Research on Risk of Supply Chain Finance of Small and Medium-Sized Enterprises Based on Fuzzy Ordinal Regression Support Vector Machine

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1 Internationa Journa of Business and Management Vo. 7, No. 8; Apri 202 Research on Risk of Suppy Chain Finance of Sma and Medium-Sized Enterprises Based on Fuzzy Ordina Regression Support Vector Machine Ying Chen Sydney Institute of Language & Commerce, Shanghai University Chengzhong road 20, Jiading district, Shanghai, China E-mai: Received: January, 202 Accepted: February 4, 202 Pubished: Apri 6, 202 doi:0.5539/ibm.v7n8p5 URL: Abstract This artice expained the financia innovation service product - fundamenta mode of suppy chain finance, and expored the risk of suppy chain finance. Fuzzy ordina regression support vector machine is used to anaysis the risk of suppy chain finance by the index system of risk assessment, and the resuts were effective and coud be improved in the future. Keywords: Suppy chain finance, Risk, SME, Fuzzy ordina regression support vector machine. Introduction Since the 990s, market competition is no onger between the individua enterprises, but is competition between suppy chains. Suppy chain is a concept which refers to the process of commodities from purchasing raw materias, manufacturing to seing. It incudes energy enterprises, manufacture enterprises, commercia enterprises and so on. These enterprises have their own business modes, suppiers and retaiing patterns as we as their derivative suppy chains. Obviousy decentraized suppy chain inevitaby eads to decentraization of financia management and economic resources. As a resut, it is unabe to integrate various resources from suppy chain. Enhancing the efficiency of suppy chain wi definitey resut in request for optimizing economic resources in suppy chain. Ony financia instruments can integrate suppy chain resources. When goods are moving into suppy chain, cash fows are in motion simutaneousy because fows of ogistics and cash fows are inseparabe. There is inaienabe reationship between finance and ogistics. Financia instruments can keep assets moving, reasonaby aocate and restructure cash fow in suppy chain. Thus the issues of competition between suppy chains have changed into how to use finance instruments in suppy chains. Therefore, anayzing the reationship between suppy chains and cash fows has become a crucia question. It is in no more than 30 years since the concept of suppy chain appeared in deveoped countries in Europe and America. It is a shorter history that financia instruments used in suppy chain. Suppy chain finance refers to financia management based on suppy chain. It is intrinsic requirement of market competition as we as the inevitabe outcome of economic deveopment. At present, suppy chain finance has been a new financia product used in increasing number of maor companies and banks. Domestic maor banks have put forward their corresponding soutions. However, in practice, many issues arising in operation have not been given enough attention by researchers, functiona departments and the management. Financia risks arising from suppy chain has received itte attention and rarey researched. However, this is the key to the deveopment of suppy chain finance and to sustainabe and heathy deveopment in goba market. It is aso the practica probem for Chinese government and enterprises. 2 Literature review 2. Literature review on suppy chain finance Since 990s, iterature has focused on suppy chain optimization and improvement of suppy chain efficiency and effectiveness. To be specific, it mainy concerns oint optimization of production, transportation, and inventory of suppy chain. Usuay, confined by the eve of service, the goa of decision-making for optimizing the suppy chain is set to save cost and time, putting structure of cost (incuding transportation costs, Pubished by Canadian Center of Science and Education 5

2 Internationa Journa of Business and Management Vo. 7, No. 8; Apri 202 warehousing costs, order cost, purchase costs, manufacturing costs, inventory costs, out of stock, and other costs), product characteristics (incuding consumabe and dangerous goods etc.), time constraints, different information, the uncertainty characteristics (uncertainty of demand, uncertainty of production, transportation of raw materias as we as the uncertainty of suppy) and other factors into consideration. Methods and toos invoved to gain optimization decision of suppy chain incude ine panning, non-inear programming, dynamic panning, network technoogy and simuation. In 2006 suppy chain finance was first promoted by Shenzhen Deveopment Bank. In recent years the combination of finance and suppy chain has been expored and practiced by many corporations, for instance, Shenzhen