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.

馆际互借系统发展趋势研究

通过对当前馆际互借标准和系统的分析调研,结合图书馆馆际互借现状,试图对馆 际互借系统的发展趋势进行探索。

几种馆际互借协议之比较与探讨

论文比较分析了Z39．50 Item order和ILL(Interlibrary Loan)这两种馆际互借协议,还简要介绍了最新的馆际互借协议——Z39．83协议,并分析了其改进之处。

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.

Introduction to the special issue on Crowdfunding and FinTech

Over the past 10 years,crowdfunding,which allows a large number of individuals to collectively finance a new business venture through a technology platform,has risen rapidly as a popular way of financing a wide range of activities including business ventures,personal loans,and charity projects.The modern crowdfunding business mode consists of three types of players:the project proposers who provide the original idea/blueprint/project that requires external finance,potential investors who are interested in the idea,and an internet platform that brings all parties alongside to kick-start the new business venture.

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）.

To supervise or to self‑supervise:a machine learning based comparison on credit supervision

This study investigates the need for credit supervision as conducted by on-site banking supervisors.It builds on a real bank on-site credit examination to compare the performance of a hypothetical self-supervision approach,in which banks themselves assess their loan portfolios without external intervention,with the on-site banking supervision approach of the Central Bank of Brazil.The experiment develops two machine learning classification models:the first model is based on good and bad ratings informed by banks,and the second model is based on past on-site credit portfolio examinations conducted by banking supervision.The findings show that the overall performance of the on-site supervision approach is consistently higher than the performance of the self-supervision approach,justifying the need for on-site credit portfolio examination as conducted by the Central Bank.

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.

A dynamic credit risk assessment model with data mining techniques:evidence from Iranian banks

Giving loans and issuing credit cards are two of the main concerns of banks in that they include the risks of non-payment.According to the Basel 2 guidelines,banks need to develop their own credit risk assessment systems.Some banks have such systems;nevertheless they have lost a large amount of money simply because the models they used failed to accurately predict customers’defaults.Traditionally,banks have used static models with demographic or static factors to model credit risk patterns.However,economic factors are not independent of political fluctuations,and as the political environment changes,the economic environment evolves with it.This has been especially evident in Iran after the 2008-2016 USA sanctions,as many previously reliable customers became unable to repay their debt(i.e.,became bad customers).Nevertheless,a dynamic model that can accommodate fluctuating politicoeconomic factors has never been developed.In this paper,we propose a model that can accommodate factors associated with politico-economic crises.Human judgement is removed from the customer evaluation process.We used a fuzzy inference system to create a rule base using a set of uncertainty predictors.First,we train an adaptive network-based fuzzy inference system(ANFIS)using monthly data from a customer profile dataset.Then,using the newly defined factors and their underlying rules,a second round of assessment begins in a fuzzy inference system.Thus,we present a model that is both more flexible to politico-economic factors and can yield results that are max compatible with real-life situations.Comparison between the prediction made by proposed model and a real non-performing loan indicates little difference between them.Credit risk specialists also approve the results.The major innovation of this research is producing a table of bad customers on a monthly basis and creating a dynamic model based on the table.The latest created model is used for assessing customers henceforth,so the whole process of customer assessment need not be repeated.We assert that this model is a good substitute for the static models currently in use as it can outperform traditional models,especially in the face of economic crisis.

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.

Intelligent Decision Support System for Bank Loans Risk Classification

Intelligent Decision Support System (IISS) for Bank Loans Risk Classification (BLRC), based on the way of integration Artificial Neural Network (ANN) and Expert System (ES), is proposed. According to the feature of BLRC, the key financial and non-financial factors are analyzed. Meanwhile, ES and Model Base (MB) which contain ANN are designed . The general framework,interaction and integration of the system are given. In addition, how the system realizes BLRC is elucidated in detail.

A Tentative Analysis of the Use of Potential by Commercial Bank in Controlling Credit Scale

This article brings forward the conception of potential and filed potential in bank's competition under the inspiration of law of electric current in electrodynamics. It discusses the impact of potential shifting on commercial bank's credit scale and builds up a model for commercial bank to control the scale by credit pricing and risk policy in a dynamic way, and also gives some advice to domestic commercial bank for improving loan business, aiming to settle down the existing credit management problems.

Designing of Commercial Bank Loans Risk Early Warning System Based on BP Neural Networks

According to the index early warning method, a commercial bank loans risk early warning system based on BP neural networks is proposed. The warning signal is mainly involved with the financial situation signal of loaning corporation. Except the structure description of the system structure the demonstration of attemptive designing is also elaborated.

On Financing Models of Real Estate Enterprise

Against the background that the central government is strengthening macro control and tightening credit scale of real estate businesses, financing capacity becomes the determinant for a real estate enterprise＇s development. Domestic enterprises have many ways of financing, and this paper describes ten common models, simply analyses the advantages and disadvantages of each model, while explains and recommends three financing models with practical examples： individual entrusted loan, trust financing and assets securitization.