Bank Credit Risk Management Early Warning and Decision-making based on BP Neural Networks
|
|
- Theodore Morrison
- 8 years ago
- Views:
Transcription
1 Bank Credit Risk Management Early Warning and Decision-making based on BP Neural Networks 1 Zhi-Yuan Yu, 2 Shu-Fang Zhao 1 Department of Economics and Management, Taiyuan Institute of Technology, Taiyuan Shanxi, China, economicer@sina.com 2 Institute of Computer Science and Technology, Taiyuan University of Science and Technology, Taiyuan, Shanxi, China Abstract Credit management, which is the basic of the credit application, is the most perfect embodiment in the bank credit application and asset supervision. The ultimate purpose of credit management is to ensure that credit fund is of safety, profit and fluidity. At present, it is extremely important of commercial banks to set up an early bank system. The author who makes great effort on the credit and its reason, besides bringing in the western commercial banks experience of bank credit management, makes researches on credit in a microcosmic view. The author sets up early indicators for commercial bank credit, and carries out the for the credit in advance with the help of artificial neural networks. The experiment has proved that this method is objective and effective. So it can provide theoretical basis, which is more scientific and credible for detection and early about commercial bank credit. 1. Introduction Keywords: BP Neural Networks; Credit Risk; Early Warning; Decision-Making Since any business are faced with various s, the commercial bank operating financial assets as a special enterprise, even operating its special management target, a wide range of social contact and a strong far-reaching influence becomes the focus of the of separation. Credit of commercial bank credit s faced by commercial banks, is the most basic, the most ancient and most dangerous [1]. Generalized credit refers to the loan principal security and income uncertainty and volatility, all kinds of uncertain factors lead to banking financial institutions in the business activities of loss or gain extra income a possibility. Special credit refers to the bank loans can not be recovered, resulting in the possibility of loss of credit funds. In actual operation, the bank 's first concern is to narrow the credit. Because only realized the value of assets, could they talk about the income. According to the present our country banking industry 's specific situation, bank credit assets makes most of the bank assets [2].This paper mainly studies the narrow credit. Credit activities mainly involves banks, borrowers and monetary fund. The maintain of relationship between banks and borrowers needs borrowing, which is with monetary fund as an intermediary. As a result of this lending relationship takes place in the economic environment, they are limited by the environmental factors and impacts. At present,the bank credit comes mainly from the following several aspects: (1) The market. Currency market fund price changes led to the bank the potential loss that market s, including interest rate, exchange rate and inflation. For the market interest rate as the fund demand fluctuations, so when the loan interest rate is higher than the credit contract interest rate, it will cause the credit assets relative loss. Exchange rate in general international credit activity occurs in. The is the main reason for China s interest rate and exchange rate management is still not fully open, belong to a kind of macroscopical management y (2) The operational is caused by not a sound internal control system, fault management, low quality of personnel and the personnel such as moral hazard. The operation of the employees by moral of fraud, will cause huge loss to the bank. (3) Credit refers to the that the debtor fails to repay the default due to various reasons causing the possibility of loss and its size. It is the most common, but also caused the loss of one of the biggest s in a commercial bank. When the bank carries on the credit, it will judge the borrower's credit level. But the borrower's credit level is not fixed, and it will have a credit, if out Advances in information Sciences and Service Sciences(AISS) Volume5, Number9, May 2013 doi: /aiss.vol5.issue
2 of control of the bank. Credit is often caused by the financial crisis and it makes the bank faces huge loss. Therefore converting the bank credit measurement to measure the financial situation of enterprises is the effective way to reduce credit. The establishment of commercial bank credit early index, which used artificial neural network to forecast the credit of the credit management system is the reason that forms this context[3]. Enhancing credit management to respond to the new financial situation and credit quantitative research is the necessary task of commercial banks. Our country commercial bank loans to enterprises financial condition monitoring is not enough, usually after treatment rather than prevention, qualitative analysis quantitative analysis more, even when the credit assets and losses, the bank can not aware. When the bank credit assets are aware, has become bad debts and bad debts, resulting in the loss of the credit assets of commercial banks. Therefore, credit management system based on the BP neural network for commercial bank credit management[4], can any time analyze loan financial situation and management performance of enterprises to conduct a comprehensive, systematic analysis, through a simple statistical processing, resolution of the financial situation of enterprises, on the commercial bank credit precaution is necessary. From the bank credit management theory, credit has the diffusion and hidden features, if not controlled in time, will have a great impact on Commercial Bank management. And through the use of credit management system based on BP neural network,the of bank credit is to perfecting the management, it complements the commercial bank credit quantification in theory. From the information economics theory, credit is the fundamental cause of the asymmetry of information. For example, before the credit contracts signed, the borrower has more information in about their own financial status, use of the loan and the of investment projects ; and after it, they have more complete information in about the practical use