Why The Constitution Should Protect Personal Credit Information?——An Approach of Right Argumentation

Protecting personal credit information through constitutional rights is not only essemtial for individuals to defend against infringements on their personal credit information rights and interests by public power in the social credit system,but also a requirement for unified legislation on social credit to explore the basis for constitutional norms.In the era of the credit economy,personal credit information has become a vital resource for realizing personal autonomy.Along with the increase in the state’s supervision and control of personal credit,the realization of the autonomous value in the interests related to personal credit information has also set more obligations for the state.Therefore,interests related to personal credit information should be regarded as a constitutional right.Because of its significant economic interest and value,the right to personal credit information should be classified as a constitutional property right.As a constitutional property right,the right to personal credit information can not only help protect people’s economic interests,but also achieve the goal of safeguarding their personality interests.

The Credit Risk Assessment Model of Internet Supply Chain Finance: Multi-Criteria Decision-Making Model with the Principle of Variable Weight

The characteristics of the financing model are firstly analyzed when the e-commerce enterprises participate in the supply chain finance. Internet supply chain finance models are divided into three categories with the standard of whether the electronic commerce enterprises provide funds for small and medium enterprises instead of banks. And then we further study the financing process and the functions of the e-commerce platform with specific examples. Finally, combined with the characteristics of the supply chain finance model, we set up a small and medium enterprises credit evaluation model based on the principle of variable weight with its dynamic data. At the same time, a multi-time points and multi-indicators decision-making method based on the principle of variable weight is proposed and a specific example is presented. In this paper, the multi-criteria decision-making model with the principle of variable weight has been used two times. At last, a typical case has been analyzed based on this model with a higher accuracy rate of credit risk assessment.

The Credit Risk Assessment Model of Internet Supply Chain Finance: Multi-Criteria Decision-Making Model with the Principle of Variable Weight

The characteristics of the financing model are firstly analyzed when the e-commerce enterprises participate in the supply chain finance. Internet supply chain finance models are divided into three categories with the standard of whether the Electronic commerce enterprises provide funds for small and medium enterprises instead of banks. And then we further study the financing process and the functions of the e-commerce platform with specific examples. Finally, combined with the characteristics of the supply chain finance model, we set up a small and medium enterprises credit evaluation model based on the principle of variable weight with its dynamic data. At the same time, a multi time points and multi indicators decision-making method based on the principle of variable weight is proposed and a specific example is presented. In this paper, the Multi-criteria decision-making model with the principle of variable weight has been used two times. At last, a typical case has been analyzed based on this model with a higher accuracy rate of credit risk assessment.

Research on the Influencing Factors of Personal Credit Based on a Risk Management Model in the Background of Big Data

Between states, between enterprises and enterprises, between people, it can be stated that credit is full of every corner of our lives. But the current lack of social credit is fundamental. Credit risk is particularly prominent. In the extensive data generation today, the information on personal credit statistics is very large, but still lack the data system processing and screening. Through the information retrieval of 200 credit information reports, this paper constructs the evaluation system of personal credit by using the basic information of the individual. The basic information of these individuals has great convenience in information collection and information statistics, and this basic information covers all aspects that are likely to result in the breach of contract. Through the use of single factor analysis and logistic model to solve the index system, you can not only find the impact of individual indicators on the degree of personal credit, but also see the overall impact of indicators on the degree of credit, that is, the weight of the indicators. Finally, four different credit ratings are divided by assigning the indicators to the scores. Credit rating can clearly measure the respective credit situation. Through the classification of these levels, measuring the credit line when a person in the individual credit operation, at the same time, it can provide reference and proval to administrative departments, which is benefit for managing credit risks. It has a substantial meaning and value in use. The solution to the rating system cannot only be applied to individuals, but also to the enterprises, with a wide range of versatility.

