Financial Service of Wealth Management Banking: Balanced Scorecard Approach

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1 Journal of Socal Scences 4 (4): , 2008 ISSN Scence Publcatons Fnancal Servce of Wealth Management Bankng: Balanced Scorecard Approach Cheng-Ru Wu, Chn-Tsa Ln and Pe-Hsuan Tsa Graduate Insttute of Busness and Management, Yuanpe Unversty, 306 Yuanpe St., Hsn Chu 30015, Republc of Chna, Tawan Abstract: Problem Statement: There are four man bankng busness sectors n Tawan, nvolvng the areas of consumer, corporate, wealth management, and nvestment bankng. The wealth management bankng sector s actvely promoted for reapng a rsk-free premum. In the proposed model, the dmensons of fnancal servces for wealth management banks have been taken from four perspectves derved from balanced scorecard approach, vz. fnance, customer, nternal busness, learnng and growth. Approach: The organzatonal performance of wealth management banks n Tawan s evaluated by applyng the Analytcal Herarchy Process (AHP) and the Technque for Order Preference by Smlarty to Ideal Soluton (TOPISI). Results: Table 6 shows the relatve weghts of the four banks based on the results of from AHP, as well as the relatve weghts from TOPSIS. In the demonstrated example, Bank C should be perfect because t has the largest relatve weghts (Bank C = and 0.539, from AHP and TOPSIS n Table 8). In Table 6, Summary of the TOPSIS C * wth respect to wealth management banks: A (0.482), B (0.269), C (0.539) and D (0.294). C performs the best. Concluson: Importantly, the proposed model can beneft the bankng sector n assessng the organzatonal performance of wealth management banks, makng t hghly applcable for bank managers and fnancal sector analysts. Key words: Organzatonal performance, wealth management, AHP, TOPSIS, balanced scorecard INTRODUCTION Tawan s economc and fnancal markets have experenced dramatc changes n recent years. Addtonally, the organzatonal structure of the wealth management servce sector has mproved as banks have mplemented management practces that have helped to ncrease ther compettveness. In such an ntensve envronment, selectng a performance measurement of wealth management bankng has become a prorty. Durng the process of selectng a wealth management bank, apart from legal ssues, polcymakers and busness groups seldom consder potental factors that could mpact a bank s compettveness. Many busness organzatons have found the Balanced Scorecard to be a valuable tool n performance and strategc management [7-10]. The objectve of ths study s to examne the value of Balanced Scorecard n the organzatonal performance of wealth management banks and to descrbe an analytc herarchy framework that can be used to evaluate scorecards of departments and programs wthn wealth management banks and the organzatonal performance of wealth management banks as a whole. The Technque for Orderng Preference by Smlarty to the Ideal Soluton (TOPSIS) was frst developed by [2], based on the concept that the selected alternatve should have the shortest dstance from the postve deal soluton and the farthest from the negatve-deal soluton for solvng the MCDM problem. Thus, the best alternatve should not only have the shortest dstance from the postve deal soluton, but also the longest dstance from the negatve deal soluton. In short, the deal soluton comprses all of the optmum crtera values, whereas the negatve deal soluton comprses all the least optmal crtera values. However, the results vary accordng to perod, modelng and approach. In the proposed AHP model, the dmensons of the organzatonal performance for the wealth management banks have been taken from the four perspectves of the Balanced Scorecard, thus balancng as well as lnkng the fnancal and nonfnancal, tangble and ntangble, nternal and external factors. Therefore, the proposed framework provdes a Correspondng Author: Cheng-Ru Wu, Graduate Insttute of Busness and Management, Yuanpe Unversty, 306 Yuanpe St., Hsn Chu 30015, Republc of Chna, Tawan 255