of funds and the completion of the project[5]. As funding,the bank not directly involved in the actual operation of investment projects, they only through indirect channels to understand the statement investment project benefits and s. The asymmetric information in the financial intermediary and the nature of the financial intermediary intrinsic vulner has a special significance. Moral and adverse selection in this asymmetry is generated under the surroundings. In the bank credit market, facing the degree of different credit enterprises, banks often fail to identify enterprise project investment. And the use of credit management system based on BP neural network can provide the basis for 2. Construction BP neural networks principle and model 2.1. BP neural networks principle How to analysis the credit and is more important. From the point of the practice of bank credit management, the analysis of financial statement is the credit management important link, and the credit management system based on BP neural network can clearly reflect the customer's credit and financial situation[7]. Through quantitative analysis, it can objectively reflect the financial information. The use of credit management system based on the BP neural network can solve the credit management departments the poor information sharing, credit decision-making non-standard wait for a problem more standardized. The Application of credit management system based on BP neural network can monitor the credit continuously and effectively,making more scientific credit decision mechanism. BP neural networks is a nonlinear self-adaptive dynamic system, which simulates human s neural system structure. It is composed of a lot of collateral neural elements which have the of learning, memorizing, computing and intellectual handling. Generally include one input layer, connotative layers and one output layer. Each node between two close layers joins each other in single direction. In order to forecast the Credit BP neural network and to avoid the shortcoming of traditional methods, BP Algorithm that is improved is adopted to settle the problem in this thesis. Optimization methods are also introduced. It has already proved that using one input layer, many connotative layers and one output layer, it can realize the mapping from arbitrary M dimension to N dimension. So, in the neural networks algorithm of the bank's credit evaluation we generally choose three layers. Structure of three -layers neural 429
3 networks is shown in figure 1. I1 I2 Output I3 I4 Figure 1. Structure of three -layers neural networks The connotative layer node and the output layer node's transfer function uses the Sigmoid function: 1 ƒ(x)=. 1 e x The application of BP neural networks is the most extensive at present; BP neural network has more self-adaptive capacity. The application including training and testing two stepping course. The purpose of network training is to find a set of weights, and makes it minimum. In three BP neural networks, what is quite big to the network performance influence is the weight correction method, uses the following method revision weight: E Djk Djk Djk Djk D jk E Dij Dij Dij Dij D In the equation, (0< <1)is a positive constant, called studying rate,which reflects the adjustment speed of the weight.if is too small, the efficiency of study is relatively low. Conversely, if is too large, it may cause oscillation. For this reason, we introduce the momentum. Doing this can strain the high-frequency deviation of error-curved surface in weight space, and then make the interval of effective weight strengthen. Under the normal circumstances, while the momentum can reduce shaking, it makes the restraining speed of algorithm faster Construction of BP neural networks model The customer degree of comparison evaluation is the credit management foundational work. The evaluation content take credit capacity as a core, overall evaluation profit, business, factors and so on management, after the synthesis evaluation, obtains the customer degrees of comparison, establishes including the enterprise operational, management, the financial and the credit record early signal system, sets each target the marginal value, when some target tends a critical point, sounds can warn promptly. (1) Designing the input layer. The BP neural networks can only deal with the numerical data[6], so the quantitative index need be standardized and the qualitative index is quantized and standardized, generally in the limitative scope [0,1]. The nodes in the input layer correspondent to 14 indexes of 4 types in small and medium-sized enterprise credit evaluation. (2) Robert Hecht-Nielson proves that one BP networks with implicit layer can approach continuous function in the close block in 1989; therefore this paper contains an implicit choice of the three-layer BP neural network. The nodes number of the connotative layer is confirmed as 3 in experimentation. The number is the best when the total error of the system is minimum. While the number is confirmed as 3, with passing the test, the total error of the system is minimum. (3) Designing the output layer. The output node is 1.The police degree of early system has four kind of situations: normal, low-, medium and high-. It is the status output. Output is ij 430
4 normal (1000), low- (0100), Medium Risk Alert (0010), high- (0001). 3. Decision system of credit The early is a key link for credit control[8]. Early of the commercial bank credit is a process that the mode categorize: from the mapping relation along promise alert index alert feeling index and alert degree. Economic early is the course of a approximation of function; From the noise along Promise alert index alert feeling index and alert degree and Handling in the way with calling the police accurately, Economic early-- is the optimum course. So, a BP neural network that applies to early of the commercial bank credit is suitable. BP neural networks is composed of input layer connotative layer output layer. Input layer corresponding to alert index of promising, connotative layer corresponding to alert feeling index, output layer corresponding to alert degree Alert indexes The target early method is the commonly used early method. Alert index can be deemed to finance rate of input layer. Finance rate, an important aspect in quantities