A new method of AHP applied to personal credit evaluation

This paper presents a new negative judgment matrix that combines the advantages of the reciprocal judgment matrix and the fuzzy complementary judgment matrix, and then puts forth the properties of this new matrix. In view of these properties, this paper derives a clear sequencing formula for the new negative judgment matrix, which improves the sequencing principle of AHP. Finally, this new method is applied to personal credit evaluation to show its advantages of conciseness and swiftness.

Research on Personal Credit Risk Assessment Model Based on Instance-Based Transfer Learning

Personal credit risk assessment is an important part of the development of financial enterprises. Big data credit investigation is an inevitable trend of personal credit risk assessment, but some data are missing and the amount of data is small, so it is difficult to train. At the same time, for different financial platforms, we need to use different models to train according to the characteristics of the current samples, which is time-consuming. In view of these two problems, this paper uses the idea of transfer learning to build a transferable personal credit risk model based on Instance-based Transfer Learning (Instance-based TL). The model balances the weight of the samples in the source domain, and migrates the existing large dataset samples to the target domain of small samples, and finds out the commonness between them. At the same time, we have done a lot of experiments on the selection of base learners, including traditional machine learning algorithms and ensemble learning algorithms, such as decision tree, logistic regression, xgboost and so on. The datasets are from P2P platform and bank, the results show that the AUC value of Instance-based TL is 24% higher than that of the traditional machine learning model, which fully proves that the model in this paper has good application value. The model’s evaluation uses AUC, prediction, recall, F1. These criteria prove that this model has good application value from many aspects. At present, we are trying to apply this model to more fields to improve the robustness and applicability of the model;on the other hand, we are trying to do more in-depth research on domain adaptation to enrich the model.

A Cuideto Personal Credit

The construction of a social credit system is a social systematic pro-ject.China’s social credit system includes four aspects:social credit sys-tem,credit management and service system,credit practices。

Journeying with the Terminally Ⅲ： Decision-making Issues and Challenges

The article intends to present a patient＇s illness experience while reflecting on the individual＇s inner struggle. The apparent inconsistencies in the patient＇s care decisions from time to time could actually be the result of inner unresolved struggle. Care givers and family members could become easily disenchanted and think the patient is being difficult, or simply refusing care. The author will highlight some issues of ethical importance. First, there is individual struggle by the patient in accepting a terminal diagnosis. While the patient may have an intellectual understanding of a diagnosis, spiritually,the patient needs human support in accepting the reality of a terminal condition. Second, there has to be an acknowledgment of the patient＇s individuality by family and care givers. Third, respect for patient＇s autonomous decision making right. The author will argue that respect for persons essentially recognizes the autonomy of each individual as a decision maker for the self. This has to be recognized with every individual, especially the most vulnerable. When an individual is not able to actively exercise the decision making power, one could use a surrogate decision maker or an advance directive. The author＇s goal is to argue that care givers should make terminal care as compassionate as possible by relating to patient＇s spiritual, psychological and physiological needs.

社会交互成本理论与社会信用法的法理重构

社会信用体系建设探索实践面对法治拷问,社会交互成本理论对社会信用法治之路将如何前行进行了回应。该理论通过揭示和描述社会信用机制的内在规律,对我国社会信用体系建设当前实践给出了学理解读。在社会交互成本理论看来,社会信用建设现有的法治探索经验显示,社会信用法在法律的调整对象等一系列方面已然显现新的特征,以“行为本位”为前提的法理思维已经无法涵括社会信用法领域出现的新的法律现象。在依据社会交互成本理论形成的法理观念看来,社会信用法的调整对象已不只是信用行为,而是信用行为习惯及其背后的社会关系;调整手段不只是国家的强制力,而是国家强力规制与社会自我管理有机融合;调整方式不再是单纯的负面惩戒,而是以正向调整鼓励守信为主。

基于逻辑回归的个人信用评分卡模型研究

构建有效的个人信用风险评价系统,用以应对潜在的个人信贷风险,这对金融行业和社会公众皆有重要的现实意义。文章首先对数据进行清洗、预处理,然后通过WOE编码分箱、IV值进行变量筛选,构建了逻辑回归模型并基于逻辑回归模型建立了个人信用评分卡模型,该模型可辅助决策者制定合理的授信政策、定价策略以及其他相关业务运营策略。

