向非金融法律实体发放贷款时的风险评估

Daniele Dias Cardoso, Nilton César Lima
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引用次数: 0

摘要

目的:本研究旨在核实法人实体通过与客户谈判融资发放信贷时的风险评估程序。研究方法:在一家与信息技术有关的 XYZ 机构进行的实验研究中,采用了文献法,强调定性分析。结果:他们指出,考虑到公司的历史、文件、担保、财务健康状况、现金流、负债、公司治理和市场前景,通过评估阶段确定的信用分数和评级分数可以对其分析的客户进行风险分类,从 "阿尔法 "客户的 AAA 到 "贝塔 "客户的 D。由此可以推断,信用评估是商业活动融资决策的适当自动化,能够促进财务灵活性和商业敏捷性。因此,客户风险分类被视为改进 XYZ 公司财务决策、最大限度地降低违约风险和保证其商业运营的财务安全的基本工具,它是为违约和非违约公司建立风险评分的结果。研究的贡献:本研究通过强调验证融资标准的重要性以及可能影响决策的背景因素,为研究领域做出了相关的理论贡献。实际贡献在于分析了大流行病背景下的非金融机构,以及他们如何通过建立信用分析机制最大限度地减少违约情况,从而为贷方提供改进和更大的安全保障。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Risk assessment when granting credit to non-financial legal entities
Purpose: This study aimed to verify risk assessment procedures when granting credit by a legal entity via financing in negotiations with its customers. Methodology: A documentary approach was used, emphasizing qualitative analysis, during the experimental study conducted at an XYZ organization linked to information technology. Results: They point out that the credit score and rating score, established through the evaluation stages, taking into account the company's history, documentation, guarantees, financial health, cash flow, indebtedness, corporate governance, and market prospects, enable the risk classification of their analyzed clients, ranging from AAA for the "alpha" client to D for the "beta" client. This result made it possible to deduce that credit assessment is appropriate automation in financing decisions for commercial activities, capable of promoting financial flexibility and commercial agility. Customer risk classification is therefore seen as a fundamental tool for improving XYZ's financial decisions, minimizing default risks, and guaranteeing the financial security of its commercial operations, resulting from establishing risk scores for both defaulting and non-defaulting companies. Contributions of the Study: This study makes a relevant theoretical contribution to the field of research by highlighting the importance of validating the criteria used in granting financing, as well as the contextual factors that can affect decisions. The practical contribution of analyzing a non-financial institution under the pandemic context and how they minimize their default by establishing credit analysis mechanisms provides improvements and consequently greater security as lenders.
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