The Evaluation and Prediction of Wealthy Management in Business Performance Efficiency - Case of S Bank

碩士 === 東吳大學 === 商用數學系 === 96 === In 2001, the domestic and overseas stock market performed badly and theCentral Bank kept lowering the deposit interest rate which shortened the interest gap(between deposit and loan) dramatically. Besides, in 2006, the issue about cash cardand credit card impacted th...

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Bibliographic Details
Main Authors: Ming-chun Tsai, 蔡明春
Other Authors: Chin-Hsiung Hsu
Format: Others
Language:zh-TW
Published: 2008
Online Access:http://ndltd.ncl.edu.tw/handle/s6bxwf
Description
Summary:碩士 === 東吳大學 === 商用數學系 === 96 === In 2001, the domestic and overseas stock market performed badly and theCentral Bank kept lowering the deposit interest rate which shortened the interest gap(between deposit and loan) dramatically. Besides, in 2006, the issue about cash cardand credit card impacted the (financial) individual consuming affair, the governmentsupported (promoted) the liabilities negotiation and banks showed (reported/ had)their bad debts. There are so many factors influencing the surplus of the financialindustry. The main income resource of banks was the interest gap (between depositand loan), but now it tends to be the fee that charges on the client who needs us tomanage his wealth. In that case, there’s no need to report (show) bad debts andcommission. Moreover, wealth management business is with great potential andmarket share, so domestic banks put massive emphasis on it. However, it’s alsoimportant to discuss the management efficiency when every bank puts all theresources into it. The study takes S bank as an example using the data from the second season in2006 to the fourth season in 2007 classified by regions and using Data EnvelopmentAnalysis (Input: the number of financial counselor and the salary cost. Output: theincome of handling charge of structured note, insurance product and mutual fund.) toanalyze the performance of some local banks. In this thesis, we try to analyze themanagement efficiency of each region about wealth management to offer managers an important reference about making decisions about wealth management business. Data Envelopment Analysis doesn’t predict the future efficiency, so I will useGrey prediction model to predict the next input and output and then compare thecomputation to cover the weakness of Data Envelopment Analysis. Finally, we willgive some useful suggestions to these inefficient units in our study.