press Announcements on Share Prices: An Empirical Study”, The Icfaian Journal of Management Research, vol. VII No 3, March 2008, pg 35-55.

  • Taffl er, C., (2001),” Alternative Financial Ratios as Predictors of Failure”, Accounting Review XLIII, 113-122.

  • Thynne K. (2006), “Test of the Generalizability of Altman’s Bankruptcy. Prediction Model,” Journal of Business Research, 53-61, 10, 2006


Abstract Views: 335

PDF Views: 0




  • Z Score Reveals Credit Capacity: a Case Study of SBI

Abstract Views: 335  |  PDF Views: 0

Authors

Roli Pradhan
assistant Professor, DOMS, MANIT
K K Pathak
Scientist-EI, AMPRI, Bhopal
V P Singh
Ex-Director, Crescent Institute of technology

Abstract


The prediction of corporate fi nancial failure, crucial for the prevention and mitigation of economic downturns in a national economy, requires the categorization of healthy and unhealthy companies. This study examines the case of SBI and applies artifi cial neural network architectures-the self-organizing map -to assess the corporate fi nancial health of the fi rm. The research work fi rst estimates the internal parameters of the Z Score for a fi rm, these parameters from 2001-2008 to the train the BPNN and uses the estimates of the year 2009 and 2010 values for the validation process. Finally it dwells to draw predictions for the period 2011-2015 and emphasizes the growing role of BPNN application based Z Score computation of fi nancial Bankruptcy.

Keywords


BPNN, neural network, credit lending, Z sore

References