个人信用信息异议权保护研究

个人信用信息异议权在保障个人信用信息权益层面发挥着重要作用,但在个人信用信息异议权的立法中存在异议处理程序不完善、不良信息保存规则不合理、信息处理者事先告知义务缺失以及举证责任规定不一致等问题。为解决上述问题,应在结合我国实际情况的基础上借鉴域外有益经验,完善异议处理程序,细化异议处理机制,确保个人信息主体能够充分行使个人信用信息异议权。

个人信用信息采集范围最小化原则之替代方案

被许多国家立法奉为个人信息收集行为基本准则的最小化原则,适用至个人征信领域会产生理论不适和现实弊端。三种优势互补的系统组合方案可以成为个人信用信息采集范围最小化原则替代之选:以绝对敏感信息为主要内容的负面清单制度,通过确定禁止采集的信用信息范围实现对信用主体核心权益的底线保护;相关性原则将最小化原则意涵中的直接相关性拓展至间接相关性,这使得相对敏感信息和替代数据能够有条件地进入个人征信系统;从采集最小化原则到使用最小化原则体现了“严进”向“严出”征信理念的转变,它要求个人征信机构和信用信息使用者做到“最少使用”和“最小侵害”。

征信体系建设下个人信息保护的进路研究

目前,我国征信体系在社会多个领域实现了覆盖且仍在深入。为弥补“结果保护”理念引发的个人信息收集与共享泛化、个人信息处理规则透明度较低等缺陷,应引入“过程保护”理念,明晰个人征信信息收集、共享的范围,加强有关征信规则的有效应用。同时,要统筹个人征信与失信惩戒的体系建设,明晰个人征信信息侵权赔偿的认定标准,进而实现对个人信息的有效保护。

基于机器学习的不平衡数据下个人信用评分预测模型研究

文章介绍了个人信用评分的基本概念,以及不平衡数据及其处理方法和机器学习算法在信用评分中的应用。然后,通过数据预处理,包括数据来源与特性、数据清洗与整理、数据不平衡分析、数据增强方法和效果评估,为后续模型构建提供基础。最后,使用实际数据集进行模型训练和测试,并评估模型的性能。实验结果表明,基于机器学习的不平衡数据下个人信用评分预测模型能够有效地预测个人信用风险,对于金融机构的风险管理和信贷决策具有重要意义。

社会信用与城市创业活跃度

本文在探析社会信用影响城市创业活跃度理论机制的基础上,选取2008—2018年中国285个城市作为研究样本,利用城市失信被执行人数据表征社会信用,并与用于刻画城市创业活跃度的新增企业注册信息相匹配,实证分析社会信用对城市创业活跃度的影响效应及作用机理。研究结果显示,社会信用能够提升城市创业活跃度。该结论在处理内生性问题,以及替换不同度量指标、排除相关政策影响、考虑滞后效应、更换研究样本和剔除异常样本等稳健性检验之后仍然成立。机制分析结果表明,社会信用通过促进劳动力集聚、吸引风险投资以及降低交易成本三方面机制,进一步提升城市创业活跃度。进一步分析结果表明,社会信用对中西部地区城市、一般等级城市创业活跃度的提升作用更强,其有利于提升资本密集型和劳动密集型行业创业活跃度,但对技术密集型行业创业活跃度的影响不明显;不同城市的创业活跃度存在正向空间关联性,社会信用不仅能够激发城市的创业活力,还有利于提高相邻城市甚至地理距离更远关联城市的创业活跃度。

Odor cues rather than personality affect tadpole deposition in a neotropical poison frog