research on the corporation credit, is the main portion about the evaluation of the corporation credit. Moreover, credit is the key. Corporation credit evaluation system is mainly considered into four aspects that are the to refund, to profit, to operate and manage, developmental and potential, through the credit rating the credit transfers guarded against in anticipation before from supervised afterward. Especially, a bank will pay more attention to it about the valuation of the corporation credit. A company finance condition system that adapts to loaning has been utilized. In order to cope with the imprecise analysis and judgment and to make the operation easy. The system include four finance portions the to refund, to profit, to operate and manage. The following table 1 make a illustration about them in detail: Table 1. Alert index Criterion Index name Calculate formulae The to refund The to profit Management and administration asset-li ratio liquidity ratio rapidly ratio cash ratio debt ratio of cash in business activities current cash ratio rate of main business profit and financial expenses main business profit ratio net assets profit ratio assets profit ratio Turnover rate of the account receivable turnover rate of stock total debt/total asset*100% current assets/ current li*100% rapidly asset/ current li*100% cash assets/ current li*100% current cash in bushiness activities/total debt*100% total of cash net flux of management, investment and raise funds main business profit/ financial expenses*100% main business profit/ main business income*100% net profit/average net assets*100% total profit/total assets*100% main business income/average remaining of account receivable*100% cost of main business/average stock*100% Developmental and potential increased income ratio of main business rate of increase of the profit main business income in this issue/ main business income in last issue*100% (net profit of this issue-net profit of last issue)/net profit of last issue*100% 431
5 3.2. Early BP neural networks apply on loan early, which can make good deal with slowly changing information, and have great study and fault-tolerant. At first, this text carry on discussion with BP neural networks to early mechanism, showing that early system can say with BP model of 3 layers. Correspond to early rules of the index with BP model of 3 layers, And then to the finance early signal, the extraction credit capacity, profit, the management and operation, development and potentiality 4 aspects alert index correspond to input layer to BP,the alert index correspond to implies layer, alert degree is exported layer correspondingly. Alert degree is divided into the normal condition, the low, the middle, the high,as the output of exports layer. Node of connotative-layers act as n=sqrt(m+k)+a (a is a constant between 0 and 10) according to experience,means train and Test with the topological structure of The financial crisis grade regard as similar separate question,for the good moral character of ANN,which has correct rate of classification analyzed more than common discrimination. 4. Experiment design According to the data offered by a commercial bank and feature sample with credit, the to refund, to profit, to operate and manage, developmental and potential can make the input of the networks input layer as four alert index. The alert can be divided into four scales, respectively are normal state, low, mid, high--, and all of them can be used as the input of the network input layer. The data that were inputted have been changed into experiment data. The experiment data are in the following table (table 2): Table 2. Experiment data Alert Enterprise The The Management and Developmental and degree number to refund to profit administration potential Normal state Low Mid High With the help of the toolbox of the Matlab software, the objective error is in the range of the demand. It is illustrated in detail in the following figure
6 Figure 2. Simulation result In order to enable the network model has better to identify the difference, each additional sample will be retrained again. The three-layer BP network optimization model is illustrated in the Figure 1. The error which are used to make credit forecast is less than what is expected by using Matlab learning procedures. As is illustrated in the Figure, emulation trainings suggest: (1) If training samples are the same, the quantity of the connotative layer unit selected can generate a direct influence on network performance. The more connotative layer units are, the more accurate the system's prediction is, and the higher connotative layer units are. (2) If the number of connotative layer units in the same circumstances, the larger the number of training samples are, the better prediction performance BP neural network shows. With the parallel illation for the experiment design, the result can be obtained, using the Matlab neural network toolbox and the bank credit early procedures based on BP neural network, a better credit of early s is available. Furthermore, it can offer the result of an early ; early findings are showed in table Conclusions From the angle of theory combines with practice, this article analyze the profession and causation of loans in bank. And it get the mostly conclusion: (1) Back-propagation neural networks were applied in loans evaluation. It conquered the difficulty of making certain weight, and the character of non-linear was incarnated. In addition, the restrain the speed BP neural networks became faster. (2) Fault-tolerant. Because the network knowledge information adopts the distributional memory, the individual unit s damage cannot cause the output mistake. The fault-tolerant is stronger in the course of prediction and identifiably, and more credit. (3) Because of the limitations of condition and time, I can t consult and collect the sample data of large city and four commercial banks. It must have some limitation. 433
