Journal of Computer and Communcatons, 2016, 4, 1-11 http://www.scrp.org/journal/jcc ISSN Onlne: 2327-5227 ISSN Prnt: 2327-5219 The Credt Rsk Assessment Model of Internet Supply Chan Fnance: Mult-Crtera Decson-Makng Model wth the Prncple of Varable Weght Yuelang Su, Baoyu Zhong School of Busness, South Chna Unversty of Technology, Guangzhou, Chna How to cte ths paper: Su, Y.L. and Zhong, B.Y. (2016) The Credt Rsk Assessment Model of Internet Supply Chan Fnance: Mult-Crtera Decson-Makng Model wth the Prncple of Varable Weght. Journal of Computer and Communcatons, 4, 1-11. http://dx.do.org/10.4236/jcc.2016.416001 Receved: November 10, 2016 Accepted: December 4, 2016 Publshed: December 9, 2016 Copyrght 2016 by authors and Scentfc Research Publshng Inc. Ths work s lcensed under the Creatve Commons Attrbuton Internatonal Lcense (CC BY 4.0). http://creatvecommons.org/lcenses/by/4.0/ Open Access Abstract The characterstcs of the fnancng model are frstly analyzed when the e-commerce enterprses partcpate n the supply chan fnance. Internet supply chan fnance models are dvded nto three categores wth the standard of whether the Electronc commerce enterprses provde funds for small and medum enterprses nstead of banks. And then we further study the fnancng process and the functons of the e-commerce platform wth specfc examples. Fnally, combned wth the characterstcs of the supply chan fnance model, we set up a small and medum enterprses credt evaluaton model based on the prncple of varable weght wth ts dynamc data. At the same tme, a mult tme ponts and mult ndcators decson-makng method based on the prncple of varable weght s proposed and a specfc example s presented. In ths paper, the Mult-crtera decson-makng model wth the prncple of varable weght has been used two tmes. At last, a typcal case has been analyzed based on ths model wth a hgher accuracy rate of credt rsk assessment. Keywords Credt Rsk Assessment Model, Mult-Crtera Decson-Makng Model, Varable Prncple 1. Introducton Internet plus, as a new model of the development of the Internet, s a new form of the socal development. Internet plus means that Internet and tradtonal ndustry mx together deep and a new form of development s created usng Internet nformaton DOI: 10.4236/jcc.2016.416001 December 9, 2016
technology and the Internet platform, etc. [1]. On the background of the Internet, based on the e-commerce platform, supply chan fnance also has a new development form. On December 10th 2013, a Jngdong s Internet fnancal product, Jng BaoBe, sets off a wave of supply chan fnance agan [2] [3]. Be Jng Bao s a fnancng model based on the purchasng, sales, fnance and other data of supplers wthout a guarantee or collateral. Jngdong analyses and determnes a suppler s loan capacty and credt rsk accordng to the suppler s regstraton nformaton, purchasng data, sales data and network behavor data, etc. [4]. On the one hand, the Internet has brought more possbltes for the development of supply chan fnance. On the other hand, the accuracy of credt rsk assessment of small and medum szed enterprses s also more and more mportant. Based on ths, ths paper analyses the change of the fnancng mode of the supply chan fnance based on the e-commerce platform on the background of the Internet. At the same tme, standng n the perspectve of the e-commerce platform, how to use dynamc network data to evaluate the credt rsk of small and medum fnancng customers s proposed. 2. Internet Supply Chan Fnance Mode 2.1. The Frst Supply Chan Fnance Fnancng Mode Based on E-Commerce Platform In the frst mode of supply chan fnance, the e-commerce platform not only provdes tradng platform, but also drectly partcpates n the supply chan as the core enterprse of the supply chan. At the same tme, e-commerce platform corporates wth the bank, provdng guarantee credt for the small and medum enterprse of captal shortage [5]. The bggest dfference between tradtonal and Internet supply chan fnance s that the transacton and fnancng process of all enterprses n the whole supply chan are completed on lne. The typcal e-commerce platform of ths model s the Jngdong Mall. Frst of all, the electronc commerce enterprse orders products from upstream suppler who wll provde products accordng to the orders. Next, as the core enterprse wth a more powerful poston, such as Jngdong Mall, the e-commerce platform does not