A New Perspective Over the Risk Assessment in Credit Scoring Analysis Using the Adaptive Reference System

被引:0
|
作者
Vac, Gelu I. [1 ]
Gaban, Lucian V. [2 ]
机构
[1] Univ Babes Bolyai, Cluj Napoca 400084, Romania
[2] 1 Decembrie 1918 Univ Alba Iulia, Alba Iulia 510009, Romania
来源
关键词
Adaptive Reference System; Risk assessment; Risk Culture; Credit risk;
D O I
10.1007/978-3-319-39426-8_11
中图分类号
F [经济];
学科分类号
02 ;
摘要
The main goal of this paper is the development of a platform which can insure the effectiveness and the simplification of the loan granting process performed by financial credit institutions and banks oriented to small and medium enterprises. The factors considered include employee's education, experience, philosophy, self-beliefs and self-understanding of the bank's target and values and his self-commitment to the bank's objectives. This paper proposes a platform which implements a statistical model, containing financial indicators. The model is flexible, being able to include, besides financial indicators, some emotional ones, considered as model corrections pertaining to the decision maker. The latter indicators are important in borderline decisions. Our platform has been validated on samples containing financial data for Romanian small and medium sized enterprises.
引用
收藏
页码:130 / 143
页数:14
相关论文
共 50 条
  • [1] A new corporate credit scoring system using semi-supervised discriminant analysis
    Huang, Shian-Chang
    [J]. AFRICAN JOURNAL OF BUSINESS MANAGEMENT, 2011, 5 (22): : 9355 - 9362
  • [2] Towards a Reference Architecture for Trusted Data Marketplaces ∼The Credit Scoring Perspective∼
    Roman, Dumitru
    Stefano, Gatti
    [J]. PROCEEDINGS 2016 2ND INTERNATIONAL CONFERENCE ON OPEN AND BIG DATA - OBD 2016, 2016, : 95 - 101
  • [3] PREDICTING CREDIT RISK WITH A NUMERICAL SCORING SYSTEM
    MYERS, JH
    [J]. JOURNAL OF APPLIED PSYCHOLOGY, 1963, 47 (05) : 348 - 352
  • [4] Application of multiple discriminant analysis (MDA) as a credit scoring and risk assessment model
    Chijoriga, Marcellina Mvula
    [J]. INTERNATIONAL JOURNAL OF EMERGING MARKETS, 2011, 6 (02) : 132 - 147
  • [5] Variable Selection for Credit Risk Scoring on Loan Performance Using Regression Analysis
    Calibo, Dawn Iris
    Ballera, Melvin A.
    [J]. 2019 IEEE 4TH INTERNATIONAL CONFERENCE ON COMPUTER AND COMMUNICATION SYSTEMS (ICCCS 2019), 2019, : 746 - 750
  • [6] Credit Risk Scoring Using a Data Fusion Approach
    El-Qadi, Ayoub
    Trocan, Maria
    Conde-Cespedes, Patricia
    Frossard, Thomas
    Diaz-Rodriguez, Natalia
    [J]. COMPUTATIONAL COLLECTIVE INTELLIGENCE, ICCCI 2023, 2023, 14162 : 769 - 781
  • [7] Fuzzy Credit Risk Scoring Rules using FRvarPSO
    Jimbo Santana, Patricia
    Lanzarini, Laura
    Bariviera, Aurelio F.
    [J]. INTERNATIONAL JOURNAL OF UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED SYSTEMS, 2018, 26 : 39 - 57
  • [8] Credit scoring analysis using kernel discriminant
    Widiharih, T.
    Mukid, M. A.
    Mustafid
    [J]. 7TH INTERNATIONAL SEMINAR ON NEW PARADIGM AND INNOVATION ON NATURAL SCIENCE AND ITS APPLICATION, 2018, 1025
  • [9] USING THE LISP-MINER SYSTEM FOR CREDIT RISK ASSESSMENT
    Berka, P.
    [J]. NEURAL NETWORK WORLD, 2016, 26 (05) : 497 - 518
  • [10] Design of adaptive Elman networks for credit risk assessment
    Corazza, Marco
    De March, Davide
    di Tollo, Giacomo
    [J]. QUANTITATIVE FINANCE, 2021, 21 (02) : 323 - 340