36
The Macrotheme Review
A multidisciplinary journal of global macro trends
An Integrated Methodology For The Financial Improvement Of The Banks With The Help Of Quality Function Deployment
Füsun KUCUKBAYand Enis YAKUT
Manisa Celal Bayar University, Business Administration Faculty,Economy and Finance Department, Manisa , TURKEY
Abstract
The banks have vital and important roles in the economic system. Their financial improvements are very essential for the sustainability of all economic system. In this study we have set out this fact and try to find actions that help the banks to improve their financial performance. The study has two main aims. Firstly, it is aimed to group the banks in Turkey into less successful, successful and very successful groups with respect to their financial performance. Secondly it is also aimed to find the best actions that improve the financial performance of the banks. By that way the banks in the less successful and successful groups will pass to upper classes. In this paper, the banks are grouped with the help of Multimoora Sort technique which is an extension of a well- known multi moora method. The proposed methodology constructs a road for improving the financial performance of the banks based on Quality Function Deployment. A numerical example is also presented to show the applicability of the proposed methodology.
Keywords: Financial ratios, financial performance, quality function deployment, multimoora sort
1. INTRODUCTION
A financial failure of a bank influences the whole ecosystem negatively. This research is based on the theoretical framework that “a financial failure which occurs as a result of strategic and operational bank decisions can be predictable and even be preventable by taking the appropriate actions; unless the failure happened as a result of global crisis and/or unexpected circumstances”.
The preventability of the financial failure has been investigated in finance literature frequently and numerous corroborative studies have been conducted. The measures that have to be taken to prevent the financial failure and the order of these measures, have to be specific to the bank and also have to be determined according to the level of the financial success of the bank.
Financial failure concept focuses on failure prediction models, comparison of these models and the success rates of the predictions in general. There are also studies where successful and unsuccessful companies are compared; the reasons of financial failures are investigated; and the prediction models are examined in terms of sectorial differences and newly established banks.
Nevertheless, the broad national and international impacts of financial success and failure require a deeper and extensive investigation of the concept. This research topic is selected because of the
37 mentioned gap in the literature. This study is different from previous financial failure studies in terms of identification of the reasons behind the failure and presenting case specific solutions to the problems which cause failures. Quality Function Deployment method will be used to prepare a failure prevention map.
When we examine the literature on Quality Function Deployment (QFD), studies are in marketing field and they mainly focus on product development and customer satisfaction. One of these studies was conducted by Chan and Wu (2005) and suggests a systematic and functional approach to QFD process. Components of House of Quality (HOQ) are explained and analyzed in detail, and a process is presented to establish a house of quality. Also, applicable methods of gathering and analyzing information from consumers and technical staff are discussed. Karsak, et al., (2003)’ s product development study, on the other hand, presents an approach which combines two decision making techniques (Analytic Network Process (ANP) and 0-1 Goal Programming (ZOGP)) in order to determine the product technical requirements in the product design process.
There are many product development studies which focus on Fuzzy Logic such as Kwong and Bai (2002)’s which uses Fuzzy Analytical Hierarchy Process, Khoo and Ho (1996)’ study which emphasizes that voice of the customer cannot be understood because of its ambiguity and variety;
and another study where researchers developed an integrated fuzzy theoretical approach and aimed to solve the QFD problems. (Kim, Moskowitz, Dhingra, & Evans, 2000).
Some other studies on quality function deployment concentrated on how to integrate QFD with some other methods. In their study, Matzler and Hinterhuber (1998) focused on how to integrate Kano’s customer satisfaction model with QFD; Tan and Shen (2000), combined Kano’s model with QFD planning matrices, and presented an integrated approach for a deeper and accurate understanding of “voice of the customer”; Bouchereau ve Rowlands (2000) summarized how to integrate technics, such as fuzzy logic, artificial neural networks and Taguchi method with QFD, in order to solve the deficiencies in QFD.