take drect payment but opens acceptance bll to the upstream suppler and promses to pay after a certan perod. Then, the e-commerce platform sales the products onlne. Due to the shortage of funds, upstream suppler has to apply to the bank for fnancng loans, pledgng order and acceptance blls from the electronc commerce enterprse. After verfyng the relevant order nformaton, the e-commerce platform makes guarantees to the bank so that bank loans to upstream the suppler. After the entre sales season, the suppler repays the loan after recevng order recevables from the electronc commerce enterprse. Fgure 1 shows the process of the frst supply chan fnance fnancng mode. Compared to the tradtonal supply chan fnance, banks wll no longer only assess the fnancal condton and collateral of the fnancng enterprse, but also all data on the e-commerce platform. On the bass of more data, the bank can analyze the fnancal condton of fnancng enterprses, procurement, sales, etc. Consderng the performance of the whole supply chan, ncludng the comprehensve ablty of upstream and 2
Fgure 1. The frst supply chan fnance fnancng mode. downstream companes, supply chan operatons, etc., banks can accurately and effectvely determne the loan capacty and credt rsk of fnancng enterprses, whch effectvely reduce the rsk of bank loans [6]. 2.2. The Second Supply Chan Fnance Fnancng Mode Based on E-Commerce Platform In the second mode of supply chan fnance, the e-commerce platform does not drectly partcpate n the supply chan, but provdes a tradng platform to the upstream supplers and downstream retalers or customers. However, the e-commerce platform stll grasp most of the nformaton n the supply chan. Because of that, the e-commerce platform can provde fnancng servces for small and medum szed enterprses by establshng a loan company or applyng for a bankng lcence [7]. The electronc commerce enterprse provdes a tradng platform for the tradng enterprses nstead of drectly partcpatng n the supply chan. Frst of all, downstream enterprse orders products from the upstream suppler. Then the suppler provdes products for the downstream enterprse accordng to order. And then the downstream enterprse opens an acceptance bll, promsng the suppler to pay after a certan perod of tme, whch becomes accounts recevable. In ths process, e-commerce enterprse does not partcpate n the transacton, but t can get the tradng behavor nformaton and logstcs nformaton, etc. of the two sdes of the transacton. After the comprehensve consderaton of the fnancal stuaton of the fnancng enterprse and onlne transacton data, the electronc commerce enterprse assesses the credt rsk level of the fnancng enterprse n the supply chan. The electronc commerce enterprse controls the rsk by accurately assessng the ablty and the wllngness of the enterprse to repay. After that, the electronc commerce enterprse provdes dfferent rates of fnancng products for the fnancng enterprses accordng to the credt rsk level. Enterprses wth a lower level of credt rsk can be offered unsecured fnancng servces wth a lower nterest rate. On the other hands, the electronc commerce enterprse may offer fnancng servces wth some collateral for the enterprse whose credt rsk level s hgh. When 3
facng the fnancng dffcultes, the enterprse can apply for fnancng applcaton to the electronc commerce enterprse that can quckly provde the correspondng servces. Fgure 2 shows the process of the second supply chan fnance fnancng mode. In the second mode of supply chan fnance, there s no bank, whch s dfferent from the frst mode of supply chan fnance. The electronc commerce enterprse replaces the bank to provde the small and medum-szed enterprses wth the fnancng servce. The electronc commerce enterprse establshes a rch database and credt records of the enterprses on the e-commerce platform and provdes fnancng servces for customers wth fnancng dffcultes on the platform. In ths knd of mode of supply chan, t s very mportant for electronc commerce enterprses to assess the credt rsk level of the fnancng enterprses. 