Deveopment Bank and Chinese foreign trade transportation (group) corporation, China Construction Bank and Chinese Commodity Storage and transportation Corporation, the Industria and Commercia Bank of China and Sino-trans Group. Foreign banks aso oin the competition of suppy chain finance through various ways, striving for more arge-scae core enterprises as their target customers. To iustrate, Citibank, Hong Kong and Shanghai banking corporation (HSBC), Standard Chartered Bank provide such suppy chain finance service as we. Hans Christian (2009) expained suppy chain finance (SCF) was the inter-company optimization of financing as we as the integration of financing processes with customers, suppiers, and service providers in order to increase the vaue of a participating companies. Lennart Söderberg (200) indicated that there was a strong reationship between suppy chain maturity and suppy chain performance in sma and medium sized enterprises, as we as some reationships between suppy chain maturity and financia performance. And if firms use maturity indicators in the Suppy Chain Operations Reference areas to improve their processes, they wi most ikey achieve positive effects on suppy chain performance and probaby aso on financia performance. 2.2 Literature review on fuzzy support vector machine Qi Wu (200) presented a new version of fuzzy support vector machine (SVM) which can penaize Gaussian noise to forecast fuzzy noninear system. Since there existed some probems of finite sampes and uncertain data in many forecasting probem, the input variabes are described as crisp numbers by fuzzy comprehensive evauation. The resuts of the appication in sae system forecasts confirm the feasibiity and the vaidity of the Fg-SVM mode. Compared with the traditiona mode, Fg-SVM method requires fewer sampes and has better generaization capabiity for Gaussian noise. Min-Yuan Cheng (20) represented the Evoutionary Fuzzy Support Vector Machine Inference Mode for Time Series Data (EFSIMT), an artificia inteigence hybrid system focusing on the management of time series data characteristics which fuses fuzzy weighted support vector machines (weighted SVMs) and a fast messy genetic agorithm (fmga), to predicting cash fow. Simuations performed on historica cash fow data demonstrate the EFSIMT is an effective too for predicting cash fow. Wei-Yuan Cheng (20) proposed an incrementa support vector machine-trained TS-type fuzzy cassifier (ISVM-FC). The ISVM-FC is a fuzzy system that consists of Takagi Sugeno (TS)-type fuzzy rues, compared with fuzzy cassifiers and Gaussian-kerne SVM, which improved training and test times, and reduced memory consumption for cassifier storage without deteriorating the generaization abiity. Fengyi Lin (20) expained a hybrid manifod earning approach mode which combined both isometric feature mapping (ISOMAP) agorithm and support vector machines (SVM) to predict the faiure of firms based on past financia performance data. Anaytic resuts demonstrate that our hybrid approach not ony has the best cassification rate, but aso produces the owest incidence of Type II errors, and is capabe of achieving an improved predictive accuracy and of providing guidance for decision makers to detect and prevent potentia financia crises in the eary stages. Arindam Chaudhuria (20) used a nove Soft Computing too viz., Fuzzy Support Vector Machine (FSVM) to sove bankruptcy prediction probem. Experimenta resuts on FSVM iustrate that it is better capabe of extracting usefu information from corporate data. At present, suppy chain finance has been a new financia product empoyed by an increasing number of maor companies and banks. Domestic maor banks have put forward their corresponding soutions. However, in practice, many issues arising in operation have not been given enough attention by schoars, functiona departments and the management. Financia risks arising from suppy chain have received itte attention and rarey been researched. However, a key to the deveopment of the suppy chain finance and to sustainabe and heathy deveopment in the goba market, suppy chain finance is aso a practica probem facing Chinese government and enterprises. Thus, there is a research gap between commercia banks and other financia institutions to evauate credit risk in suppy chain finance in that suppy chain is combined by core enterprises and many sma and medium enterprises. Commercia banks and other financia institutions shoud provide suitabe enterprises with financia services. Consequenty, it is essentia to design a comprehensive evauation system to categorize sma and medium enterprises. 6 ISSN E-ISSN