7 Table 3. Test results Enterprise number The to refund The to profit Management and administration Developmental and potential Deduce the result Alert degree ( ) ( ) ( ) ( ) Normal condition The low The middle The high 6. Acknowledgement The author would like to thank the anonymous reviewers for their valuable suggestion and comment on this work. Supported by The Shanxi province social science Joint Fund (SSKLZDKT ): On travel industry of Shanxi exploiting capital market research and the Shanxi Province philosophy and social science fund( ):research on the regional capital markets to establish and resources transformation in Shanxi. 7. References [1] Piramuthu S., Financial Credit Risk Evaluation With Neural and Neurofuzzy Systems, European Journal of Operational Research, Vol. 112, No. 2, pp , [2] LI Rong-zhou, PANG SU-lin, XU Jian-min, Neural network credit- evaluation model based on back-propagation algorithm, Machine Learning and Cybernetics, Vol. 4, No. 3, pp , [3] Peltonen T, An application of panel estimation methods and artificial neural networks, Italia: European University Institute, [4] Chai Binghua, Liao Ningfang, Artificial neural networks performing the forward operation of color appearance model, Journal of Beijing Institute of Technology, pp , [5] Daozhu Xu, Haiyan Liu, An Improved Algorithm for Creation of Delaunay Triangulation,Geomatic and spatial Information Technology, Vol. 30, No. 1, pp , [6] Cairong Wu, Huaxing Huang, "Evaluation and Research on Sports Psychology based on BP Neural Network Model", AISS, Vol. 4, No. 10, pp. 355 ~ 363, [7] Shi Hui-bin, Li Hong, Liu Lu, Wang Li, "A credit assessment system for the small and medium enterprises in China", JCIT, Vol. 7, No. 2, pp. 277 ~ 284, [8] Baosen Wang, Xiaojun Ma, Yunfeng Cui, "Study on Risk Management of Commercial Bank Card of China", JCIT, Vol. 6, No. 9, pp. 186 ~ 191,
Credit risk management of commercial bank
Available online www.jocpr.com Journal of Chemical and Pharmaceutical Research, 2014, 6(5):1784-1788 Research Article ISSN : 0975-7384 CODEN(USA) : JCPRC5 Credit risk management of commercial bank Qian
More informationOpen Access Research on Application of Neural Network in Computer Network Security Evaluation. Shujuan Jin *
Send Orders for Reprints to reprints@benthamscience.ae 766 The Open Electrical & Electronic Engineering Journal, 2014, 8, 766-771 Open Access Research on Application of Neural Network in Computer Network
More informationBank Customers (Credit) Rating System Based On Expert System and ANN
Bank Customers (Credit) Rating System Based On Expert System and ANN Project Review Yingzhen Li Abstract The precise rating of customers has a decisive impact on loan business. We constructed the BP network,
More informationA Prediction Model for Taiwan Tourism Industry Stock Index
A Prediction Model for Taiwan Tourism Industry Stock Index ABSTRACT Han-Chen Huang and Fang-Wei Chang Yu Da University of Science and Technology, Taiwan Investors and scholars pay continuous attention
More informationCredit Risk Assessment of POS-Loans in the Big Data Era
Credit Risk Assessment of POS-Loans in the Big Data Era Yiyang Bian 1,2, Shaokun Fan 1, Ryan Liying Ye 1, J. Leon Zhao 1 1 Department of Information Systems, City University of Hong Kong 2 School of Management,
More informationReal estate investment project risk analysis
Available online www.jocpr.com Journal of Chemical and Pharmaceutical Research, 2014, 6(5):1789-1794 Research Article ISSN : 0975-7384 CODEN(USA) : JCPRC5 Real estate investment project risk analysis Li
More informationStudy on the Evaluation for the Knowledge Sharing Efficiency of the Knowledge Service Network System in Agile Supply Chain
Send Orders for Reprints to reprints@benthamscience.ae 384 The Open Cybernetics & Systemics Journal, 2015, 9, 384-389 Open Access Study on the Evaluation for the Knowledge Sharing Efficiency of the Knowledge
More informationAnalecta Vol. 8, No. 2 ISSN 2064-7964
EXPERIMENTAL APPLICATIONS OF ARTIFICIAL NEURAL NETWORKS IN ENGINEERING PROCESSING SYSTEM S. Dadvandipour Institute of Information Engineering, University of Miskolc, Egyetemváros, 3515, Miskolc, Hungary,
More informationResearch on small and medium enterprises financing mode based on supply chain finance
Available online www.jocpr.com Journal of Chemical and Pharmaceutical Research, 0, ():88-8 Research Article ISSN : 09-8 CODEN(USA) : JCPRC Research on small and medium enterprises financing mode based
More informationDesign call center management system of e-commerce based on BP neural network and multifractal
Available online www.jocpr.com Journal of Chemical and Pharmaceutical Research, 2014, 6(6):951-956 Research Article ISSN : 0975-7384 CODEN(USA) : JCPRC5 Design call center management system of e-commerce
More informationThe Construction of SME Accounting Information System
The Construction of SME Accounting Information System LIU Zhihua School of Business Administration, Jiangxi University of Finance and Economics, P.R. China, 330013 jethro@163.com Abstract: SMEs have become
More informationCredit Risk Comprehensive Evaluation Method for Online Trading
Credit Risk Comprehensive Evaluation Method for Online Trading Company 1 *1, Corresponding Author School of Economics and Management, Beijing Forestry University, fankun@bjfu.edu.cn Abstract A new comprehensive
More informationNeural Network Applications in Stock Market Predictions - A Methodology Analysis
Neural Network Applications in Stock Market Predictions - A Methodology Analysis Marijana Zekic, MS University of Josip Juraj Strossmayer in Osijek Faculty of Economics Osijek Gajev trg 7, 31000 Osijek
More informationPerformance Evaluation and Prediction of IT-Outsourcing Service Supply Chain based on Improved SCOR Model
Performance Evaluation and Prediction of IT-Outsourcing Service Supply Chain based on Improved SCOR Model 1, 2 1 International School of Software, Wuhan University, Wuhan, China *2 School of Information
More informationRISK MANAGEMENT SOFTWARE PACKAGES SOLUTION FOR PERFORMANCE ASSESSMENT
RISK MANAGEMENT SOFTWARE PACKAGES SOLUTION FOR PERFORMANCE ASSESSMENT Dragos Cazacu 1 Abstract This stuff is presenting a short introduction of the software application aiming to assess different types
More informationInternational Monetary Policy
International Monetary Policy 2 Preliminary concepts 1 Michele Piffer London School of Economics 1 Course prepared for the Shanghai Normal University, College of Finance, April 2011 Michele Piffer (London
More informationFault Analysis in Software with the Data Interaction of Classes
, pp.189-196 http://dx.doi.org/10.14257/ijsia.2015.9.9.17 Fault Analysis in Software with the Data Interaction of Classes Yan Xiaobo 1 and Wang Yichen 2 1 Science & Technology on Reliability & Environmental
