The Effects of Intangible Assets （IA） on the Loan Interest Rates for Small- and Medium-Sized Enterprises （SMEs） in Taiwan

This study is motivated by the lack of direct empirical research on the relationship between intangible assets （IA） and loan interest rates for small- and medium-sized enterprises （SMEs） in emerging markets. This study uses a multivariate regression to investigate the effects of 1A on loan interest rates by focusing on SMEs. Using a panel sample of 186 publicly-listed SMEs with 952 annual observations in Taiwan from 2001 to 2006, the empirical findings indicate that an SME＇s IA does negatively affect loan interest rates. The main contribution of this study lies in its direct testing of whether IA can affect the loan interest rates for SMEs in an emerging market. The finding provides empirical evidence that an SME with greater IA leads to lower interest rates on bank loans, implying that SMEs should strive to invest in IA and enhance their knowledge management for obtaining more benefits of loan interest rates. Furthermore, the findings may provide empirical evidence for SMEs in emerging markets and can be compared with those for firms in industrialized economies.

Review of Arbitral Award of Network Loan and Analysis of Construction of Implementation Review Rules

The network arbitration cases arising from the network lending disputes are pouring into the courts in large numbers.It is reported that the network arbitration system of some arbitration institutions even“can accept more than 10,000 cases every day,”while online lending is booming,it has also caused a lot of contradictions and disputes,and traditional dispute resolution methods have failed to effectively respond to the need for efficient and convenient resolution of online lending disputes.This paper tries to study the arbitral award of online loans and proposes the construction of implementation review rules.

Hybrid 1DCNN-Attention with Enhanced Data Preprocessing for Loan Approval Prediction

In order to reduce the risk of non-performing loans, losses, and improve the loan approval efficiency, it is necessary to establish an intelligent loan risk and approval prediction system. A hybrid deep learning model with 1DCNN-attention network and the enhanced preprocessing techniques is proposed for loan approval prediction. Our proposed model consists of the enhanced data preprocessing and stacking of multiple hybrid modules. Initially, the enhanced data preprocessing techniques using a combination of methods such as standardization, SMOTE oversampling, feature construction, recursive feature elimination (RFE), information value (IV) and principal component analysis (PCA), which not only eliminates the effects of data jitter and non-equilibrium, but also removes redundant features while improving the representation of features. Subsequently, a hybrid module that combines a 1DCNN with an attention mechanism is proposed to extract local and global spatio-temporal features. Finally, the comprehensive experiments conducted validate that the proposed model surpasses state-of-the-art baseline models across various performance metrics, including accuracy, precision, recall, F1 score, and AUC. Our proposed model helps to automate the loan approval process and provides scientific guidance to financial institutions for loan risk control.

A Model of Interest Rate and Loan Covenant Competition

This paper develops a model where two lenders to subprime borrowers compete with the interest rates charged and the severity of loan covenants. The model has a stable equilibrium, which demonstrates how an increase in the number of borrowers or an increase in the cost of meeting covenants will reduce the severity of the covenants required by lenders, and each of these changes will increase the difference in the severity of the loan covenant levels. An increase in the expected losses to the lender from relaxing covenants will increase the severity of loan covenants, and this will also make the levels of severity more dispersed. Additional analysis demonstrates how exogenous shifts affect the interest rates charged by the lenders and their profits

无息借款与受贿罪的成立

关于国家工作人员向他人无息借款是否成立受贿罪,我国刑法及司法解释均无明确规定,实践中对此类案件的定性也存在较大分歧。化解分歧的关键是准确把握受贿罪“权钱交易”之本质。无息借款中被免去的利息能够被评价为刑法意义上的财物。对“为他人谋取利益”的认定,应以一般人观念为判断基准,结合借贷双方的关系、利息数额的大小及借贷双方与他人的借款情况等因素,综合判断“无息借款中免去的利息”与“为他人谋取利益”是否存在对价关系。若对价关系成立,实行的着手应具体情况具体判断:退还或免除利息、约定或推定无息、特定关系人借款的着手时点分别为接收财物或作出意思表示时、借款合同生效时、可能退还或上交财物的最初时点。若对价关系不成立,则无息借款属正常的民间借贷行为。