3 Internationa Journa of Business and Management Vo. 7, No. 8; Apri Basic mode of suppy chain finance Suppy chain finance is to provide financia services to a reated businesses in suppy chain. As a resut, the suppy chain-reated enterprises receive financia support and grow rapidy, so as to sove the probem of uneven funds distribution and upgrade the entire suppy chain, even the competitiveness of whoe industry. And the commercia banks provide financia services of suppy chain to opened up their own business channe, and even dominate the chain of a reevant financia business enterprises. This innovative mode has brought dramatic improvement in the rationaization of aocating resources and performance to the banks and enterprises on suppy chain. For exampe in 2006, Shenzhen Deveopment Bank integrated resources and provided such financia services as RMB, foreign currencies and integrative off and on shore financia services in fu-chain to chain-oriented industries. Trade financing customers and business voume both had the 50% growth, and that year the tota amount of finance was up to 300 biion, at the same time their ratio of non-performing oans kept beow percent, and the overa ratios of non-performing oans were ony 0.4%. In the process, business cash fow has been ensured, and then doubed saes growth, such as Yongan Corporation in Chongqing, cooperated with Shenzhen Deveopment Bank for three years, their saes increased from 600 miion yuan to 2.5 biion. Despite the Shenzhen Deveopment Bank, Shanghai Pudong Deveopment Bank, Minsheng Bank, Industria and Commercia Bank of China have their respective suppy chain finance programs, but their basic pattern is the same, which is a financia service, with we-known arge-scae manufacturing enterprises as the core, makes fu use of the core upstream and downstream businesses and fixed commercia reationships. This kind of upstream and downstream business reationships arising from ogistics and cash fow removes the obstaces in the ogistics through improvements in cash fow, thus greaty increasing performance in banks and the suppy chain. The chart beow is a comparison between the basic mode of suppy chain in finance and the traditiona mode From Figure, the basic pattern of suppy chain finance is that the bank providing comprehensive financia services to an industry through a singe enterprise or a number of upstream and downstream enterprises in the suppy chain in order to promote and support the operations in these enterprises effectivey and efficienty, thus to buid up commonweath among banks, enterprises and suppy chain to achieve mutuay beneficia co-existence and sustainabe deveopment. Because 80% of enterprises on suppy chain in China are SMEs, with the shortage of cash fows, sma and medium-sized enterprises are not ony the main customers to demand financia support from suppy chain finance but aso the important entry for banks to break into the industria chain. From Figure 2, it can be found that in traditiona mode, the reationship between banks and suppy chain is that the dominant core enterprises take advantage of its strong position to demand for deivery of raw materia suppiers before payments whie they request payment before deivery of goods from whoesaers and retaiers. There are many critica terms from these core enterprises in trading process of deivery, pricing, accounting from the upstream and downstream enterprises, thereby causing tremendous pressure on these enterprises. However the upstream and downstream enterprises are aways sma and medium-sized enterprises. Therefore it is difficut to finance from banks. As a resut, it is very tense for funding chain, causing an imbaance in the whoe suppy chain. The core businesses with arger-scae and stronger competitiveness give more pressure on the funds for upstream and downstream enterprises, and these upstream and downstream enterprises are being affected by the imitations of a kinds of resources and sma-scae and difficut to negotiate with their respective banks individuay to require funds, even the preferentia oan. Therefore, the reasons for financing probem in those sma and medium-sized enterprises are not in the enterprises themseves, because the core businesses in suppy chain have occupied cash fows of sma and medium-sized suppiers and whoesaers, for exampe, the inventory and accounts receivabe owned by the core business is about.5 times of their needs. If these inventory and accounts receivabe coud be used efficienty, it wi sove the financia probems in suppy chain and increase the profit for banks, thus giving rise to the concept of suppy chain finance. For exampe, Guangzhou Branch of Shenzhen Deveopment Bank had found from their practice that the suppiers of energy industry generay did not have fixed assets, but had adequate accounts receivabe. The staff customized a financing soution to sove these enterprises shortage of cash, which pedged accounts receivabe to the bank financing. Shenzhen Deveopment Bank