Credit Risk Assessment of Online Shops Based on Fuzzy Consistent Matrix

Transcription

1 Appled Matheatcs & Inforaton Scences An Internatonal Journal 2 NSP 5 (2) (2), 63S-69S Credt Rs Assessent of Onlne Shops Based on Fuzzy Consstent Matrx Yao Yao Insttute of Servce Engneerng, Hangzhou Noral Unversty, 32, Chna Eal address: yyaoexst@hotal.co Receved Jun 8, 2; Revsed Jan 2, 2 Abstract: Despte the fast developent n tradng volue, potental credt rs hndered the developent of e-coerce n eergng econoes. Ths paper studes the credt ratng ndustry and ts applcaton n e-coerce frstly. Then fuzzy consstent atrx, whch aes confor to the consstency of huan decson ang as ts specal property of center-dvson transtvty, s appled to construct a coprehensve credt rs assessent syste. Fuzzy consstent atrx helps to ntegrate ncoparable credt rs ndcators nto one unfed crtera. Fnally, credt rs ranng s provded for onlne shops. Keywords: Credt ratng, onlne shop, fuzzy consstent atrx Introducton Wth ncreasng avalablty of coputers and accessblty of the nternet, E- coerce becoe a boong ndustry, not only n developng countres but also n eergng econoy. Despte the fast developent n tradng volue, lac of regulaton and potental default rs hnder standardzaton of the ndustry and the perfecton of e- coerce aret structure, especally n eergng econoy. The credt rs ssue n onlne shoppng s not suffcently addressed. Asyetrc nforaton proble s ore serous n on-lne shoppng than other fors of coercal actvtes. Credt ratng syste, whch was orgnally used n credt rs assessent n fnancal and banng ndustry, can be ntroduced nto e-coerce ndustry. A coprehensve evaluaton ndcator syste would be necessary n credt ratng. There are any credt rs ndcators, whch dffer treendously and ncoparable. Fuzzy consstent atrx, a scentfc ethod to deal wth ultple objectve decson ang process, would be applcable n constructng the coprehensve evaluaton ndcator syste. Ths paper wll dscuss credt rs assessent of onlne shops wth applcaton of fuzzy consstent atrx. In secton 2 I wll dscuss the selecton of the ndcators n credt

2 Yao Yao 64 ratng; n secton 3 construct the atheatcal odel; n secton 4 gve an exaple; n secton 5 gve soe conclusons. 2 The Indcators of Credt Ratng for Onlne Shops Ths secton wll llustrate credt ratng syste and ts applcablty. Reference to well accepted credt ratng ndcators and consdered specal characters of e-coerce, a set of scentfc ndcators of credt rs of onlne shops wll be wored out. The ost outstandng character of credt ratng s to put all aspects of credt rs nforaton nto one sngle result whch denote a certan credt qualty degree, such as AAA denotes hgh credt qualty or low rs (A.Duff, and S.Eng, 29). Indcators n any credt ratng ethod can be devded nto two types, quattatve or qualtatve. Character, capacty, anageent econoc factors are consdered portant ndcators n any credt ratng syste. Regardless of the orgnal applcaton feld, the a of credt ratng s a copound easure of credt rs, whch applcable n any area, nclude e- coerce. Hence, credt ratng can also be appled n onlne shoppng. Most onlne shops fall nto the category of sall and edu szed corporaton. Large proporton of onlne shops are ndvdual-owned busness. Therefore, the credt ratng for sall fr s ore applcable n on-lne shop credt ratng. Generally speang sall fr has shorter operatng hstory, lted producton varety, less experenced anageent, centralzed ownershp and gnored huan captal nvestent. All the characters above aes sall fr ore senstve to credt rs. However, saller frs are also ore effcent than average, ore flexble and adaptve, ore otvated to nnovaton and ay have soe potentals n certan ndustry. In credt ratng, econoc and ndustral envornent should have hgher weghtng for sall frs. Sall frs are ore senstve to the econoc envornent, such as econoc cycle, natonal ndustral polcy, law odfcaton and geograpghc factors. Sple bussness structure and lted producton of sall copany creased operaton rs. The lfe cycle of ndustry also has ore nfluence on sall copany. Wthout faous brand or sold sales partner, they are ore vulnarable n sunsettng ndustry or hghly copettve ndustry. Moreover, qualtatve easures s ore portant than quanttatve easures n credt ratng for sall and edu szed corporaton. Short hstory, fast change, vast extents of operatng status and lted anageent all these aes fnancal data of sall copany naccsessble and unrelable. Potental proftablty and credt qualty n the long run s ore portant. Inforaton asyetry proble n e-coerce could be effectvely reduced by an ndependent credt ratng aongst dfferent staeholders (M.H.Mllon, and A.V. Thaor, 984). In eergng econoes, ost onlne shops are not oblged to subt fnancal

