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A group decision model for credit granting in the financial market

Author

Listed:
  • Paulo Cesar Schotten

    (Universidade Federal de Pernambuco)

  • Danielle Costa Morais

    (Universidade Federal de Pernambuco)

Abstract

Group decision models that contemplate the particularities of the decision-making process help organizations pursue their strategic objectives. In the financial market, the primary interest of organizations consists in ensuring financial returns, which guarantee stability for the organization. This study identifies major problems in the current process of credit granting in the financial market and argues the need for automatizing the organizational decision process while respecting the autonomy of decision-makers. To this end, this study proposes a group decision model based on the Strategic Choice Approach (SCA) for granting credit in a financial market organization. The results show that the adoption of the proposed model offers considerable gains in terms of organizational goals, transparency of the decision-making process, security for decision-makers, and reduction of organizational conflicts.

Suggested Citation

  • Paulo Cesar Schotten & Danielle Costa Morais, 2019. "A group decision model for credit granting in the financial market," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 5(1), pages 1-19, December.
    • Handle: RePEc:spr:fininn:v:5:y:2019:i:1:d:10.1186_s40854-019-0126-4
    DOI: 10.1186/s40854-019-0126-4
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    Cited by:

    1. Chao, Xiangrui & Kou, Gang & Peng, Yi & Viedma, Enrique Herrera, 2021. "Large-scale group decision-making with non-cooperative behaviors and heterogeneous preferences: An application in financial inclusion," European Journal of Operational Research, Elsevier, vol. 288(1), pages 271-293.
    2. Zhiying Zhang & Huchang Liao & Jiaying Chang & Abdullah Al-barakati, 2019. "Green-Building-Material Supplier Selection with a Rough-Set-Enhanced Quality Function Deployment," Sustainability, MDPI, vol. 11(24), pages 1-21, December.
    3. Yufei Xia & Xinyi Guo & Yinguo Li & Lingyun He & Xueyuan Chen, 2022. "Deep learning meets decision trees: An application of a heterogeneous deep forest approach in credit scoring for online consumer lending," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(8), pages 1669-1690, December.
    4. Kuang-Hua Hu & Fu-Hsiang Chen & Ming-Fu Hsu & Gwo-Hshiung Tzeng, 2023. "Governance of artificial intelligence applications in a business audit via a fusion fuzzy multiple rule-based decision-making model," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-31, December.
    5. Paulo Cesar Schotten & Leydiana Sousa Pereira & Danielle Costa Morais, 2022. "Credit granting sorting model for financial organizations," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-24, December.
    6. Li, Yanhong & Kou, Gang & Li, Guangxu & Peng, Yi, 2022. "Consensus reaching process in large-scale group decision making based on bounded confidence and social network," European Journal of Operational Research, Elsevier, vol. 303(2), pages 790-802.
    7. Alexandre de A. Gomes Júnior & Vanessa B. Schramm, 2022. "Problem Structuring Methods: A Review of Advances Over the Last Decade," Systemic Practice and Action Research, Springer, vol. 35(1), pages 55-88, February.
    8. Kuang-Hua Hu & Ming-Fu Hsu & Fu-Hsiang Chen & Mu-Ziyun Liu, 2021. "Identifying the key factors of subsidiary supervision and management using an innovative hybrid architecture in a big data environment," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-27, December.

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