attracted a arge number of deaers. Having estabished the ong-term credit reationships with many suppiers, Shenzhen Deveopment Bank had negotiated with the refineries, taking the refineries as the center and providing cash fows to their raw materias suppiers and imported enterprises or to the distributors seing gasoine, diese, PVC series of petrochemica products. After this, Shenzhen Deveopment Bank and miions of distributors negotiated with the domestic energy giants such as Petro China, Sinopec, CNOOC and so on. Then setting up financia system with these corporations throughout the country, Shenzhen Deveopment Bank had become a dominant bank in the energy fied. Pubished by Canadian Center of Science and Education 7

4 Internationa Journa of Business and Management Vo. 7, No. 8; Apri 202 Nowadays, there were many financia service products in Shenzhen Deveopment Bank, such as short-term oans, banks acceptance, commercia acceptance bi discounting and other products. For specific customer, they aso deveoped a business vote discounting and management, export credit insurance financia products of the extension and expansion of suppy chain finance mode. It not ony heped domestic bank sove the ong-term financing probems of sma and medium-sized enterprises, but aso provided a great dea of new business opportunities for banks. It coud be seen from the basic mode of suppy chain finance that the effect of such a mode of financing is the concentration of much more financia resources toward those core groups of enterprises. In practice, the domestic banks woud usuay enarge the credit of core business by 0% -20% to increase more business through greater credit support to enterprises in suppy chain. These resuted in a series of practica probems. First, if this core group companies had the business inking with 0 banks and each bank provided simiar credit support, the credit for those companies woud be invisiby expanded by 00% -200%; however, these enterprises whether their strength and capacity coud support such a huge credit growth was sti in doubt? Second, how did the banks supervise risks from the tremendous growth in credit? Third, given the ower degree of information technoogy in China, how to review and evauate authenticity of the arge number of trade documents? Fourth, how did we guard against and prevent financia risks and mora risk? Risks of suppy chain finance woud be anayzed beow to tacke these probems. First, the core corporations don t have an adequate understanding of the risks. Because assets management in arge groups in Chinese had often been negected, many groups coud not distinguish between assets management department and investment department. With the ack of assets management rues as we as the shortage of appropriate professiona staff, not enough attention had been paid to suppy chain risk. The financia system in groups, because of their ess sensitivity to market and their shortage of rationa management system, had brought a ot of financia risks. Assets management of suppy chain had caused operating difficuties or bankruptcy to severa domestic companies. Once the financia chain of the core enterprises broke down, it woud bring disaster to the whoe suppy chain. Second, the credit environment was compex. The credit situation in China was very serious. It was not rare to find that the credit is not honored. For exampe, the debtors dared to borrow and use the arge number of money, even dared not to return, a few enterprises owed enrichment and performance to ustified arrears, there were ots of phenomena that scraping debts were paid, deadbeats were meritorious and refused paying debts was ustified. Internationa etter of credit is used to guarantee internationa trade, but there was no such domestic etter of credit in domestic trade. The bi settement of accounts was mosty used in domestic trade. Administrative reguations on domestic etters of credit were announced in 997, which had not been renewed within 0 years. There was ess feasibe pattern for RMB etter of credit in procedure where deposits and withdrawas were processed at any branch of bank. The domestic trade settement acked consistent guarantee that coud be circuated and accepted by a sides, which contributed to the risk in suppy chain finance transactions and the operations. Third, the process and recognition of property rights were compicated and confused. In China, there was ack of uniform standards in transportation and warehousing norms, and many property rights cases appeared frequenty in transaction. The way that Chinese current egisations and reguations dea with such cases was quite confused. It usuay used contract approach, but the contract was ony the evidence of changes in debts, and it was not effective enough to bear evidence to iustrate the effect of changes in property rights occurred in circuation. Because it was difficut to obtain the corresponding guarantee, the banks coud hardy exercise contro over the property rights process, resuting in vunerabiities inherent in suppy chain management of financia risks. 