Animals constantly need to evaluate available external and internal information to make appropriate decisions.Identifying,assessing,and acting on relevant cues in contexts such as mate choice,intra-sexual competition,and parental care is particularly important for optimizing individual reproductive success.Several factors can infuence decision-making,such as external environmental cues and the animal’s own internal state,yet,we have limited knowledge on how animals integrate available information.Here,we used an entire island population(57 males,53 females,and 1,109 tadpoles)of the neotropical brilliant-thighed poison frog Allobates femoralis to investigate how 2 factors(olfactory cues and personality traits)infuence the ability of males to fnd and use new resources for tadpole deposition.We experimentally manipulated the location of tadpole deposition sites and their associated olfactory cues,and repeatedly measured exploration and boldness in adult males.We further reconstructed tadpole deposition choices via inferred parent–offspring relationships of adult frogs and tadpoles deposited in our experimental pools using molecular parentage analysis.We found that the discovery and use of new rearing sites were heavily infuenced by olfactory cues;however,we did not fnd an effect of the measured behavioral traits on resource discovery and use.We conclude that in highly dynamic environments such as tropical rainforests,reliable external cues likely take priority over personality traits,helping individuals to discover and make use of reproductive resources.

数字化个人破产信用评价机制构建的机理、困境与图景

基于数字时代实施个人破产制度的现实需要、数字司法对于破产案件办理的改革要求、数字社会中的信用不可见风险,构建数字化个人破产信用评价机制已经成为支撑个人破产制度建立实施的重要内容。以“数据—算法—平台”三维结构为框架的数字化个人破产信用评价机制在通过信用数据采集、算法信用画像、平台联通应用得以实施的同时,面临着数据孤岛导致的非正义前见、算法黑箱引发的公信力危机、平台薄弱产生的应用性困境等问题。未来可以通过合作治理达成信用数据共享,依托可信算法实现信用评价公信,完善制度供给推动破产平台建设,以此驱动数字化个人破产信用评价机制更好、更有力地赋能社会信用体系和个人破产制度建设。

大数据技术与个人征信评估:作用机制和实践路径

大数据征信作为社会信用体系构建的关键环节,外延了信用体系的内涵,丰富了信用管理的手段和范围。基于大数据技术使用场景,从信息集成、流程优化和安全维护三个维度对大数据技术应用于个人征信评估的优势展开系统分析,深入探究大数据技术应用于个人征信评估的作用机制,并从加强立法约束、降低数据歧视、注重信息保护三个方面提出大数据技术应用背景下个人征信评估的实践进路,以更好地发挥大数据技术对征信体系及金融领域的赋能作用。

基于贝叶斯优化LightGBM的个人信用评估模型

针对传统信用评估模型无法处理大规模不平衡数据以及训练用时长、评估不准确等问题,提出了一种优化的个人信用评估模型,模型基于梯度提升框架LightGBM,结合贝叶斯全局优化算法进行个人信用评估。为验证模型适用性,采用Lending Club公开数据集进行相关实验,并与逻辑回归、随机森林、XGBoost模型的预测结果进行比较。实验结果表明,该模型的个人信用评估效果更好,评估准确率达到99.97%,少数类样本F1-score达到89.02%。

基于图卷积网络的个人信用评估研究

传统的机器学习模型无法表现出个人信用评估问题中贷款者之间的高维邻居关系,通过构造图数据,利用图卷积网络进行分类预测的方式可以考虑贷款者在多个信息维度的相互联系。首先,利用递归特征消除(Recursive Feature Elimination,RFE)进行特征选择,筛选出贡献度最大的特征集。其次,利用随机森林(Random Forest,RF)计算出筛选后特征的重要性权重,同时将特征划分为类别特征和数值特征,根据特征类型并结合特征权重计算贷款者之间的距离,从而得到邻接矩阵。最后,将构造的图数据输入图卷积网络(Graph Convolutional Network,GCN)进行训练并预测结果。基于公开的德国个人信用数据集,通过两种评价指标对比了该模型与4篇近年研究结果,以及通过4种评价指标对比了该模型与3种基准模型。最终结果显示该模型的预测结果均要优于其他模型,能够有效进行个人信用贷款评估问题研究。