More informationBoosting SMEs with Better and Innovative Financing Services
ISSN 1816-6075 (Print), 1818-0523 (Online) Journal of System and Management Sciences Vol. 4 (2014) No. 2 Boosting SMEs with Better and Innovative Financing Services Wei Liu 1 1 Department of Integrated
More informationReview on Financial Forecasting using Neural Network and Data Mining Technique
ORIENTAL JOURNAL OF COMPUTER SCIENCE & TECHNOLOGY An International Open Free Access, Peer Reviewed Research Journal Published By: Oriental Scientific Publishing Co., India. www.computerscijournal.org ISSN:
More informationThe relation between news events and stock price jump: an analysis based on neural network
20th International Congress on Modelling and Simulation, Adelaide, Australia, 1 6 December 2013 www.mssanz.org.au/modsim2013 The relation between news events and stock price jump: an analysis based on
More informationRandom forest algorithm in big data environment
Random forest algorithm in big data environment Yingchun Liu * School of Economics and Management, Beihang University, Beijing 100191, China Received 1 September 2014, www.cmnt.lv Abstract Random forest
More informationU.P.B. Sci. Bull., Series C, Vol. 77, Iss. 1, 2015 ISSN 2286 3540
U.P.B. Sci. Bull., Series C, Vol. 77, Iss. 1, 2015 ISSN 2286 3540 ENTERPRISE FINANCIAL DISTRESS PREDICTION BASED ON BACKWARD PROPAGATION NEURAL NETWORK: AN EMPIRICAL STUDY ON THE CHINESE LISTED EQUIPMENT
More informationResearch on the UHF RFID Channel Coding Technology based on Simulink
Vol. 6, No. 7, 015 Research on the UHF RFID Channel Coding Technology based on Simulink Changzhi Wang Shanghai 0160, China Zhicai Shi* Shanghai 0160, China Dai Jian Shanghai 0160, China Li Meng Shanghai
More informationMethod of Fault Detection in Cloud Computing Systems
, pp.205-212 http://dx.doi.org/10.14257/ijgdc.2014.7.3.21 Method of Fault Detection in Cloud Computing Systems Ying Jiang, Jie Huang, Jiaman Ding and Yingli Liu Yunnan Key Lab of Computer Technology Application,
More informationRISK FACTORS AND RISK MANAGEMENT
Bangkok Bank Public Company Limited 044 RISK FACTORS AND RISK MANAGEMENT Bangkok Bank recognizes that effective risk management is fundamental to good banking practice. Accordingly, the Bank has established
More informationChapter 2 The Research on Fault Diagnosis of Building Electrical System Based on RBF Neural Network
Chapter 2 The Research on Fault Diagnosis of Building Electrical System Based on RBF Neural Network Qian Wu, Yahui Wang, Long Zhang and Li Shen Abstract Building electrical system fault diagnosis is the
More informationOptional Insurance Compensation Rate Selection and Evaluation in Financial Institutions
, pp.233-242 http://dx.doi.org/10.14257/ijunesst.2014.7.1.21 Optional Insurance Compensation Rate Selection and Evaluation in Financial Institutions Xu Zhikun 1, Wang Yanwen 2 and Liu Zhaohui 3 1, 2 College
More informationForecasting of Economic Quantities using Fuzzy Autoregressive Model and Fuzzy Neural Network
Forecasting of Economic Quantities using Fuzzy Autoregressive Model and Fuzzy Neural Network Dušan Marček 1 Abstract Most models for the time series of stock prices have centered on autoregressive (AR)
More informationSmall Joint-stock Commercial Bank Lending to Small Business Risk Analysis
Small Joint-stock Commercial Bank Lending to Small Business Risk Analysis WANG Shuying, YAN Chao School of Management, Zhengzhou University, P.R.China, 450001 yanmaohou@yahoo.com.cn Abstract: in China
More informationCONCEPTUAL MODEL OF MULTI-AGENT BUSINESS COLLABORATION BASED ON CLOUD WORKFLOW
CONCEPTUAL MODEL OF MULTI-AGENT BUSINESS COLLABORATION BASED ON CLOUD WORKFLOW 1 XINQIN GAO, 2 MINGSHUN YANG, 3 YONG LIU, 4 XIAOLI HOU School of Mechanical and Precision Instrument Engineering, Xi'an University
More informationPrice Prediction of Share Market using Artificial Neural Network (ANN)
Prediction of Share Market using Artificial Neural Network (ANN) Zabir Haider Khan Department of CSE, SUST, Sylhet, Bangladesh Tasnim Sharmin Alin Department of CSE, SUST, Sylhet, Bangladesh Md. Akter
More informationResearch on the Income Volatility of Listed Banks in China: Based on the Fair Value Measurement
Research on the Income Volatility of Listed Banks in China: Based on the Fair Value Measurement Pingsheng Sun, Xiaoyan Liu & Yuan Cao School of Economics and Management, North China Electric Power University,
More informationModeling of Knowledge Transfer in logistics Supply Chain Based on System Dynamics
, pp.377-388 http://dx.doi.org/10.14257/ijunesst.2015.8.12.38 Modeling of Knowledge Transfer in logistics Supply Chain Based on System Dynamics Yang Bo School of Information Management Jiangxi University
More informationMonitoring and Warning System for Information Technology (IT) Outsource Risk in Commercial Banks Based on Nested Theory of Excel Logical Function
Advance Journal of Food Science and Technology 9(4): 302-307, 2015 ISSN: 2042-4868; e-issn: 2042-4876 Maxwell Scientific Organization, 2015 Submitted: March 3, 2015 Accepted: March 14, 2015 Published:
More informationAnalysis of Influence Factors on Scientific and Technological SMEs Financing Based on DEMATEL
2011 International Conference on Information Communication and Management IPCSIT vol.16 (2011) (2011) IACSIT Press, Singapore Analysis of Influence Factors on Scientific and Technological SMEs Financing
More informationNeural Networks and Support Vector Machines
INF5390 - Kunstig intelligens Neural Networks and Support Vector Machines Roar Fjellheim INF5390-13 Neural Networks and SVM 1 Outline Neural networks Perceptrons Neural networks Support vector machines
More informationData quality in Accounting Information Systems
Data quality in Accounting Information Systems Comparing Several Data Mining Techniques Erjon Zoto Department of Statistics and Applied Informatics Faculty of Economy, University of Tirana Tirana, Albania
More informationEFFICIENT DATA PRE-PROCESSING FOR DATA MINING
EFFICIENT DATA PRE-PROCESSING FOR DATA MINING USING NEURAL NETWORKS JothiKumar.R 1, Sivabalan.R.V 2 1 Research scholar, Noorul Islam University, Nagercoil, India Assistant Professor, Adhiparasakthi College
More informationThe Application of 360 +KPI Performance Evaluation Model in Chinese and Western Culture Background
