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Credit risk assessment and meta-judgment

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Abstract

Decision-making problems in credit risk assessment and authorization are often too complex to be processed by conventional methods. They involve judgmental procedures which are by nature non-deterministic. Artificial intelligence methods can be used to approach the problem from a different angle. This paper shows the feasibility of a multi-expert approach driven by a meta-model in assessing business risk. More precisely it describes the meta-expert as part of a knowledge-based system being developed to assist bank loan officers in assessing the activities of firms applying for a loan. The use of a meta-model to represent the expert's strategic reasoning has the advantage of offering adaptable systems capable of building dynamically the resolution strategy most suited to the problem to be solved.

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References

  • Alvey Report: 1982, A Program for Advanced Information Technology, HMSO, London.

    Google Scholar 

  • Aucoin, M. and Micha, B.: 1985, ‘Système Expert pour l'Aide au Diagnostic d'Enterprise’, Colloque SIAD 85, Paris, pp. 72–96.

  • Benchimol, G., Levine, P., and Pomerol, J. C.: 1987, Developing Expert Systems for Business, North Oxford Academic.

  • Ben-David, A. and Sterling, L.: 1986, ‘A Prototype Expert System for Credit Evaluation’, in L. F. Pau (ed.), Artificial Intelligence in Economics and Management, Elsevier Science Publisher, North-Holland, pp. 121–128.

    Google Scholar 

  • Blanning, R. W.: 1984, ‘Management Applications of Expert Systems’, Information and Management, pp. 311–316.

  • Bonnet, A., Haton, J. P., and Truong-Ngoc, J. M.: 1986, Systèmes Experts, Vers la Maîtrise Technique, Inter Editions.

  • Bourgine, P. and Laurière, J. L.: 1985, ‘Mise sous Forme Déclarative du Logiciel ALICE à l'Aide du Moteur d'Inférence SNARK’, Colloque Intelligence Artificielle, Publication 58, Laboratoire C. F. Picart, Université Paris VI.

  • Brehmer, B., Jungermann, H., Lourens, P., and Sevon, G., 1986, New Directions in Research on Decision-Making, North Holland, Amsterdam.

    Google Scholar 

  • Buchanan, B. G. and Shortliffe, E. H.: 1984, Rule-Based Expert Systems: The MYCIN Experiments of the Stanford Heuristic Programming Project, Addison-Wesley, Reading, MA.

    Google Scholar 

  • Chandrasekaran, B.: 1987, ‘Towards a Functional Architecture for Intelligence Based on Generic Information Processing Tasks’, Proc. IJCAI-87, Milan, p. 1183.

  • Chevalier, A. and Hirsh, R.: 1982, Le Risk Management, Enterprise Moderne d'Edition.

  • Davis, R.: 1980, ‘Meta-Rules: Reasoning about Control’, Artificial Intelligence 15, pp. 179–222.

    Google Scholar 

  • Davis, R. and King, J.: 1977, ‘An Overview of Production Systems’, in E. W. Elcock and D. Michie, Machine Intelligence, 8, John Wiley, New York.

    Google Scholar 

  • Einhorn, H. J. and Hogarth, R. M.: 1981, ‘Behavioral Decision Theory: Processes of Judgment and Choice’, Annual Review of Psychology, 32.

  • Farreny, H.: 1985, Les Systèmes Experts: Principes et Exemples, Cepadues Editions, Paris.

    Google Scholar 

  • Hewit, C. E.: 1977, ‘Control as Messages Passing’, in Winston P. H. and Brown R. H. (eds.), Artificial Intelligence: An MIT Perspective, vols. 1 and 2, MIT Press, pp. 435–484.

  • Hofstadter, D. R.: 1979, Gödel, Escher and Bach: and Eternal Golden Braid, Basic Books Inc. Publisher, N.Y.

    Google Scholar 

  • Holsapple, C. W. and Whinston, A. B.: 1985, ‘Management Support through Artificial Intelligence’, Human Systems Management, 5, pp. 163–171.

    Google Scholar 

  • Hwang, C. L. and Yoon, K.: 1981, Multiple Attribute Decision-Making, Methods and Applications, Springer-Verlag, Berlin.

    Google Scholar 

  • Johnson, D. M.: 1972, Systematic Introduction to the Psychology of Thinking, Harper and Row, N.Y.

    Google Scholar 

  • Johnson, T.: 1984, The Commercial Application of Expert System Technology, Ovum, London.

    Google Scholar 

  • Kerschberg, L. and Dickinson, J.: 1985, ‘FINEX: An Expert Support System for Financial Analysis’, 5th Intern. Workshop on Expert Systems and Their Applications, Avignon, pp. 919–942.

