Knowledge acquisition and representation for expert systems in the field of financial analysis

Abstract Knowledge acquisition and representation has been characterised as the major bottleneck in the development of expert systems (Barr & Geigenbaum, 1982), especially in problem domains of high complexity. Financial analysis is one of the most complicated practical problems, where the expert systems technology is highly applicable, mainly because of its symbolic reasoning and its explanation capabilities. The aim of this paper is to present a complete methodology for knowledge acquisition and representation for expert systems development in the field of financial analysis. This methodology has been implemented in the development of the FINEVA multicriteria knowledge-based decision support system for the assessment of corporate performance and viability. The application of this methodology in the development of the FINEVA system is presented.

[1]  Louis F. Pau,et al.  Artificial Intelligence in Economics and Management , 1986 .

[2]  M. Shaw,et al.  Using an Expert System with Inductive Learning to Evaluate Business Loans , 1988 .

[3]  Stephan Heuer,et al.  INVEST: an expert system for financial investments , 1988, IEEE Expert.

[4]  J. Ross Quinlan,et al.  Learning Efficient Classification Procedures and Their Application to Chess End Games , 1983 .

[5]  Marinus J. Bouwman.  Human Diagnostic Reasoning by Computer: An Illustration from Financial Analysis , 1983 .

[6]  B. Tabachnick,et al.  Using Multivariate Statistics , 1983 .

[7]  Efraim Turban,et al.  Decision Support and Expert Systems: Management Support Systems , 1990 .

[8]  Venkat Srinivasan,et al.  A dedicated shell for designing expert credit support systems , 1992, Decis. Support Syst..

[9]  V. Srinivasan,et al.  CGX: An expert support system for credit granting , 1990 .

[10]  Constantin Zopounidis,et al.  An integrated DSS for financing firms by an industrial development bank in Greece , 1994, Decis. Support Syst..

[11]  P. Lévine,et al.  Knowledge representation by schemata in financial expert systems , 1989 .

[12]  G. Hartvigsen.  Limitations of knowledge-based systems for financial analysis in banking , 1992 .

[13]  Timothy Paul Cronan,et al.  Production System Development for Expert Systems Using a Recursive Partitioning Induction Approach: An Application to Mortgage, Commercial, and Consumer Lending , 1991 .

[14]  Thomas H. Rowley,et al.  Using anthropological interview strategies to enhance knowledge acquisition , 1995 .

[15]  Peter J. Elmer,et al.  An Expert System Approach to Financial Analysis: The Case of S&L Bankruptcy , 1988 .

[16]  J. Efrim Boritz,et al.  Effectiveness of neural network types for prediction of business failure , 1995 .

[17]  William E. McCarthy,et al.  FSA: Applying AI Techniques to the Familiarization Phase of Financial Decision Making , 1987, IEEE Expert.

[18]  Vijay K. Rohatgi,et al.  Advances in Fuzzy Set Theory and Applications , 1980 .

[19]  Alan Sangster,et al.  The bank of Scotland's COMPASS-The future of bank lending? , 1995 .

[20]  John R. Anderson,et al.  MACHINE LEARNING An Artificial Intelligence Approach , 2009 .

[21]  Suzanne Pinson,et al.  Credit risk assessment and meta-judgment , 1989 .

[22]  J. Courtis.  MODELLING A FINANCIAL RATIOS CATEGORIC FRAMEWORK , 1978 .

[23]  Leon Sterling,et al.  A prototype expert system for credit evaluation , 1986 .

[24]  Ramesh Sharda,et al.  Bankruptcy prediction using neural networks , 1994, Decis. Support Syst..

[25]  Constantin Zopounidis,et al.  Application of the Rough Set Approach to Evaluation of Bankruptcy Risk , 1995 .

[26]  Gunnar Hartvigsen,et al.  KABAL: a knowledge-based system for financial analysis in banking , 1990 .

[27]  Cheng F. Lee.  Financial analysis and planning : theory and application , 1985 .

[28]  Hans-Jürgen Zimmermann,et al.  Fuzzy Set Theory - and Its Applications , 1985 .

[29]  James V. Hansen,et al.  Inducing rules for expert system development: an example using default and bankruptcy data , 1988 .

[30]  Peter Duchessi,et al.  Lending Analysis Support System (LASS): An Application of a Knowledge-Based System to Support Commercial Loan Analysis , 1987, IEEE Transactions on Systems, Man, and Cybernetics.

[31]  Jon Carpenter,et al.  Using rule induction for knowledge acquisition: An expert systems approach to evaluating material errors and irregularities , 1995 .

[32]  Constantin Zopounidis,et al.  DEVELOPING A MULTICRITERIA KNOWLEDGE-BASED DECISION SUPPORT SYSTEM FOR THE ASSESSMENT OF CORPORATE PERFORMANCE AND VIABILITY: THE FINEVA SYSTEM , 1996 .

[33]  Jerzy W. Grzymala-Busse,et al.  Rough Sets , 1995, Commun. ACM.

[34]  Avron Barr,et al.  The Handbook of Artificial Intelligence , 1982 .

[35]  Michel R. Klein,et al.  Knowledge-Based Decision Support Systems With Applications in Business , 1995 .

[36]  D. O'Leary,et al.  Expert Systems in Finance , 1992 .

[37]  Lotfi A. Zadeh.  Management of uncertainty in expert systems , 1986 .

[38]  Ehsan Nikbakht,et al.  APPLICATION OF EXPERT SYSTEMS IN EVALUATION OF CREDIT CARD BORROWERS , 1989 .

[39]  J. Siskos.  Assessing a set of additive utility functions for multicriteria decision-making , 1982 .

[40]  Daniel E. O'Leary,et al.  AI in Accounting, Finance and Management , 1995 .