The Application of 360 +KPI Performance Evaluation Model in Chinese and Western Culture Background Wei Tan The Institute of Public Affairs, Chongqing Three Gorges University The No.780 of ShaLong street,
More informationResearch on the Risk of Human Resource Management Outsourcing for First-class Hotel --- A Case of InterContinental Shenzhen
Universal Journal of Management 4(6): 361-366, 2016 DOI: 10.13189/ujm.2016.040605 http://www.hrpub.org Research on the Risk of Human Resource Management Outsourcing for First-class Hotel --- A Case of
More informationApplication Research of CMM in Real Estate Entreprise Management
International Journal of Business and Management July, 2009 Application Research of CMM in Real Estate Entreprise Management Linjie Chen Nanjing Institute of Industry Technology Nanjing 210046, China E-mail:
More informationThe Combination Forecasting Model of Auto Sales Based on Seasonal Index and RBF Neural Network
, pp.67-76 http://dx.doi.org/10.14257/ijdta.2016.9.1.06 The Combination Forecasting Model of Auto Sales Based on Seasonal Index and RBF Neural Network Lihua Yang and Baolin Li* School of Economics and
More informationUSING LOGIT MODEL TO PREDICT CREDIT SCORE
USING LOGIT MODEL TO PREDICT CREDIT SCORE Taiwo Amoo, Associate Professor of Business Statistics and Operation Management, Brooklyn College, City University of New York, (718) 951-5219, Tamoo@brooklyn.cuny.edu
More informationAnalysis of Defects in Financial Accounting Management of Construction Enterprises and Corresponding Strategies
Send Orders for Reprints to reprints@benthamscience.ae 1218 The Open Cybernetics & Systemics Journal, 2015, 9, 1218-1222 Open Access Analysis of Defects in Financial Accounting Management of Construction
More informationStudy of Lightning Damage Risk Assessment Method for Power Grid
Energy and Power Engineering, 2013, 5, 1478-1483 doi:10.4236/epe.2013.54b280 Published Online July 2013 (http://www.scirp.org/journal/epe) Study of Lightning Damage Risk Assessment Method for Power Grid
More informationPrediction of Stock Performance Using Analytical Techniques
136 JOURNAL OF EMERGING TECHNOLOGIES IN WEB INTELLIGENCE, VOL. 5, NO. 2, MAY 2013 Prediction of Stock Performance Using Analytical Techniques Carol Hargreaves Institute of Systems Science National University
More informationOnline Tuning of Artificial Neural Networks for Induction Motor Control
Online Tuning of Artificial Neural Networks for Induction Motor Control A THESIS Submitted by RAMA KRISHNA MAYIRI (M060156EE) In partial fulfillment of the requirements for the award of the Degree of MASTER
More informationAccounting Information and Stock Price Reaction of Listed Companies Empirical Evidence from 60 Listed Companies in Shanghai Stock Exchange
Journal of Business & Management Volume 2, Issue 2 (2013), 11-21 ISSN 2291-1995 E-ISSN 2291-2002 Published by Science and Education Centre of North America Accounting Information and Stock Price Reaction
More informationBased on Artificial Neural Network in the Training of Human Resources
Based on Artificial Neural Network in the Training of Human Resources Performance Evaluation Analysis Department of Economic and Business Management, Chongqing University of Education, China, 708996379@qq.com
More informationResearch on the Factor Analysis and Logistic Regression with the Applications on the Listed Company Financial Modeling.
2nd International Conference on Social Science and Technology Education (ICSSTE 2016) Research on the Factor Analysis and Logistic Regression with the Applications on the Listed Company Financial Modeling
More informationAn Analysis of Agricultural Risk and Intelligent Monitoring Technology Fantao Kong 1, a, Shiwei Xu 2,b, Shengwei Wang 3,c and Haipeng Yu 4,d
Advanced Materials Research Vol. 628 (2013) pp 265-269 Online available since 2012/Dec/27 at www.scientific.net (2013) Trans Tech Publications, Switzerland doi:10.4028/www.scientific.net/amr.628.265 An
More informationAn Evaluation System Model for Analyzing Employee Turnover Risk
An Evaluation System Model for Analyzing Employee Turnover Risk Xin Wang School of Economics & Management, Dalian Maritime University, Dalian 116026, Liaoning, P.R. China wonderxin@sohu.com Abstract. Evaluation
More informationA Network Simulation Experiment of WAN Based on OPNET
A Network Simulation Experiment of WAN Based on OPNET 1 Yao Lin, 2 Zhang Bo, 3 Liu Puyu 1, Modern Education Technology Center, Liaoning Medical University, Jinzhou, Liaoning, China,yaolin111@sina.com *2
More informationVariable Selection for Credit Risk Model Using Data Mining Technique
1868 JOURNAL OF COMPUTERS, VOL. 6, NO. 9, SEPTEMBER 2011 Variable Selection for Credit Risk Model Using Data Mining Technique Kuangnan Fang Department of Planning and statistics/xiamen University, Xiamen,
More informationNEURAL NETWORKS IN DATA MINING
NEURAL NETWORKS IN DATA MINING 1 DR. YASHPAL SINGH, 2 ALOK SINGH CHAUHAN 1 Reader, Bundelkhand Institute of Engineering & Technology, Jhansi, India 2 Lecturer, United Institute of Management, Allahabad,
More informationMULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question.
ECON 4110: Sample Exam Name MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. 1) Economists define risk as A) the difference between the return on common
More information2. IMPLEMENTATION. International Journal of Computer Applications (0975 8887) Volume 70 No.18, May 2013
Prediction of Market Capital for Trading Firms through Data Mining Techniques Aditya Nawani Department of Computer Science, Bharati Vidyapeeth s College of Engineering, New Delhi, India Himanshu Gupta
More informationNetwork Machine Learning Research Group. Intended status: Informational October 19, 2015 Expires: April 21, 2016
Network Machine Learning Research Group S. Jiang Internet-Draft Huawei Technologies Co., Ltd Intended status: Informational October 19, 2015 Expires: April 21, 2016 Abstract Network Machine Learning draft-jiang-nmlrg-network-machine-learning-00
More informationDATA MINING FOR THE MANAGEMENT OF SOFTWARE DEVELOPMENT PROCESS
International Journal of Software Engineering and Knowledge Engineering Vol. 0, No. 0 (1994) 000 000 c World Scientific Publishing Company DATA MINING FOR THE MANAGEMENT OF SOFTWARE DEVELOPMENT PROCESS
More informationCredit Risk. Loss on default = D x E x (1-R) Where D is default percentage, E is exposure value and R is recovery rate.