4. Research methodoogy Based on the above anaysis, in order to prevent possibe risks, the key was to estabish a nationa credit management system and improve the formuation of standardization of financia instruments in trading process. Prior to that, it was necessary to estabish a reativey unified index system of risk assessment to anaysis risk of suppy chain finance of SME, which incudes industry and market prospect anaysis (nationa industria poicy, oca support poicy, internationa market situation anaysis), financia anaysis (return on equity, inventory turnover, accounts receivabe turnover, saes growth rate), business process anaysis (effective deivery ead-time rate, ordering satisfying rate, production fexibiity, suppy chain added vaue ratio), feedback service anaysis (time of operating circe, customer satisfaction rate, customer hoding rate, eve of member coordination, eve of information sharing ). Thus we coected 336 sma medium-sized companies from the customer database of a commercia bank in 8 ISSN E-ISSN

5 Internationa Journa of Business and Management Vo. 7, No. 8; Apri 202 Zheiang province in China, whose customers were most of the sma and medium sized enterprises in east of China. The one third of these companies did not receive the oans from the bank, because of poor performance, the one third of these companies was the VIP customers of the bank and the rest of them were ordinary customers. And some sma and medium-sized companies did not have enough information, defaut data was 0. And sampe data obtained mosty were quaitative variabes, we shoud use the theory of fuzzy sets proposed in 965 by Zadeh, which has been used for handing fuzzy decision-making probems. The eements of fuzzy sets have degrees of membership. A fuzzy set is a pair (A, m) where A is a set and m: A [0, ].For each x A, m(x) is caed the grade of membership of x in (A, m). For a finite set A = {x xn}, the fuzzy set (A, m) is often denoted by {m (x) / x,..., m (xn) / xn}. Let x A. Then x is caed not incuded in the fuzzy set (A, m) if m(x) = 0, x is caed fuy incuded if m(x) =, and x is caed a fuzzy member if 0 < m(x) <. The set is {x A m(x) > 0} is caed the support of (A, m) and the set {x A m(x) = } is caed its kerne. After cacuation, we changed quantitative variabes into data [0, ], and easiy used in next cacuation. And the seected indicators wi dupicate information, such as tota assets, and debt ratio. Therefore, principa component anaysis is used to dimension reduction anaysis, which obtained variabes through computing process. Because this probem beongs to sma sampe cassification question, it seects support vector machine of muti-cassification agorithm on sma sampe earning. Assigns training set: n n T x, x 2,..., (x, x 2 ) R y x i R, y i Y,-, i,..., () Support vector machine soving muti-cassification probem is to construct a series of probems into two cassifications, and estabish corresponding two cassified machines, to determine which category input x beongs to based on two cassified machines. One versus one method, one versus the rest method, and Crammer-Singer muti-cassification support vector machines. It is seected ordina regression support vector machine, consider that M category of input is sequentia from to M in space Rn, which has identified adacent reationship, that is, cass is the adacent cass of -, +, and cass - and cass + are not adacent cass, and space can be separated by M- parae hyper pane. T 2,..., M, (2) x i i, 2,..., Here, x i is training input, superscript expresses the category of corresponding training, i is the number of th kind training data. The primitive question is: min 2 (3) w w, b 2 s.t. ( w x i ) b,,..., M, i,..., (4) ( w x i ) b,,..., M, i,..., (5) Here b ( b T,..., b M ), b 0, b M According to the training reguations and training set, introduce to sack variabe ( x) M * * M *M T (,...,,...,,...,,,...,,..., ) M M and penaty parameter C>0, primitive question transforms to M convex quadratic programming probem: s.t. And M 2 * min 2 w C ( i i ) w, b, (*) i ( w x i ) b i,,..., M, i,..., * ( w x i ) b i,,..., M, i,..., * i 0, i 0,,..., M, i,..., T b ( b,..., b M ), b 0, b M (6) Pubished by Canadian Center of Science and Education 9