坚持以人民为中心的发展思想破解房地产困局——基于降低个人住房贷款利率的角度

中国房地产市场的发展既是经济问题,也是关乎人民利益的社会问题。面对房地产困局,“以人民为中心”应当作为房地产市场政策调整的出发点和落脚点。房地产市场发展的最终目的是为了改善人民的物质文化生活,实现人民共同富裕。从宏观金融角度而言,降低个人住房贷款利率有利于稳定房价,稳定金融市场,助力房地产市场软着陆。从微观角度而言,降低个人住房贷款利率能够降低购房成本,减小生活成本支出,有利于提高人民生活质量,更好地体现“以人民为中心”的发展理念。同时,降低个人住房贷款利率具备相应的理论基础和现实依据,个人住房贷款利率存在继续降低的空间。

抽水蓄能电站TBM全寿命期经济性分析研究

本文通过实际案例计算,采用TBM法施工,对整个抽水蓄能投资的影响情况进行对比分析,从全寿命期分析TBM整体效益,综合考虑固定资产投资额增加,工期缩短后对建设期贷款利息的影响,提前发电后对运营期还本付息额的影响情况。以样本工程的投资数据为基础,提出计算模型。

贷款市场报价利率(LPR)对企业投资决策的影响探究

本文深度剖析了贷款市场报价利率(LPR)的形成背景及其深远意义,详细解释了贷款市场报价利率(LPR)的概念,并分析了其在宏观经济、企业微观层面以及创新领域的深远影响,探讨了贷款市场报价利率(LPR)的变动与企业的投资决策之间的紧密联系。本文运用投资决策理论框架,结合实际案例,采用定量和定性研究方法,从宏观经济、企业微观层面以及LPR调整机制等多个角度,深入挖掘了贷款市场报价利率(LPR)对企业投资决策的潜在影响,并提出了一系列企业应对贷款市场报价利率(LPR)调整变化的策略。本文研究的成果不仅丰富了贷款市场报价利率(LPR)的理论研究体系,还为企业在实际操作中的决策提供了有益的参考和借鉴。

涉农贷款如何实现可持续供给——基于利率定价和补偿测算的四维分析框架

农村金融的可持续发展离不开涉农贷款的供给。但涉农贷款具有低收益和高风险并存的特征,防范和化解风险的同时又要激励银行持续支农,因而需要建立完善的风险补偿机制。本文立足于农村金融的供给侧,通过拓展利率定价中的价格领导模型,厘定可识别风险的贷款利率,提出了以此利率为基础的补偿数额测算方法,构建银行“内部收益补偿-外部收益补偿”“内部损失补偿-外部损失补偿”的四维量化分析框架,并以W农村商业银行为例做了具体测算。研究发现:(1)当前风险补偿以银行内部补偿为主,外部补偿力度不足;(2)银行外部补偿过少和内部补偿过多,会加剧其脱农离农倾向和贷款行业的持续分化;(3)相比损失补偿,银行对涉农贷款的收益补偿需求更多。据此,应以银行主要承担损失补偿和政府加大外部收益补偿为思路,进一步优化涉农贷款的补偿机制。

Modelling time series properties of Australian lending interest rates

The purpose of this paper is to examine the time series properties of Australian residential mortgage interest rates, and in doing so, establish whether or not selected home loan rates （product-level monthly home loan interest rates for CBA） exhibit the expected cyclical and seasonal variations and whether seasonality, if present, is stochastic or deterministic. In particular, due to a well established presence of cyclicality in financial markets＇ interest rates and strong correlation between financial markets＇ interest rates and home loan interest rates, the paper presumes that cyclicality is also to be found in home loan interest rates. Furthermore, the paper tests the hypothesis that home loan interest rates, for selected products, exhibit the three identified （＂Spring＂, ＂Autumn＂ and ＂The end of the Financial Year＂） season-related interest rate reductions. The paper uses a structural time series modelling approach and product-level home loan interest rates data from one of the biggest banks in Australia, Commonwealth Bank of Australia （CBA）. As expected, the results overall confirm the existence of cyclicality in home loan interest rates. With respect to the seasonality of home loan interest rate, although most of the analysed variables show the presence of statistically significant seasonal factors, the majority of the statistically significant seasonal factors observed cannot be attributed to any of the three considered seasonal effects.