Credit Risk Bank operations involve sanctioning of loans and advances to customers for variety of purposes. These loans may be business loans for short or long term commitments and consumer finance for
More informationTraffic Prediction in Wireless Mesh Networks Using Process Mining Algorithms
Traffic Prediction in Wireless Mesh Networks Using Process Mining Algorithms Kirill Krinkin Open Source and Linux lab Saint Petersburg, Russia kirill.krinkin@fruct.org Eugene Kalishenko Saint Petersburg
More informationR&I Rating Methodology by Sector
R&I Rating Methodology by Sector Electric Wires and Cables December 3, 2013 R&I applies this rating methodology to electric wire and cable manufacturers that position three sectors "electric wires and
More informationChapter 4. Money, Interest Rates, and Exchange Rates
Chapter 4 Money, Interest Rates, and Exchange Rates Preview What is money? Control of the supply of money The willingness to hold monetary assets A model of real monetary assets and interest rates A model
More informationAgricultural E-Commerce Sites Evaluation Research
International Journal of Business and Social Science Vol. 4 No. 17 [Special Issue December 2013] Agricultural E-Commerce Sites Evaluation Research Hang Liu Yuming Wang Kui Xie College of Management Shanghai
More informationStudy on Human Performance Reliability in Green Construction Engineering
Study on Human Performance Reliability in Green Construction Engineering Xiaoping Bai a, Cheng Qian b School of management, Xi an University of Architecture and Technology, Xi an 710055, China a xxpp8899@126.com,
More informationPrediction Model for Crude Oil Price Using Artificial Neural Networks
Applied Mathematical Sciences, Vol. 8, 2014, no. 80, 3953-3965 HIKARI Ltd, www.m-hikari.com http://dx.doi.org/10.12988/ams.2014.43193 Prediction Model for Crude Oil Price Using Artificial Neural Networks
More informationStudy on the Comprehensive Evaluation of the Financial Core Competitiveness for the Listed Companies in Chinese Steel Industry
Study on the Comprehensive Evaluation of the Core Competitiveness for the Listed Companies in Chinese Industry Yanhui Wang, Yajun Guo & Yanqing Zhuang School of Business Administration Northeastern University
More informationfocus Managing Long-Term Assets OVERVIEW Learning Objectives By the end of this chapter, you should be able to:
8 Managing Long-Term Assets Learning Objectives By the end of this chapter, you should be able to: focus Distinguish between long-term and shortterm assets. Explain how depreciation relates to the valuation
More informationThe Compound Operations of Uncertain Cloud Concepts
Journal of Computational Information Systems 11: 13 (2015) 4881 4888 Available at http://www.jofcis.com The Compound Operations of Uncertain Cloud Concepts Longjun YIN 1,, Junjie XU 1, Guansheng ZHANG
More informationTHE IMPACT OF MACROECONOMIC FACTORS ON NON-PERFORMING LOANS IN THE REPUBLIC OF MOLDOVA
Abstract THE IMPACT OF MACROECONOMIC FACTORS ON NON-PERFORMING LOANS IN THE REPUBLIC OF MOLDOVA Dorina CLICHICI 44 Tatiana COLESNICOVA 45 The purpose of this research is to estimate the impact of several
More informationResearch of Enterprise Accounting Information System Internal Control Based on ERP. Huiyin Zheng
International Conference on Management Science, Education Technology, Arts, Social Science and Economics (MSETASSE 2015) Research of Enterprise Accounting Information System Internal Control Based on ERP
More informationWORKING CAPITAL MANAGEMENT
WORKING CAPITAL MANAGEMENT What is Working Capital Working capital management is the set of activities that are required to run day to day operations of the business to ensure that cash is adequate to
More informationAN IMPROVED CREDIT SCORING METHOD FOR CHINESE COMMERCIAL BANKS
AN IMPROVED CREDIT SCORING METHOD FOR CHINESE COMMERCIAL BANKS Jianping Li Jinli Liu Weixuan Xu 1.University of Science & Technology of China, Hefei, 230026, P.R. China 2.Institute of Policy and Management
More informationArtificial Neural Network and Non-Linear Regression: A Comparative Study
International Journal of Scientific and Research Publications, Volume 2, Issue 12, December 2012 1 Artificial Neural Network and Non-Linear Regression: A Comparative Study Shraddha Srivastava 1, *, K.C.
More information2. Financial management:
2. Financial management: Meaning, scope and role, a brief study of functional areas of financial management. Introduction to various FM tools: ratio analysis, fund flow statement, cash flow statement.