3 Credt Rs Assessent of Onlne Shops Based on. 65 report, or gve any detaled fnancal or operatonal nforaton. The captal, asset, lablty, and earnngs of ost onlne shops rean unnown to the pubc. Hence, the asyetrc nforaton brngs ore deand for credt rs ratng n e-coerce. Flexblty s another character of onlne shops. Onlne shops draatcally vary n sze. Judgng an onlne shop erely on operatng te or sze can be sleadng. Sall szed shops can covert easly whle econoc condton changes, and not necessarly ore vulnerable to econoc envronent than larger ones. Credt ratng s a copound easureent. In front of tons of ndcator data nforaton fro all aspects, professonals need to ae evaluaton based on ther own experence. There are large nubers of onlne shops eergng everyday. Credt ratng syste needs to assess varous sorts of soft nforaton nto ntegrty (Butler and Rodger, 23). The objectvty and accuracy of credt ratng s hard to derve. Fuzzy consstent atrx can help brng objectvty to ntegrate soft nforaton, and guarantee optal result n ratonal decson-ang on credt ratng. The credt ratng result s usually updatng accordng to the operatonal or econoc condton. (A.Duff, and S.Eng, 29) When credt rs decreased, the ratngs wll update to a better result and vce versa. However, wth nether entry nor ext barrer, short duraton of onlne shops ae accurate forecastng or tely adjustng of credt ratng relatvely dffcult. Most credt nforaton of onlne shops s only good for ex post rather than ex ante analyss. Credt ratng s portant for not only custoers but also busness owners. Credt ratng nforaton can be useful for dfferent staeholders, nclude partes of both buyers and sellers, as well as regulaton organzatons (A.W.A.Boot, T.T.Mlbourn, and A. Schets, 26). Standardzed credt ratng syste could brought stablty and developent nto the onlne aret, credt ratng could reove hestaton of potental custoers, lead sellers to be ore credble and operate ore prudently. The credt ratng ethod actually used n practce based only on anonyous custoer coent onlne, whch s nether objectve nor scentfc. Consderng coonly used ndcators n credt ratng as a source of reference, cobne credt ratng of sall and edu szed copany and the character of onlne shops, I select sx ndcators to splfy the proble, nclude both qualtatve and quanttatve easures. There are anly fve deternants of credt rs, each wth soe ndcators: character (custoer coent on qualty), capacty (operatng te, sales volue), anageent (nventory turnover, delvery servce), and envronent (econoc and ndustral perspectve). 3 Matheatcal Model There are any dfferent types of ndcators n credt ratng, whch are not coparable and dffcult to ntegrate nto one unfed ndcator. Fuzzy consstent atrx s applcable n ult-objectve decson (M.Yao, B.Shen, and J. Luo, 25). Partcularly,

4 Yao Yao 66 the specal propertes of center-dvson transtvty aes fuzzy consstent atrx confor to the consstency of huan decson-ang. Therefore, fuzzy consstent atrx can be appled effectvely n wdespread felds. Suppose there are n objectves (O ), each has a weght of w ( =,, n ). There are solutons A ( =,, ),the optzaton process based on fuzzy consstent atrx s as followng: 3.. Construct the Fuzzy Preferental Relaton Matrx (FRM): We can derve n fuzzy preferental relaton atrces B = ( b ),( =,, n) n whch b =. f under O, A s preferable to A j ; b j =. 5 f A s equally preferable as Aj ; j f A j s preferable to A, then b j =. ; 3.2. Transfor The FRM nto Fuzzy Consstent Matrces: R ( r ) j = j n whch r = ( r r ) j j r = b j j= (3.) (3.2) 3.3. Calculate Relatve Iportance Degree Under Sngle Objectve: Calculate relatve preferental degree s of A under O wth root ethod, s = s s j= (3.3) n whch s = ( r ) (3.4) 3.4. Calculate the Total Relatve Preferental Degree under Mult Objectves: j= j If T T 2 T n w s = T =,then the order of preference would be A A 2 A (3.5) 4 Applcatons, a Sulated Exaple Credt rs ratng s a ult-objectve decson ang process. There are any probles, nclude ncoparablty aongst ndcators and dffculty n quantfcaton. The ndcators and the syste could be ether postve or negatve related. Fuzzy consstent atrx would help solate the subjectvty n the ntegraton of ndcators, and acheve relatvely reasonable credt ratng result.