2.3. The Thrd Supply Chan Fnance Fnancng Mode Based on E-Commerce Platform In ths secton, we analyze the thrd supply chan fnance fnancng mode that s the combnaton of the two modes of supply chan fnance analyzed above. But t s dfferent from the two. In the thrd supply chan fnance fnancng mode, the electronc commerce enterprse s the core enterprse n the supply chan, who orders products from the upstream suppler and sales to the downstream enterprses. Besdes, as a fnancal nsttuton wth a strong captal, the electronc commerce enterprse loans to the enterprses wth a shortage of captal n the supply chan and earn the nterest [8]. Fgure 3 shows the process of the thrd supply chan fnance fnancng mode. 3. The Model The credt rsk of small and medum-szed fnancng enterprses s relatvely hgh due to shortage of ts own funds and weak comprehensve ablty. So the credt rsk assessment s partcularly mportant. In the Secton 2, we analyzed the three knds of Internet supply chan fnance mode based on the Internet. In ths secton, from the perspectve Fgure 2. The second supply chan fnance fnancng mode. 4
Fgure 3. The thrd supply chan fnance fnancng mode. of electronc busness enterprse, we buld the credt rsk assessment ndcators combned wth the characterstcs of Internet supply chan fnancng mode and ts platform data. When evaluatng the credt rsk of the fnancng enterprses n the supply chan, mult ndcator decson problem arses. At the same tme, due to the real-tme nature of Internet data, the ndcator state value wll change wth tme. Based on ths, ths paper establshes a Mult-crtera decson-makng model based on varable weght [9] [10]. 3.1. A Varable Weght Model wth Multple Tme Ponts of Any Indcator In the selecton of the mpact ndcator of small and medum enterprses n supply chan fnancng credt evaluaton, there are some ndcator state values changng over tme and the nformaton value decayng. In order to determne the comprehensve functon of the ndcator n dfferent tme, we consder usng the varable weght theory. Next, excted varable state vectors s ntroduced [11]. Gven mappng [ 0,1] m m S: [ 0,1] such that X S( X) = ( S1( X), S2( X),, Sm ( X) ), where S [ 0,1] m X = [ 0,1]. S( X) = ( S1( X), S2( X),, Sm ( X) ) s called excted varable state vectors f S satsfes the followng axoms 1) S( X) Sj ( X) when x xj, 2) S( X) = S( x1, x2,, xm) s contnuous on each x 3) For any constant weght vector, w0 = ( w1, w2,, wm ), there s a varable state vector w0 * S( X) w( X) = (1) m ws X = 1 Assumng that there are N ndcators, f = ( f1, f2,, fn ), whose values changng f n M tme ponts are y ( y, y,, y ) over tme. The values of M ndcators = 1 2 M, where y s the closest state value from the current tme. Gven the constant M 5
weght vector w0 ( w1, w2,, wm ) S ( y ) ( S 1( y ), S2( y ),, SM ( y )) =, the varable state vector = can be defned as yj Sj ( y 1, y2,, ym ) = j = 1,2,, M (2) M j+ 1 It can be proved that the varable state vectors S ( y, y,, y ) j 1 2 M satsfes the defned condtons of excted varable state vectors. So the value of all varable state vectors n dfferent tme ponts w can be defned w0 * S ( 1 1, 2 2,, y ws y ws y w MSM ( y) ) w( y) = = (3) M M ws y ws y j= 1 j j j= 1 j j Calculate the values of the comprehensve functon of all ndcatores n dfferent tme ponts whch are the Hadamard product of varable vectors and state values, y = w y y (4) j Fnally, the state values of all evaluaton ndcators can be defned as yy changes by tme x = yy doesn't change by tme (5) 3.2. A Varable Weght Model wth Multple Indcators The state value of ndcator s dfferent, as well as the mportance of dfferent ndcator. In tradtonal, constant weght varable s usually used to determne the mportance of ndcator. In ths paper, the weght of ndcator s also adopted to the varable weght theory n order to study the nfluence of the state value on the ndcator. Satsfacton Prncple s ntroduced [12]. For a mult crtera decson makng problem, assumng a decson set U, an ndcator set related decson makng problem f = ( f1, f2,, fm ) and a constant weght vector of the ndcators, w= ( w1, w2,, wm ). The value of the ndcator f s X = ( x1, x2,, xm ) and m 0 s the number of satsfacton. For any choce u U, the choce u s the satsfacton choce f there are more than m 0 ndcators who are satsfactory. Indcator x s satsfactory f x > a where a s the basc number whose values s the standard gven by decson makers. Assumng that there are m small and medum szed enterprses p = ( p1, p2,, pm ) and N ndcators that measure the credt rsk of small and medum szed enterprses. For any p t n p = ( p1, p2,, pm ), assumng that the value of N ndcators s xt = ( xt1, xt 2,, xtn ) and the number of satsfacton s m 0. In order to determne the constant weght vector more objectvely, ths paper uses the analytc herarchy process to determne the value of the constant weght vector w 0 = ( w 1, w 2,, w N ). The state value of all ndcators are standardzed by Z-score method and then the basc number can be a = ( 0,0,,0). Accordng to Lu Chang (2014, S x = S x, S x,, S x can be defned as [13]), varable state vector t ( t ) ( t1( t ) t 2( t ) tn ( t )) θ x e tj xtj 0 Stj ( xt1, xt 2,, xtn ) = (6) 1 xtj < 0 6
