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Neural Computing and Applications
Erschienen in: Neural Computing and Applications 9/2021

31.01.2021 | S.I. : SPIoT 2020

Farmers credit optimization decision model and applications based on common risk guarantee fund

verfasst von: Sulin Pang, Min Wei, Zhiming Wen

Erschienen in: Neural Computing and Applications | Ausgabe 9/2021

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Abstract

The paper proposes the farmers credit optimization decision model and applications based on common risk guarantee fund. By considering two conditions of with default risk and without default risk, the individual rationality of bank and farmer is designed, respectively, and the mathematical formulas for calculating the risk loss ratio of bank loans under the guarantee fund are established and discussed innovatively, respectively. A nonlinear optimal model based on risk compensation fund is established in the paper. By mathematical proof, the optimal bank credit decision mechanism is studied. By the analysis of numeric experiments of two cases of with default risk and without default risk, the expected income and invest income are varied by the changing of farmer project success probability and default probability, and the relationship of loan interest, farmer expected income and invest income is studied. The research has scientific guiding significance and practical application value for farmers' credit decision making.
Vorheriger Artikel Permeability characteristics of bedrock fissures under disturbance conditions based on neural network
Nächster Artikel Two-stage adaptive integration of multi-source heterogeneous data based on an improved random subspace and prediction of default risk of microcredit

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Metadaten
Titel
Farmers credit optimization decision model and applications based on common risk guarantee fund
verfasst von
Sulin Pang
Min Wei
Zhiming Wen
Publikationsdatum
31.01.2021
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 9/2021
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-020-05651-7

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