More informationChapter 14. Preview. What Is Money? Money, Interest Rates, and Exchange Rates
Chapter 14 Money, Interest Rates, and Exchange Rates Slides prepared by Thomas Bishop Copyright 2009 Pearson Addison-Wesley. All rights reserved. Preview What is money? Control of the supply of money The
More informationCorporate Credit Analysis. Arnold Ziegel Mountain Mentors Associates
Corporate Credit Analysis Arnold Ziegel Mountain Mentors Associates I. Introduction The Goals and Nature of Credit Analysis II. Capital Structure and the Suppliers of Capital January, 2008 2008 Arnold
More informationARTIFICIAL NEURAL NETWORKS FOR ADAPTIVE MANAGEMENT TRAFFIC LIGHT OBJECTS AT THE INTERSECTION
The 10 th International Conference RELIABILITY and STATISTICS in TRANSPORTATION and COMMUNICATION - 2010 Proceedings of the 10th International Conference Reliability and Statistics in Transportation and
More informationThe Study of Working Capital Strategies in Life Cycle of Companies
2013, World of Researches Publication Ac. J. Acco. Eco. Res. Vol. 2, Issue 4, 77-88, 2013 Academic Journal of Accounting and Economic Researches www.worldofresearches.com The Study of Working Capital Strategies
More informationResearch on Operation Management under the Environment of Cloud Computing Data Center
, pp.185-192 http://dx.doi.org/10.14257/ijdta.2015.8.2.17 Research on Operation Management under the Environment of Cloud Computing Data Center Wei Bai and Wenli Geng Computer and information engineering
More informationOverseas Investment in Oil Industry and the Risk Management System
Overseas Investment in Oil Industry and the Risk Management System XI Weidong, JIN Qingfen Northeast Electric Power University, China, 132012 jelinc@163.com Abstract: Based on risk management content,
More informationBehavior Model to Capture Bank Charge-off Risk for Next Periods Working Paper
1 Behavior Model to Capture Bank Charge-off Risk for Next Periods Working Paper Spring 2007 Juan R. Castro * School of Business LeTourneau University 2100 Mobberly Ave. Longview, Texas 75607 Keywords:
More informationBankersHub.com December 2014 Newsletter Page - 1
BankersHub.com December 2014 Newsletter Page - 1 Newsletter Article December, 2014 A NEW WAY TO CALCULATE THE CUSHION Editorial Content by Paul Sanchez, CPA, CBA, CFSA, Reprinted with permission from November
More informationUPS battery remote monitoring system in cloud computing
, pp.11-15 http://dx.doi.org/10.14257/astl.2014.53.03 UPS battery remote monitoring system in cloud computing Shiwei Li, Haiying Wang, Qi Fan School of Automation, Harbin University of Science and Technology
More informationData Mining Solutions for the Business Environment
Database Systems Journal vol. IV, no. 4/2013 21 Data Mining Solutions for the Business Environment Ruxandra PETRE University of Economic Studies, Bucharest, Romania ruxandra_stefania.petre@yahoo.com Over
More information6.2.8 Neural networks for data mining
6.2.8 Neural networks for data mining Walter Kosters 1 In many application areas neural networks are known to be valuable tools. This also holds for data mining. In this chapter we discuss the use of neural
More informationMany members will be in some way involved with the control of Working Capital and its influence upon business success.
Working Capital Control, Philip E Dunn Many members will be in some way involved with the control of Working Capital and its influence upon business success. Working capital is a key element in business
More informationIMPLEMENTATION NOTE. Validating Risk Rating Systems at IRB Institutions
IMPLEMENTATION NOTE Subject: Category: Capital No: A-1 Date: January 2006 I. Introduction The term rating system comprises all of the methods, processes, controls, data collection and IT systems that support
More informationFuzzy logic decision support for long-term investing in the financial market
Fuzzy logic decision support for long-term investing in the financial market Abstract This paper discusses the use of fuzzy logic and modeling as a decision making support for long-term investment decisions
More informationPerformance Evaluation On Human Resource Management Of China S Commercial Banks Based On Improved Bp Neural Networks
Performance Evaluation On Human Resource Management Of China S *1 Honglei Zhang, 2 Wenshan Yuan, 1 Hua Jiang 1 School of Economics and Management, Hebei University of Engineering, Handan 056038, P. R.
More informationHow the small and medium-sized enterprises owners credit features affect the enterprises credit default behavior?
E3 Journal of Business Management and Economics Vol. 3(2). pp. 090-095, February, 2012 Available online http://www.e3journals.org/jbme ISSN 2141-7482 E3 Journals 2012 Short communication How the small
More informationA New Method for Traffic Forecasting Based on the Data Mining Technology with Artificial Intelligent Algorithms
Research Journal of Applied Sciences, Engineering and Technology 5(12): 3417-3422, 213 ISSN: 24-7459; e-issn: 24-7467 Maxwell Scientific Organization, 213 Submitted: October 17, 212 Accepted: November
More information1 Define Management. Explain Mintzberg Managerial Roles. 12M
Question Paper Code :GMB11T01 MANAGEMENT AND ORGANIZATIONAL BEHAVI0R 1 Define Management. Explain Mintzberg Managerial Roles. 2 Define Social Responsibility. Explain the Arguments for and against Social
More informationSpecifics of national debt management and its consequences for the Ukrainian economy
Anatoliy Yepifanov (Ukraine), Vyacheslav Plastun (Ukraine) Specifics of national debt management and its consequences for the Ukrainian economy Abstract This article is about the specifics of the national
More informationAnalysis of Inventory Management in China Enterprises
Analysis of Inventory Management in China Enterprises JIAO Jianling, LI Kefei School of Accounting, Hebei University of Economics and Business, China, 050061 jeanjiao@tom.com Abstract: Inventory management
More informationForecasting Trade Direction and Size of Future Contracts Using Deep Belief Network
Forecasting Trade Direction and Size of Future Contracts Using Deep Belief Network Anthony Lai (aslai), MK Li (lilemon), Foon Wang Pong (ppong) Abstract Algorithmic trading, high frequency trading (HFT)
More informationFinancial Analysis of Real Estate Enterprises: A Case Study of Vanke
International Business and Management Vol. 9, No. 1, 2014, pp. 74-78 DOI:10.3968/5469 ISSN 1923-841X [Print] ISSN 1923-8428 [Online] www.cscanada.net www.cscanada.org Financial Analysis of Real Estate
More informationLIQUIDITY RISK MANAGEMENT GUIDELINE
LIQUIDITY RISK MANAGEMENT GUIDELINE April 2009 Table of Contents Preamble... 3 Introduction... 4 Scope... 5 Coming into effect and updating... 6 1. Liquidity risk... 7 2. Sound and prudent liquidity risk
More informationDesign and Implementation of Supermarket Management System Yongchang Rena, Mengyao Chenb
4th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering (ICMMCCE 2015) Design and Implementation of Supermarket Management System Yongchang Rena, Mengyao Chenb College
More informationDesign on Emergency Dispatch and Command System of Urban Rail Transit 1
Design on Emergency Dispatch and Command System of Urban Rail Transit 1 Wang Hua The School of Management The College of Urban Rail Transit Shanghai University of Engineering Science Shanghai China Liu
More information