η t+ 1 t 0 where θ s the excted factor, θ = η µ ( ξ m0 ) µ ( t) ξ, =, = 0 t < 0, ξ s the number of satsfacton ndcators that the number of satsfed condton xtj 0 N 1 t 0 and ξ = j= 1ν ( xtj ), ν ( t) = 0 t < 0 It can be proved easly that Stj ( xt1, xt 2,, xtn ) satsfes all condtons of the defnton excted varable state vectors and then the value of the varable weght vector of all supplers w t can be calculated w 0 * S ( 1 1, 2 2,, t x ws xt ws x t t w NS N ( xt) ) wt ( xt) = (7) N N ws x ws x j= 1 j tj t j= 1 j tj t Fnally, calculate the values of the comprehensve functon of all small and medum szed enterprses n dfferent ndcators whch are the Hadamard product of varable vectors and state values, x = w x x (8) t t t t Equaton (8) gves the fnal scores of all small and medum szed enterprses. 4. Case Analyss 4.1. Index Desgn and Data Descrpton Based on the characterstcs of the supply chan on the electronc platform and the lterature of supply chan, the credt rsk assessment ndex s constructed as Table 1. Accordng to the credt rsk assessment ndexes, ths paper collects the data through the questonnare to the merchant and the electronc busness platform. Qualtatve ndexes take 5 ponts system score, and quanttatve ndexes are from the electronc busness platform hstory records. There were 13 vald questonnares returned. Therefore, Table 1. The credt rsk evaluaton ndex of nternet supply Chan Fnance. Frst-grade ndex Second-grade ndex Index descrpton Credt status of the fnancng enterprse B1 Fnancng project status B2 Operaton status onlne B3 Regstraton nformaton X1 Fnancal dsclosure qualty X2 Sales proft margn X3 Purchasng data X4 Sales data X5 Returned merchandse data X6 Onlne operaton level X7 Informatzaton level X8 The basc nformaton of a fnancng enterprse when t s regstered on the platform Fnancal statement audt and nformaton dsclosure Sales proft/sales revenue Project related purchasng data Project related sales data Whether there s a record of returned merchandse The age of onlne operaton of the fnancng enterprse, etc. Onlne busness condtons 7
a Mult-crtera decson-makng model can be constructed wth 13 fnancng enterprses p = ( p1, p2,, p13 ) and 8 credt rsk assessment ndexes f ( f1, f2,, f8) Some ndexes have three months of data y = ( y, y, y ). 1 2 3 4.2. A Varable Weght Model wth Multple Tme Ponts of Any Indcator =. In the collected data, some of them change wth tme. Sales proft margn X3, Purchasng data X4, Sales data X5 and Returned merchandse data X6 need to be calculated the values of the comprehensve functon wth three months record. Gven a constant weght vector w0 = ( w1, w2, w3) = (0.2,0.3,0.5), the comprehensve functon value of any ndcator n three months can be calculated by Equaton (5). Besdes, ths paper uses the analytc herarchy process to determne the value of the constant weght vector w 0. Accordng to the relatve mportance of each ndex, the judgment matrx of the herarchcal structure s determned. The relatve mportance between each other of the Frst-grade ndex can be expressed as a matrx A and the Second-grade ndex one can be expressed as a matrx B, C, D 1 3 5 1 1 3 1 0.2 3 1 3 A= 1 5 B = 1 3 C = 1 5 D = 1 1 1 1 The relatve weght and combned weght of ndex can be determned by MATLAB accordng the judgment matrx. The relatve weght and combnaton weght are shown as Table 2. 4.3. A Varable Weght Model wth Multple Indcators Accordng to varable weght theory, when an ndex meets the requrements of fnancal nsttutons, ncrease the weght of the ndex to ndcate the mpact of the ndex, or to reduce ts weght. Constant weght vector w 0 = ( w1, w2, w3, w4, w5, w6, w7, w8) = ( 0.25, 0.25, 0.107, 0.064, 0.208, 0.031, 0.067, 0.022 ), can be obtaned from Table 2 by analytc herarchy process. By Equaton (6), the varable Table 2. The relatve weght and combnaton weght of ndex by AHP. B1 (0.067) B2 (0.303) B3 (0.090) Combned weght X1 0.412 0.000 0.000 0.250 X2 0.412 0.000 0.000 0.250 X3 0.176 0.000 0.000 0.107 X4 0.000 0.211 0.000 0.064 X5 0.000 0.686 0.000 0.208 X6 0.000 0.102 0.000 0.031 X7 0.000 0.000 0.750 0.067 X8 0.000 0.000 0.250 0.022 8