5 Credt Rs Assessent of Onlne Shops Based on. 67 Sx ndcators (objectves) are selected to assess credt rs of onlne shops, nclude: custoer coent (O ), operatng hstory (O 2 ), sales volue (O 3 ), nventory turnover (O 4 ), delvery servce (O 5 ), econoc and ndustral perspectve (O 6 ). Suppose there are fve onlne shops to be assessed. 4.. Construct Fuzzy Preferental Relaton Matrces: Fuzzy preferental relaton atrces of fve shops under sx dfferent ndcators can be constructed by usng the ethod descrbed before n secton 3.. B to B 6 ndcate Fuzzy preferental relaton atrces under objectves O to O 6 respectvely n sequence. B = B 2 = B 3 = B 4 = B 5 = B 6 = 4.2. Construct Fuzzy Consstent Matrces: Usng equaton (3.) and (3.2) n secton 3.2, FRMs n secton 4. can be transferred nto fuzzy consstent atrces as followng: R.45 = R 2.6 = R 3.6 = R 4 5 = R 5 = R 6.4 = Calculate Relatve Preferental Degree:

6 Yao Yao 68 The relatve preferental degree under all ndcators can be calculated by equaton (3.3) and (3.4) n secton 3.3. The result of relatve preferental degree under all ndcators s n Table 4.. Table 4.: Relatve preferental degree. Indcators Shop A Shop B Shop C Shop D Shop E Custoer coent Operatng hstory Sales volue Inventory turnover Delvery servce Econoc perspectve Calculate the Total Relatve Preferental Degree under Mult Indcators: Consderng the nfluental power of dfferent ndcators on credt rs, the weghng of each ndcator s as followng: w =.2, w 2 =., w 3 =.2, w 4 =.5, w 5 =.5, w 6 =.2. The total relatve portance can be calculated by equaton (5), the result s as followng: T =.993, T 2 =.27, T 3 =.999, T 4 =.975, T 5 =.229 That s T 5 >T 2 >T 3 >T >T 4. Hence, the order of the fve shops fro hgh to low credtworthness s shop 5, shop 2, shop 3, shop and shop 4. Shop 5 has hghest credblty, whle shop 4 has the lowest credblty. 5 Conclusons At present credt rs proble of onlne shops s not suffcently regulated n eergng econoes. Based on fuzzy consstent atrx, ths paper constructed a coprehensve evaluaton ndcator syste n Credt ratng. There are any ndcators to assess credt rs of onlne shops. However, the ntegraton of dfferent ndcators s a coplcated proble. Fuzzy consstent atrx, a scentfc ethod to deal wth ultple objectve decson ang process, s used to unfy the ndcators and construct a credt rs assessent syste of onlne shops. Credt rs s dffcult to be easured n quantty, and the fnancal nforaton of onlne shops s hard to collect. Therefore, applcaton of fuzzy consstent atrx can help solve the proble, construct a credt ratng syste cobne any qualtatve easures and soe quanttatve easures, on an ordnal rather than nueral bass. In the future, thrd-party specalzed nsttutons are supposed to provde far, scentfc, objectve assessent. The property of dscreton brought uncertanty n credt rs evaluaton. Fuzzy consstent atrx ethod gves soe perspectve to address ths

7 Credt Rs Assessent of Onlne Shops Based on. 69 proble. Moreover, other easures, such as posng copulsory fnancal report of onlne shops, would be necessary to prove credt worthness of e-coerce along wth credt ratng. References [] E.I. Altan, S.T., Bharath, and A..Saunder, Credt ratngs and the BIS captal adequacy refor agenda, Journal of Banng & Fnance, 26 (22), [2] A.W.A.Boot, T.T.Mlbourn, and A..Schets, Credt ratngs as coordnaton echanss, Revew of Fnancal Studes, 9 (26), 8-8. [3] A.W. Butler, and K..J.Rodgers, Relatonshp ratngs: how do bond ratng agences process nforaton?. EFA 23 Annual Conference Paper No. 49. (23) [4] A.Duff, and S.Eng, Credt Ratng Agences: Meetng the Needs of the Maret? Insttute of Chartered Accountants of Scotland, Ednburgh. (27) [5] A.Duff, and S.Eng, Understandng credt ratngs qualty: Evdence fro UK debt aret partcpants, The Brtsh Accountng Revew, 4(2), (29), 7-9. [6] M.Cheng, and M. Neatu, An eprcal analyss of changes n credt ratng propertes: Telness, accuracy and volatlty, Journal of Accountng and Econocs, 47 (29), 8-3. [7] M.H Mllon, and A.V Thaor, Moral hazard and nforaton sharng: a odel of fnancal nforaton gatherng agences, Journal of Fnance, 4(984), [8] M.Yao, B. Shen, and J. Luo, The constructon and cobned operaton for fuzzy consstent atrxes, Journal of Zhejang Unversty Scence, 6A (), (25), [9] W.F.Treacy, and M.Carey, Credt rs ratng systes at large US bans, Journal of Banng & Fnance, 24 (2), Yao Yao receved the MS degree n nternatonal oney and banng fro Unversty of Brngha n 27. She s currently a teacher n the Insttute of Servce Engneerng, Hangzhou Noral Unversty. Her research nterests are n the areas of nowledge servce, fnancal engneerng and coputng, and nternatonal fnance.

8 Appled Matheatcs & Inforaton Scences An Internatonal 5 (2) (2), 33S-37S