2 holstc approach to the selected Mult-Crtera Decson-Makng (MCDM) problem for wealth management banks. Next, a case dentfes proposal model usng AHP and the TOPSIS technque to evaluate wealth management banks organzatonal performance. Ths proposal further combnes the concepts of the AHP and TOPSIS models to evaluate and rank wealth management bank performance. The AHP and TOPSIS-based decson-makng method for constructng an evaluaton method can provde bank decson makers or admnstrators wth a valuable reference for evaluatng the organzatonal performance. Importantly, the proposed model can provde Tawan s bank accredtaton polcy a reference materal, makng t hghly applcable for bank admnstrators and fnancal sector analysts. MATERIALS AND METHODS The AHP Methodology: Analytc Herarchy Process (AHP), whch s a technque of Mult-Crtera Decson Makng (MCDM), was developed by Saaty n AHP s used to solve complex decson-makng problems n dfferent areas, such as mantenance selecton problem [16], selecton of locaton [13,14,15], measurng performance [1,14], allocatng resources [17], choosng the best polcy after fndng a set of alternatves [18]. As a decson method that decomposes a complex mult-crtera decson problem nto a herarchy [11], AHP s also a measurement theory that prortzes the herarchy and consstency of judgmental data provded by a group of decson makers. AHP ncorporates the evaluatons of all decson makers nto a fnal decson, wthout havng to elct ther utlty functons on subjectve and objectve crtera, by parwse comparsons of the alternatves [12]. The TOPSIS Methodology: The TOPSIS was frst proposed by Hwang and Yoon [2]. The underlyng logc of TOPSIS s to defne the deal soluton and the negatve deal soluton. The deal soluton s the soluton that maxmzes the beneft crtera and mnmzes the cost crtera; whereas the negatve deal soluton maxmzes the cost crtera and mnmzes the beneft crtera. The optmal alternatve s the one, whch s closest to the deal soluton and farthest to the negatve deal soluton. The rankng of alternatves n TOPSIS s based on the relatve smlarty to the deal soluton, whch avods from the stuaton of havng same smlarty to both deal and negatve deal solutons. J. Socal Sc., 4 (4): , Fg. 1: Four perspectves of balanced scorecard The balanced scorecard: Kaplan and Norton [5,6,8] presented the Balanced Scorecard concept n a seres of artcles publshed n the Harvard Busness Revew. They argued that tradtonal fnancal accountng measures such as return-on-nvestment and payback perod analyss [4,8] offer a narrow and ncomplete pcture of busness performance and that relance on such data hnders the creaton of future busness value. Accordngly, they suggest that fnancal measures can be supplemented wth addtonal ones that reflect customer satsfacton, nternal busness processes and the ablty to learn and grow. The Balanced Scorecard was desgned to complement fnancal measures of past performance wth measures of the drvers of future performance [8]. Of the four key performance perspectves of the Balanced Scorecard, only one nvolves standard fnancal performance ndcators, whereas the other three nvolve non-fnancal performance measurement perspectves: customer satsfacton, nternal busness processes and learnng and growth capactes. These four perspectves consttute the framework of the Balanced Scorecard (Fg. 1). Evaluaton model: The evaluaton procedure of ths study conssts of several steps as shown n Fg. 2. The frst step s to dentfy the multple crtera that are consdered n the decson makng process for the decson makers to make an objectve and unbased decson. The Delph method s adopted here not only to accumulate expert opnons, but also to dentfy the

3 Fg. 2: AHP and TOPSIS Measurement Processes for Wealth Management Bank s Organzatonal Performance determnants of the ntegrated marketng communcaton-based model. After constructng a crtera framework, the crtera weghts can be calculated by usng AHP. Fnally, we conduct a TOPSIS approach to acheve the fnal rankng results. The detaled descrptons of each step are elaborated n each of the followng sub-crtera. Establsh an evaluate model and defne the evaluatve crtera: Usng the Delph method, a consensus among experts on establshng a model can be reached. The ultmate goal of evaluatng the deal organzatonal performance can be acheved, followng the dentfcaton of four evaluaton crtera, nneteen sub-crtera and fnally, the alternatves (Fg. 3). The evaluaton crtera and sub-crtera used to evaluate the organzatonal performance are defned as follows: Fnancal perspectve: Fnancal perspectve refers to a wealth management bank s revenue durng the operaton tme, ncludng handlng charge/revenue, customer market share rato, capacty for proftablty and management assets (suggested by bank admnstrators and academcans): Handlng charge/revenue: Wealth management bank s revenue ganed by sellng the customer s product Customers market share rato: Reflects the proporton of busness n a gven market (n terms of the number of customers, dollars spent, or unt volume sold) that a busness unt sells J. Socal Sc., 4 (4): , Capacty for proftablty: The varous products and projects created by wealth management banks that serve to ncrease ther capacty for proftablty Management assets: Management assets are a very mportant factor n Tawan s wealth management bankng sector Customer perspectve: Factors nvolvng the customers of wealth management banks nclude customer acquston, VIP-certfed fnancal servces (suggested by bank admnstrators and academcans), customer proftablty, customer confdence and customer retenton [8]. Customer acquston: Measures, n absolute or relatve terms, the rate at whch a busness unt attracts or wns new customers or busness. VIP-certfed fnancal servce: The provson to customers of complete VIP-certfed fnancal servces Customer proftablty: Measures the net proft of a customer, or of a segment, after allowng for the unque expenses requred to support that customer or segment Customer confdence: Wealth managers mprove the VIP servce for new customers and assure them confdentalty Customer retenton: Tracks, n absolute or relatve terms, the rate at whch a busness unt retans or mantans ongong relatonshps wth ts customers Internal busness process perspectve: Wealth management bank performance measurement, organzaton, management practces and compettors all nfluence the followng factors: lead n nnovaton system programmng, certfed fnancal ntegraton platform for professonals, operatng qualty for a group of customers, nternal customer satsfacton and management stratum support (suggested by bank admnstrators and academcans). Lead n nnovaton system programmng: Measures how well a wealth management bank accedes to nnovaton system programmng n accordance wth the wealth manager s professonal knowledge and ablty Certfed fnancal ntegraton platform for professonals: The wealth management bank provdes the certfed fnancal ntegraton platform for professonal VIP customers Operatonal qualty for a group of customers: The admnstraton of the operatonal qualty for a