weght vectors of each ndex of the 13 fnancng enterprses can be obtaned. Varable weght vector of each ndex of sample fnancng enterprse are shown as Table 3. By Equaton (8), the fnal scores of 13 small and medum szed enterprses are calculated. Take P as a boundary value. When P s larger, the credt rsk degree of the fnancng enterprse s lower; when P s smaller, the credt rsk of the fnancng enterprse s hgher. The values are gven as Table 4. The fnal score values and rsk assessment degrees of the 13 fnancng enterprses based on Mult-crtera decson-makng (MID) model wth the prncple of varable weght and Analytc herarchy process (AHP) model are shown as Table 5. 5. Concluson The credt rsk of small and medum-szed fnancng enterprses s relatvely hgh due to shortage of ts own funds and weak comprehensve ablty. In tradtonal supply chan fnance, when evaluatng the credt level of small and medum szed enterprses, banks often take the analyss of the fnancal data of small and medum-szed enterprses, and so on. In ths paper, from the perspectve of electronc busness enterprse, we buld the credt rsk assessment ndcators combned wth the characterstcs of Internet supply chan fnancng mode and ts platform data. In ths paper, the credt rsk assessment ndex s constructed through analyss of the characterstcs of the fnancng model and the change of the model when the Electronc commerce enterprse partcpatng n the Table 3. Varable weght vector of each ndex of sample fnancng enterprse. Sample w1 ( x t ) w2 ( x t ) w3 ( x t ) w4 ( x t ) w5 ( x t ) w6 ( x t ) w7 ( x t ) w8 ( x t ) P1 0.190 0.225 0.154 0.089 0.206 0.011 0.121 0.005 P2 0.250 0.250 0.107 0.064 0.208 0.031 0.067 0.022 P3 0.250 0.250 0.107 0.064 0.208 0.031 0.067 0.022 P4 0.252 0.298 0.087 0.028 0.273 0.014 0.040 0.007 P5 0.146 0.245 0.233 0.084 0.158 0.018 0.095 0.021 P6 0.188 0.315 0.098 0.048 0.204 0.055 0.064 0.027 P7 0.250 0.250 0.107 0.064 0.208 0.031 0.067 0.022 P8 0.250 0.250 0.107 0.064 0.208 0.031 0.067 0.022 P9 0.179 0.305 0.085 0.106 0.195 0.022 0.091 0.016 P10 0.250 0.250 0.107 0.064 0.208 0.031 0.067 0.022 P11 0.565 0.170 0.043 0.059 0.109 0.012 0.027 0.015 P12 0.163 0.270 0.151 0.092 0.175 0.047 0.080 0.023 P13 0.250 0.250 0.107 0.064 0.208 0.031 0.067 0.022 Table 4. The fnal score boundary value and rsk degree. P P 1 0 P 1 1 P 0 2 P 1 P 2 rsk degree 1 2 3 4 5 9
Table 5. The fnal score values and rsk assessment degrees of the 13 fnancng enterprses. The score based on MID Rsk degree predcton based on MID The score based on AHP Rsk degree predcton based on AHP Rsk degree P1 1.769 1 1.630 1 1 P2 0.549 3 0.721 3 3 P3 1.557 4 1.352 4 4 P4 1.392 1 1.384 1 1 P5 0.523 2 0.214 2 2 P6 0.256 2 0.022 2 3 P7 0.615 3 0.762 3 3 P8 0.290 3 0.027 2 3 P9 0.043 2 0.004 3 2 P10 0.489 3 0.679 3 3 P11 0.613 2 0.480 2 2 P12 0.454 2 0.181 2 2 P13 0.238 3 0.420 3 3 supply chan fnance. At the same tme, the ndex state value wll change wth tme due to the real-tme nature of Internet data. Then a mult-crtera decson-makng model based on the prncple of varable weght was establshed combned wth the characterstcs of Internet supply chan fnancng model, complexty and dynamc of data and the credt rsk assessment ndex. Fnally, based on the case valdaton, through comparng wth the results of the tradtonal analytc herarchy process, t s proved that the Mult-crtera decson-makng model have hgher accuracy rate of credt rsk assessment for fnancng enterprses. Acknowledgements Ths research was supported by the Fundamental Research Funds for the Central Unverstes (2015ZKYJZX02) and Guangzhou Fnancal Servces Innovaton and Rsk Management Research Base. References [1] Edtoral Department of Chna Constructon Informaton (2015) To Meet the Internet plus Era. Chna Constructon Informaton, 6, 8-9. [2] Edtoral Department of Era of Fnancal Scence and Technology (2014) Rcoh (Chna) Color Management Expert Awarded G7 Experts Certfcaton. Fnancal Technology Tme, 1, 8. [3] Mn, W.W. and Luo, L. (2015) Innovaton Is the Only Way Out An Intervew wth Yao Nasheng, Vce Presdent of Jngdong Fnance. Modern Bankers, 3, 90-93. [4] Edtoral Department of Era of Fnancal Scence and Technology (2014) Chna s Frst Mo- 10
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