  • Lampert, A.: 1985, ‘Expert Systems Get Down to Business’, Computer Decision 17, 136–140, 142, 144.

    Google Scholar 

  • Laurière, J. L.: 1986a, Intelligence Artificielle, Résolution de Problèmes par l'Homme et la Machine, Editions Eyrolles, Paris.

    Google Scholar 

  • Laurière, J. L.: 1986b, ‘SNARK, a Language to Represent Declarative Knowledge and an Inference Engine Which Uses Heuristics’, Proc. of the IFIP, Dublin, pp. 811–816.

  • Lee, R. M.: 1984, ‘Expert vs Management Support System: Semantics Issues’, Cybernetics and Systems, nℴ 139, vol. 39, pp. 139–157.

    Google Scholar 

  • Lenat, D., Davis, R., Doyle, J., Genesereth, M., Goldstein, I., and Schrobe, H.: 1983, ‘Reasoning about Reasoning’, in Hayes-Roth, F., Waterman, D. A., and Lenat, D. B. (eds.), Building Expert Systems, Addison-Wesley, Reading, MA, pp. 219–239.

    Google Scholar 

  • Luconi, F., Malone, T., and Morton, M. S.: 1986, ‘Expert Systems: The Next Challenge for Managers’, Sloan Management Review, Summer.

  • Methlie, L. B. and Sprague, R. H. (eds.): 1985, Knowledge Representation for Decision Support Systems, North-Holland, Amsterdam.

    Google Scholar 

  • Michaelsen, R. and Michie, D.: 1983, ‘Expert Systems in Business’, Datamation, n ℴ 11.

  • Minsky, M.: 1975, ‘A Framework for Representing Knowledge’, in P. Winston (Ed.), The Psychology of Computer Vision, McGraw-Hill, N.Y., pp. 211–277.

    Google Scholar 

  • Nadler, P.: 1983, ‘Lending by Computer?’, Bankers Monthly Magazine, May 15.

  • National Research Council Governing Board Committee on the Assessment of Risk: 1981, The Handling of Risk Assessment in NRC Reports, Washington D.C., US, National Research Council.

    Google Scholar 

  • Newell, A. and Simon, H. A.: 1972, Human Problem Solving, Prentice-Hall, Englewood Cliffs, N.J.

    Google Scholar 

  • Nisbett, R. E. and Ross, L.: 1980, Human Inference Strategies and Shortcomings in Social Judgment, Prentice-Hall, Englewood Cliffs, N.J.

    Google Scholar 

  • Pau, L. F. (ed.): 1986, Artificial Intelligence in Economics and Management, NorthHolland, Amsterdam.

    Google Scholar 

  • Pinson, S.: 1981, ‘Représentation des Connaissances dans les Systèmes Experts’, RAIRO Informatique Computer Sciences 15(4), 343–367.

    Google Scholar 

  • Pinson, S.: 1987, ‘A Multiattribute Approach to Knowledge Representation for Loan Granting’, Proc. IJCAI-87, Milan, pp. 588–591.

  • Pinson, S.: 1988, ‘Système multi-expert et processus d'évaluation du risque entreprise: Le système CREDEX’, 8 th Intern. Workshop on Expert System and Their Applications, Avignon, pp. 517–538.

  • Pitrat, J.: 1986, ‘Using Knowledge to Use Knowledge’, International Conference on Information Processing and Management of Uncertainty in Knowledge-Based System, Paris.

  • Rechenman, F. and Doize, M. S.: 1987, ‘SAFIR: SHIRKA: Un Système à Base de Connaissance Centrée Objet pour l'Analyse Financière’, 7 th Intern. Workshop on Expert System and Their Applications, Avignon, pp. 949–967.

  • Roos, J. L. (ed.): 1986, Economics and Artificial Intelligence, Pergamon Press, Oxford.

    Google Scholar 

  • Wanet, G.: 1987, ‘Artificial Intelligence in Banking - Why and How’? 1 th Intern. Conf. on Banking Applications and Artificial Intelligence, Brussels.

  • Waterman, D. A. and Hayes-Roth, F. (eds.): 1978, Pattern Directed Inference Systems, Academic Press.

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Authors and Affiliations

  1. Département Informatique, Université Paris II, 92 Rue d'Assas, 75270, Paris cedex, France

    Suzanne Pinson

  2. LAFORIA, CNRS, Université Paris VI, 4, Place Jussieu, 75230, Paris cedex, France

    Suzanne Pinson

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  1. Suzanne Pinson
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Pinson, S. Credit risk assessment and meta-judgment. Theor Decis 27, 117–133 (1989). https://doi.org/10.1007/BF00133991

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