4 J. Socal Sc., 4 (4): , 2008 Fg. 3: Wealth Management Bank s organzatonal performance model group of customers requres professonal CEO and wealth managers Internal customer satsfacton: The nternal customer satsfacton ndex was constructed through monthly surveys of randomly selected customers n the wealth management bank s targeted segments Management stratum support: To obtan the executve manager s support Learnng and growth perspectve: The factors comprsng the learnng and growth perspectve nclude wealth manager s professonal knowledge and growth, educaton and tranng of wealth management team, wealth manager s scale of team, wealth manager s complant system and approprateness of performance polcy for rewards and punshments. Wealth managers professonal knowledge and growth: The wealth management bank develops the wealth manager s professonal knowledge and technques Educaton and tranng of wealth management team: Ths ncludes wealth management knowledge, the use of teleconferencng and the attanment of basc professonal certfcates Wealth manager s scale of team: The bank provdes a complete wealth manager s scale of team for the customer servce system 258 Wealth managers complant system: The banks provde the complant system for wealth managers Approprateness of performance polcy rewards and punshments: Herzberg s motvaton theory (1966) argued that there must be a lnk among strvng, performance and remuneraton. Academcans have also ndcated that lnkng bounty, remuneraton and performance to the performance bonus system can enable wealth managers to work more effectvely wth ncreased motvaton Determne the weght of crtera by usng AHP: As a decson method that decomposes a complex multcrtera decson problem nto a herarchy [11], AHP s also a measurement theory that prortzes the herarchy and consstency of judgmental data provded by a group of decson makers. AHP ncorporates the evaluatons of all decson makers nto a fnal decson [1,3,14,15], wthout havng to elct ther utlty functons on subjectve and objectve crtera, by par-wse comparsons of the alternatves [12]. AHP s made n the framework of a matrx and a local prorty vector can be derved as an estmate of relatve mportance assocated wth the elements (or components) beng compared by solvng the followng formulae: A w =λ w (1) max

5 J. Socal Sc., 4 (4): , 2008 Where: A = The matrx of par-wse comparson w = The egenvector λ max = The largest Egenvalue of A Saaty [11] proposed utlzng Consstency Index (CI) and Consstency Rato (CR) to verfy the consstency of the comparson matrx. CI and RI are defned as follows: λmax n C.I. = n1 (2) CI CR = (3) RI where, RI represents the average consstency ndex over numerous random entres of same order recprocal matrces. If CR 0.1, the estmate s accepted; otherwse, a new comparson matrx s solcted untl CR 0.1. Determne the wealth management banks organzatonal performance by usng TOPSIS: The TOPSIS was frst proposed by [2]. The underlyng logc of TOPSIS s to defne the deal soluton and the negatve deal soluton. The deal soluton s the soluton that maxmzes the beneft crtera and mnmzes the cost crtera; whereas the negatve deal soluton maxmzes the cost crtera and mnmzes the beneft crtera. The optmal alternatve s the one, whch s closest to the deal soluton and farthest to the negatve deal soluton. The rankng of alternatves n TOPSIS s based on the relatve smlarty to the deal soluton, whch avods from the stuaton of havng same smlarty to both deal and negatve deal solutons. The calculaton processes of the method are as followng: Establsh a Decson (D) matrx for alternatve performance: X = a crsp value ndcatng the performance ratng of each alternatve A wth respect to each crteron X j. Normalzng the D matrx: Calculate the normalzed decson matrx R (= [r ]). The normalzed value r s calculated as: X r =, j = 1,..., n; = 1,..., m n 2 X j= 1 (5) Create the weghted normalzed performance n matrx: A set of weghts w= (w 1, w 2, w n ), wj = 1, j= 1 from the ANP s accommodated weght. Ths matrx can be calculated by multplyng each column of the R wth ts assocated weght w j. Therefore, the weghted normalzed decson matrx V s equal to: V V11 V12 L V1j L V1n M M M M V V L V L V M M M M Vm1 Vm2 Vmj V L L mn wr 1 11 wr 2 12 L wr j L wnr1n M M M M wr wr L wr L w r M M M M wr 1m1 wr 2m2 wr jmj wnr L L mn = 1 2 n = j n n (6) Determne the deal soluton and negatve deal soluton: The deal soluton s computed based on the followng equatons: A = {(max V j J), (mn V j J '), = 1,2,..., m} (7) A1 X11 X12 L L X1j X1n X 2 21 X22 X2 j X A L L 2n M M M L M M M D = A X 1 X2 M M X Xn M M M L M M M A X X L L X X m m1 m2 mj mn. (4) Where: A = The possble alternatves, = 1,,m X j = Attrbutes or crtera relatng to alternatve performance, j = 1,...,n 259 A = {(mn V j J), (max V j J'), = 1,2,..., m} (8) Where: j = {j = 1,2,,n j belongs to beneft crtera} j = {j = 1,2,,n j belongs to cost crtera} Calculate the dstance between dea soluton and negatve deal soluton for each alternatve: n 2 = j j= 1 S (V V ) = 1, 2,., m (9)

