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
  • [31] Credit Scoring using Support Vector Machine: A Comparative Analysis
    Harikrishna, S.
    Farquad, M. A. H.
    Shabana
    [J]. MATERIALS SCIENCE AND INFORMATION TECHNOLOGY, PTS 1-8, 2012, 433-440 : 6527 - +
  • [32] SWAP CREDIT RISK - A MULTI-PERSPECTIVE ANALYSIS
    HENDERSON, SK
    [J]. BUSINESS LAWYER, 1989, 44 (02): : 365 - 400
  • [33] Assessment of a new automated sleep scoring system
    Pittman, SD
    MacDonald, MM
    Todros, K
    Ayas, NT
    Levy, B
    Geva, AB
    White, DP
    [J]. SLEEP, 2003, 26 : A395 - A396
  • [34] Credit risk assessment using a multicriteria hierarchical discrimination approach: A comparative analysis
    Doumpos, M
    Kosmidou, K
    Baourakis, G
    Zopounidis, C
    [J]. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2002, 138 (02) : 392 - 412
  • [35] Credit Scoring using Artificial Immune System Algorithms: A Comparative Study
    Bhaduri, Antariksha
    [J]. 2009 WORLD CONGRESS ON NATURE & BIOLOGICALLY INSPIRED COMPUTING (NABIC 2009), 2009, : 1539 - 1542
  • [36] Parameter-Tuned Deep Learning Model for Credit Risk Assessment and Scoring Applications
    Veeramanikandan, Varadharajan
    Jeyakarthic, Mohan
    [J]. Recent Advances in Computer Science and Communications, 2021, 14 (09) : 2958 - 2968
  • [37] Validation of the pediatric surgical risk assessment scoring system
    Wooda, Guilherme
    Barayan, Ghassan
    Sanchez, Daniela C. J.
    Inoue, Gustavo N. C.
    Buchalla, Carlos A. O.
    Rossini, Guilherme A.
    Trevisani, Lorenzo F. M.
    do Prado, Rogerio Ruscitto
    Passerotti, Carlo C.
    Nguyen, Hiep T.
    [J]. JOURNAL OF PEDIATRIC SURGERY, 2013, 48 (10) : 2017 - 2021
  • [38] A New Dynamic Credit Scoring Model Based on the Objective Cluster Analysis
    Gao Wei
    Cao Yun-Zhong
    Cheng Ming-Shu
    [J]. PRACTICAL APPLICATIONS OF INTELLIGENT SYSTEMS, ISKE 2013, 2014, 279 : 579 - +
  • [39] Using adaptive learning in credit scoring to estimate take-up probability distribution
    Seow, Hsin-Vonn
    Thomas, Lyn C.
    [J]. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2006, 173 (03) : 880 - 892
  • [40] Network-aware credit scoring system for telecom subscribers using machine learning and network analysis
    Gao, Hongming
    Liu, Hongwei
    Ma, Haiying
    Ye, Cunjun
    Zhan, Mingjun
    [J]. ASIA PACIFIC JOURNAL OF MARKETING AND LOGISTICS, 2022, 34 (05) : 1010 - 1030