DESIGN OF A FUZZY EXPERT SYSTEM: CREDIT RISK ASSESSMENT OF STOCK BROKERAGE FIRMS IN GRANTING FINANCIAL RESOURCES (Article published in Spanish)
DOI:
https://doi.org/10.1016/S0123-5923(07)70019-0Keywords:
Fuzzy Inference System, risk analysis, tally quota, credit riskAbstract
This research work reviews and describes the model of a system to allocate financial resources to stock brokerage companies and ensure that resources are invested for the benefit of the company (investor) in such a way that it not only mitigates the risk of not receiving equity payments, but also generates additional yields to the company from the equity investment. The model based on fuzzy expert systems allows sustaining these decisions of allocating financial resources. The paper initially provides a description of the necessary conceptual framework to ensure proper understanding of the system. Then it discusses a general description of the inference system, thereby taking into account the selection of entry variables and the creation of 3 integrated macro-assessments (risk analysis, fundamental analysis, and financial analysis). These assessments allow calculating the financial resources or credit limits allocated to each stock brokerage firm. The last section provides a review of 10 randomly selected firms to prove and validate the model and ensure that it yields results that are consistent with an expert assessment. The results can then be used in the everyday assessment of brokerage firms.
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