A Study on the Ideographic Trend of Chinese Loan Words in Translation

Based on the redefinition of Chinese loan words and corresponding types of Chinese loan words, this article makes an initiative hypothesis that nowadays the ideographic trend of Chinese loan words is being hastened to a greater degree than before.Depending on the Prototype Models Theory for the types of Chinese loan words, a comprehensive analysis of this trend is made in four aspects:the transfer from transliteration loans to loan translation;the ideographic trend of transliteration loans;the full ideograph of shift loan words;word-for-word translation of loan words.

English Loan Words in Chinese and Their Impact on Chinese

The development of China has tremendously enhanced the intercultural communication among various nations and ethnic groups. As a result, more and more words are borrowed from English into Chinese to express those western-oriented objects,concepts, values, etc. This paper focuses on English loan words and their impact on Chinese. First, their classification will be presented; then, this paper will elaborate on the main characteristics of them; at last, their lexical as well as cultural impact on Chinese are revealed. Overall, it aims at proving that English loan words help promote the development and innovation of the Chinese language and enhance the performance of different language learners thus facilitating international exchange and crosscultural communication.

浅谈催收非法债务罪的司法适用

长期以来高利贷的非法性在刑法规制层面缺乏明确的界定,使得实践中对催讨高利贷行为的违法性评价难以形成统一标准;催收非法债务罪的出台为精准打击高利放贷、套路贷等违法犯罪行为提供了有效路径,弥补了立法的不足,但具体适用时应当注重辨析催收非法债务罪与其他罪名的竞合与界分关系,做到定罪精准,罚当其罪。

催收非法债务罪中“非法债务”的法教义学展开

催收非法债务罪的政策目标是同时实现法网严密化和刑罚轻缓化,法益构建需要考虑经济秩序与社会生活秩序两个面向。催收非法债务的行为之所以为刑法所禁止,是因为催收行为之非法性与债务之非法性相加达到了需要科处刑罚的程度。催收非法债务罪中的“非法债务”要素具有双重功能:一是基于非法性,解决处罚根据问题,实现法网严密化;二是基于债务性,解决犯罪界分问题,实现刑罚轻缓化。“非法债务”的认定需要围绕非法性与债务性要素进行类型化考察:对于高利放贷,应当区分普通的民间借贷与经营性的放贷活动,区分集资型、放贷型与充分合意型借贷;对于赌债,应当区分狭义赌债、赌博借贷与出千赌债;对于“套路贷”,应当区分行为人是否实际交付给被害人本金、被害人是否自我答责。

Determinants of loan repayment among agricultural microcredit finance group members in Delta state, Nigeria

Background:This study examined the determinants of loan repayment among microcredit finance group members in Delta State,Nigeria.Methods:To capture the determinants of loan repayment in the study area,a total of 48 microcredit groups and 300 microcredit group members were randomly selected through a multi-stage random sampling technique.The study data was collected by questionnaire.Statistical tools such as simple descriptive statistics(table,frequency,percentage and mean)and a multiple regression analysis were used to examine the data.Results:The results indicate that females form a greater proportion of the study area microcredit group members at 70%,moreover 73%of the respondents have a household size of between 6 to 10 persons.These findings revealed that the groups had a mean 8 years of existence with a mean membership size of 13 persons.Further,an average interest rate of 40 percent per annum was charged on loans,with mean loan duration of 6 months.The regression’s result demonstrated that the determinants of the group member’s loan repayment included the group member’s age,household size,house income,and educational level,the amount of credit received,length of stay in their locality,distance to the credit source,supervision and disbursement lag.Conclusion:Therefore it was suggested that the various agricultural microcredit finance groups should carefully examine the significant determinants of loan repayment for the approach’s viability and sustainability and for optimum repayment performance.

Global Financial Crisis and Accounting Rules： The Implications of the New Exposure Draft （ED） Financial Instruments： Expected Credit Losses on the Evaluation of Banking Company Loans

During the financial crisis, the delayed recognition of credit losses on loans and other financial instruments was identified as a weakness in existing incurred loss model of impairment stated by International Accounting Standards （IAS） 39, because it is believed that this delay might generate pro-cyclical effects. In response to the recommendations of G20, Financial Crisis Advisory Group （FCAG）, and other international bodies, the International Accounting Standards Board （IASB） has undertaken, since 2009, as a part of the project to replace IAS 39, a project （partially shared with Financial Accounting Standards Board （FASB）） aimed at introducing an expected loss model of impairment. Within the scope of this subset project, the IASB has previously issued two exposure documents proposing models to account for expected credit losses： an exposure draft （ED） Financial Instrument： Amortized Cost and Impairment, published in November 2009, and a supplementary document （SD） Financial Instrument： Impairment, published jointly with the FASB in January 2011. However, neither of the two proposals received strong support from interested parties. Recently, the IASB, after the FASB＇s decision to withdraw from the joint project and to develop a separate expected credit loss model based on a single measurement approach consisting in the sole recognition of lifetime expected credit losses, published a third proposal--Ahe so-called expected credit losses model （ED/2013/3 Financial Instruments： Expected Credit Losses）.