6 n 2 = j j= 1 S (V V ) = 1, 2,., m (10) Calculate the relatve closeness to the deal soluton of each alternatve: S * = * S + S C = 1, 2,., m (11) where, 0 C 1 that s, an alternatve s closer to A * as C approaches to 1. Rank the preference order: A set of alternatves can be preference ranked accordng to the descendng order of C. RESULTS AND DISCUSSION Case mplementaton: Step 1: Establsh an evaluate framework: Usng the Delph method [13], acqure evaluate framework; the evaluate framework are depcted n Fg. 3. Step 2: Determne the weght of crtera and sub-crtera by usng AHP: The weghts of crtera and sub-crtera are then determned for a sample group of 19 ndvduals matchng the above characterstcs wth each respondent makng a par-wse comparson of the decson crtera and sub-crtera assgnng them relatve scores. The relatve scores provded by eleven experts are aggregated usng the geometrc mean method. The prortes for the crtera can be obtaned by the procedure stated n the prevous and s: C C C C J. Socal Sc., 4 (4): , 2008 (12) The respectve weghts of the four evaluatve crtera are fnancal perspectve (0.292), customer perspectve (0.287), nternal busness process perspectve (0.220) and learnng and growth perspectve (0.202). The egenvectors for fnancal perspectve, customer perspectve, nternal busness process perspectve and learnng and growth perspectve are organzed nto a matrx that represents the relatve mportance of sub-crtera wth respect to ther upper level crtera SC SC SC SC SC SC SC SC SC SC SC SC SC SC SC SC SC 17 SC SC C C C C (13) The respectve weghts of the four sub-crtera for fnancal perspectve are SC 1 (0.243), SC 2 (0.171), SC 3 (0.430) and SC 4 (0.156). The respectve weghts of the fve sub-crtera for customer perspectve are SC 5 (0.103), SC 6 (0.140), SC 7 (0.502), SC 8 (0.110) and SC 9 (0.145). The respectve weghts of the fve subcrtera for nternal busness process perspectve are SC 10 (0.128), SC 11 (0.192), SC 12 (0.279), SC 13 (0.171) and SC 14 (0.230). The respectve weghts of the fve sub-crtera for learnng and growth perspectve are SC 15 (0.402), SC 16 (0.209), SC 17 (0.094), SC 18 (0.182) and SC 19 (0.112). Assume there s no nterdependence among sub-crtera, whch sub-crtera should be, emphaszed more n determnng ther respectve upper level crteron. Table 1, Synthess Value (weghts of overall) of four wealth management banks under nneteen subcrtera are SC 1 (0.07), SC 2 (0.05), SC 3 (0.13), SC 4 (0.05), SC 5 (0.03), SC 6 (0.04), SC 7 (0.14), SC 8 (0.31), SC 9 (0.04), SC 10 (0.03), SC 11 (0.04), SC 12 (0.06), SC 13 (0.04), SC 14 (0.05), SC 15 (0.08), SC 16 (0.04), SC 17 (0.02), SC 18 (0.04) and SC 19 (0.02). Customer Confdence (SC 8 ), customer proftablty (SC 7 ) and ablty to proftablty (SC 3 ) are hghly n