6 Internationa Journa of Business and Management Vo. 7, No. 8; Apri Concusion Using support vector machine to cassify the risk of suppy chain finance of sma and medium-sized companies, according to the experimenta resuts, accuracy rate of training set were 82.6%, 8.3%, 80.5%, accuracy rate of testing set were: 7.3%, 70.9%, 70.4%. (Tabe ) The resuts were effective and coud be improved in the future. For these exceptiona phenomena, it is manuay adusted by artificia expert method in practice, and achieves the better resuts of udgments. Thus, it is certified that we reformuated support vector machine for ordina regression method so that different input points can make different contributions to decide hyper pane, to anayze muti-cassification probems, and divided them into different categories to demonstrate the good performance. The effectiveness of this improved method is verified in muti-cassification of credit rating of sma and medium-sized companies in growth enterprises board. The experiment resuts show that our method is promising and can be used to comprehensive evauation, sequencing probems, and other muti-cassification probems. Our future direction of the research wi focus on how to improve the accuracy of muti-cassification. We beieve that more suitabe parameters and variabes seection wi affect and improve the performance of generaization. Extending the muti-cass cassification to sove other probems is aso our future research work. References Akkermansh, Bogerd P, Vosb. (2004). Virtuous and vicious cyces on the road towards internationa suppy chain management. Internationa Journa of Operation and Production Management, 9(56), Arindam Chaudhuria., & Kaa De. (20). Fuzzy Support Vector Machine for bankruptcy prediction. Appied Soft Computing,, Baptista R. (200). Geographica custer and innovation diffusion. Technoogica Forecasting and Socia Change, 66, C. Scott et a. (20). Guide to Finance in Suppy Chain Management. Guide to Suppy Chain Management, Springer-Verag Berin Heideberg, Fengyi Lin., Ching-Chiang Yeh., & Meng-Yuan Lee. (20). The use of hybrid manifod earning and support vector machines in the prediction of business faiure. Knowedge-Based Systems, 24, Hans-Christian Pfoh., & Moritz Gomm. (2009). Suppy chain finance: Optimizing financia fows in suppy chains. Logistics Research,, Jukka, H., Urbh, P., & Vei-Mattiv. (2004). Risk management processes in suppier networks. Internationa Journa of production Economics, 90, Le Jizi, Liu Chuning. (2006). Custer suppy chain: couping industria custers and suppy chain. Modern Economic Research, 5, 5-9. Lennart Söderberg., & Lars Bengtsson. (200). Suppy chain management maturity and performance in SMEs. Operationa Management Research, 3, Min-Yuan Cheng., & Andreas F.V. Roy. (20). Evoutionary fuzzy decision mode for cash fow prediction using time-dependent support vector machines. Internationa Journa of Proect Management, 29, Qi Wu., & Rob Law. (200). Fuzzy support vector regression machine with penaizing Gaussian noises on trianguar fuzzy number space. Expert Systems with Appications, 37, Raf W. Seifert., & Danie Seifert. (20). Financing the chain. Internationa commerce review,0,, Sheffiy. (200). Suppy chain management under the threat of internationa terrorism. Internationa Journa of Logistics Management, 2, -. Shenzhen Deveopment Bank. (2009). China Europe internationa business schoo, Suppy Chain finance: new finance in new economy. Shanghai far-east pubisher. Suni, c., & Manmohan S. S. (2004). Managing risk to avoid suppy chain breakdown. MIT Soan Management Review, fa, Wang Ling-bin. (2006). Based on information-sharing mechanism for financing the suppy chain risk management study. Shenzhen specia zone economy, 0, Wei-Yuan Cheng., & Chia-Feng Juang. (20). An incrementa support vector machine-trained TS-type fuzzy 20 ISSN E-ISSN

7 Internationa Journa of Business and Management Vo. 7, No. 8; Apri 202 system for onine cassification probems. Fuzzy Sets and Systems, 63, Wu Jun. (2006). Suppy chain risk management in severa important issues. Journa of Management Science in China, 2, -2. Zsdisn G. A. (2003). Manageria Perceptions Suppy Risk. Journa of Suppy Chain Management: A Goba Review of Purchasing and Suppy, winter, Tabe. The experimenta resuts Training set Accuracy rate Testing set The companies with no oans 82.6% 7.3% The ordinary companies 8.3% 70.9% The VIP companies 80.5% 70.4% Accounts receivabe Accounts payabe Inventory (Funds) Matching Suppiers A variety of concessions Core Corporation Support center Distributor/Traders A variety of concessions A Bank oan & a basket financia service Figure. The reationships in suppy chain finance mode between commercia bank and suppy chain enterprises Pubished by Canadian Center of Science and Education 2

8 Internationa Journa of Business and Management Vo. 7, No. 8; Apri 202 Accounts receivabe Accounts payabe Inventory (Funds) Matching suppiers Core Corporation Traders/Distributors Few oans Preferentia oans Few oans B Commercia bank A commercia bank C Commercia bank Figure 2. The traditiona reationship between commercia bank and suppy chain enterprises 22 ISSN E-ISSN