Central bank digital currency,loan supply,and bank failure risk:a microeconomic approach

Central bank digital currencies(CBDCs),which are legal tenders in digital form,are expected to reduce currency issuance and circulation costs and broaden the scope of monetary policy.In addition,these currencies may also reduce consumers’need for conventional demand deposits,which,in turn,increases banks’loan provision costs because deposits require higher rates of return.We use a microeconomic banking model to investigate the effects of introducing an economy-wide,account-type CBDC on a bank’s loan supply and its failure risk.Given that a CBDC is expected to lower the cost of liquidity circulation and become a strong substitute for demand deposits,both the loan supply and the bank failure risk increase.These increases are countered by subsequent increases in the rates of return on term deposits and loans,which,in turn,reduce the loan supply and thus bank failure risk.These offsetting forces lead to no significant change in banking,as long as the rate of return on loans is below a certain threshold.However,once the rate is above the threshold,bank failure risk increases,thereby undermining banking stability.The problem is more pronounced when the degree of pass-through of funding costs to the loan rate is high and the profitability of a successful project is low.Our results imply that central banks wishing to introduce an economy-wide,account-type CBDC should first monitor yields on bank loans and consider policy measures that induce banks to maintain adequate liquidity reserve levels.

Loan growth and bank solvency:evidence from the Pakistani banking sector

Background:The dramatic loan growth and changes in the Pakistani banking system in mid-2000s have led to significant research attention on borrowers and lenders.This expansion and diversification in financial sector was driven by structural reforms,political stability and significant economic growth.Against this background,this study investigates the loan growth and risk-taking behavior of the banks during the expansionary periods of lending.Method:This study used dynamic two-step system generalized method of moment’s estimation technique,based on data taken from 32 banks in Pakistan over 2006-2014.Result:Loan growth has a significant effect on bank-specific and macroeconomicspecific variables.Loan growth in the previous year raises non-performing loans and decreases the solvency of banks with a time lag of many years.The driving force behind this phenomenon is weak prudential regulation among competitors,the asymmetric information of the borrowers,and,most importantly,that banks underestimate the risk of lending during credit booms.Conclusion:More regulatory measures are required to ensure a strong financial system when the volume of non-performing loan grows significantly.An increase in the capital requirement policy for rapidly growing banks is also needed because the problem of abnormal loan growth cannot be detected at the current time.At the same time,strong supervision is necessary to avoid the adverse consequences of borrower selection.

A Knowledge-based System for the Analysis of the Ability of Paying back Loans

This paper describes the development of a knowledgebased system (KBS) for determining whether or not, and under what conditions, a bank Ioan officer should grant a business loan to a company. The prototype system developed focuses on what is bank loans risks management, how to prevent risk by the analysis of the ability of paying back loans. The paper makes the structural analysis involved in the system's decision situation, the structured situation diagram or model, dependency diagram and the document needed by the KBS prototype system thus are developed. Through testing the samples from loan business, the quality for the analysis of the ability of paying back loans can be effectively evaluated by the KBS prototype system.

Bank loan information and information asymmetry in the stock market:evidence from China

In this study,we use bank loan information to construct proxies for corporate transparency and examine whether these measures reflect information asymmetry in the stock market.Our analysis is based on a novel dataset of stock transactions and bank loans of all publicly listed firms on the Shenzhen Stock Exchange,covering January 2008 to June 2013.We find that firms with outstanding loans have a lower level of information asymmetry in the stock market,whereas firms with defaulted loans have a higher level of asymmetry.Further evidence demonstrates that the effect of loan default on information asymmetry in the stock market is more pronounced when these loans are borrowed from joint-equity commercial banks or multiple banks and when the default occurs under inactive market conditions.Our results remain robust to a series of endogeneity and sensitivity tests and provide suggestive evidence of a close connection between the credit loan and stock markets.