7 J. Socal Sc., 4 (4): , 2008 Table 1: Egenvectors (weghts) for crtera and sub-crtera Weghts Weghts Weghts of Crtera for level 2 Sub-crtera for level 3 the overall C SC (5) SC (8) SC (3) SC (9) C SC (16) SC (13) SC (2) SC (1) SC (12) C SC (17) SC (10-11) SC (6) SC (14) SC (7) S SC (4) SC (10-11) SC (19) SC (15) SC (18) Step 3: Determne the weght of organzatonal performance by usng TOPSIS: Establshng and normalzng the D matrx: At the next level of the decson procedure, 11 experts were asked to establsh the decson matrx by comparng hosptals under each of the sub-crtera separately. The sub-crtera were assumed to be beneft sub-crtera and all the members were asked to gve a set of crsp values wthn the range from 1-10 to represent the performance of each bank wth respect to each sub-crteron. After the decson matrx was determned. Based on Table 2 normalze matrx by Eq. 5. Snce the sub-crtera weghts (W AHP ) have been obtaned from AHP, the weghted normalzed performance matrx can be calculated by Eq. 6. Table 2-4 shows the decson, normalzes and weghted normalzed matrx. Determnng the C * : Frst, determne the deal soluton and negatve deal soluton usng formulae (9) and (10). Table 5 dsplays those results. Next, calculate the relatve closeness to the deal soluton of each alternatve, C, usng Eq. 11. Accordng to Table 6 the * rankng order of the four banks s Bank C (0.539), Bank A (0.482), Bank D (0.294) and Bank B (0.269). Therefore, the best organzatonal performance s Bank C. Step 4: Fnal organzatonal performance score: Snce the sub-crtera weghts have been obtaned from AHP, the TOPSIS weghts can be calculated by Eq Table 6 summarzes those results. Summary of the performance wth respect to organzatonal performance: Bank C (0.539), Bank A (0.482), Bank D (0.294) and Bank B (0.269). Bank C performs the best. Table 2: The decson makng matrx Sc 1 Sc 2 Sc 3 Sc 4 Sc 5 Sc 6 Sc 7 Sc 8 Sc 9 Sc 10 Sc 11 Sc 12 Sc 13 Sc 14 Sc 15 Sc 16 Sc 17 Sc 18 Sc 19 A B C D Table 3: The normalze decson makng matrx Sc 1 Sc 2 Sc 3 Sc 4 Sc 5 Sc 6 Sc 7 Sc 8 Sc 9 Sc 10 Sc 11 Sc 12 Sc 13 Sc 14 Sc 15 Sc 16 Sc 17 Sc 18 Sc 19 A B C D Table 4: The weghted normalze decson makng matrx Sc 1 Sc 2 Sc 3 Sc 4 Sc 5 Sc 6 Sc 7 Sc 8 Sc 9 Sc 10 Sc 11 Sc 12 Sc 13 Sc 14 Sc 15 Sc 16 Sc 17 Sc 18 Sc 19 A B C D Table 5: Resultant of S * and S S * A B C D S

8 J. Socal Sc., 4 (4): , 2008 CONCLUSION The composte prortes of the alternatves are then determned by aggregatng the weghts throughout the herarchy. The composte prortes of the alternatves are: (14) Formulae (14) ndcate that the weghts of AHP are as n the followng: Bank A = Bank B = Bank C = Bank D = * Table 6: Summary of the TOPSIS C * C Rank A B C D Table 7: Summary of the AHP Weghts Rank A B C D Table 8: Comparson of the fndngs of AHP and TOPSIS AHP TOPSIS OP Results Rank OP Results Rank A A B B C C D D Therefore, Bank C performs the best, Table 7 summary of AHP. The purpose of ths study s to present an effectve framework applyng both AHP and TOPSIS methods to evaluate organzatonal performance of wealth management banks. In order to ascertan the value of ths model, results of the normalzed relatve weghts of the organzatonal performance of wealth management banks obtaned from AHP and TOPSIS are compared. Table 6 shows the relatve weghts of the four banks based on the results of from AHP, as well as the relatve weghts from TOPSIS. In the demonstrated example, Bank C should be perfect because t has the largest relatve weghts (Bank C = and 0.539, from AHP and TOPSIS n Table 8). In Table 6, Summary of the TOPSIS C * wth respect to wealth management banks: A (0.482), B (0.269), C (0.539) and D (0.294). C performs the best. Therefore, the admnstrators or decson makers should select C. Fnally, we recommend that admnstrators or decson makers can use ths model to evaluate the organzatonal performance of wealth management banks for bank admnstrators and fnancal sector analysts. 262

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