Quality Function Deployment also used in marketing in order to answer the consumer needs. For example, Trappey, Trappey and Hwang (1996) focused on the retailing sector, and aimed to develop an appropriate QFD procedure in order to improve the retailing sector in their study; Lu and Kuei (1995), used QFD in strategic market planning process and aimed to create a system to ensure customer satisfaction; Morris and Morris (1999) handled the context from marketing education point of view, and aimed to present an education module which can use QFD process and House of Quality model, in marketing classes; Griffin and Hauser (1992) examined the communication differences between two product development groups; Mohr-Jackson (1996) focused on how to adapt QFD process in marketing field in order to create customer oriented programs.
Even though there are studies which concentrate on QFD from different perspectives, such as environmentally friendly designs (Masui, Sakao, Kobayashi, & Inaba, 2003), tourism service sector (Jeong & Oh, 1998), sports industry (Partovi & Corredoira, 2002); a study with a financial point of view- especially on financial failure- has not been encountered.
As mentioned above, quality function deployment management has not been explored in the financial management field. Quality function deployment management establishes a relationship between the desired outcome and the independent variables which ensure to reach that outcome.
38 In this study, since the aim is preventing the financial failure; QFD will be used in to examine the relationship between several financial actions which affect the financial failure, such as investing into new projects, increasing or decreasing the receivables, making financial planning.
Recommendations for success will be made to the banks by considering the relationship between financial actions and financial success.
2. METHOD
The suggested method consists of four main stages:
1. Determining the financial success criteria and actions that influence the financial success.
2. Classification of the banks according to the financial success criteria by using multi criteria decision analysis technique (Multimoora sorting method)
3. Determining he financial actions for preventing financial failure by employing house of quality:
The steps of the house of quality is shown belw;
a- Determining relationship between financial success criteria and actions that influence the financial success
b- Determining the relationship among the actions that influence the financial success c- Determining the required actions in order to move a specific bank to the upper level
success group; and assessing the order of importance of those actions
39 Flowchart of the suggested integrated method is shown on Figure 1:
Figure 1: The Suggested Integrated Method Application
In the application part the banks operating in Turkey will be sorted due to their performance.
Bank sorting example is taken from Küçükbay (2016) study.
3. Criteria
The banks are classified according to their financial performance. In the classification 9 financial ratio are used. These abbreviations of the ratios, their formulas and the preferences of the ratios are given in table 1.
40 Table 1: Selected Criteria
Abbreviation Financial Ratio Preference
X1
Net Interest Income After Specific Provisions / Total
Assets Max.
X2 Shareholders' Equity / Total Assets Max.
X3
Shareholders' Equity / (Total Deposits+Non Deposit
Funds) Max.
X4 Loans Under Follow-up (gross) / Total Loans and
Receivable Min.
X5 Liquid Assets / Short-term Liabilities Max.
X6 Permanent Assets / Total Assets Min.
X7 Other Operating Expenses / Total Assets Min.
X8 Total Income/ Total Expenditures Max.
X9 Interest Expenditures / Total Assets Min.
4. Sorting Turkish banks according to their financial performance
The banks are sorted with the help of Mmoora sort method. This method is using the basic steps of Multimoora. Different from Multimoora the profile limits are used to sort the banks in to most successful, successful and unsuccessful bank groups. The selected financial ratios for fictive profile limits can be seen in table 2.
41 Table 2. Financial Ratios for Fictive Profile Limits
Financial
Ratios Profile 1
Alternative Profile 2 Alternative
X1 2,60 3,10
X2 10,50 11,50
X3 13,00 15,00
X4 4,00 3,00
X5 50,00 60,00
X6 3,00 2,00
X7 3,00 2,00
X8 135,00 150,00
X9 4,00 3,00
The banks are grouped according to their financial performance with the help of MMoora sort. In the table 3 the success group of the banks can be seen. The banks in C3 group is the most successful group, the banks in C2 group is in the successful group, the banks in C1 group is in the unsuccessful group.
42 Table 3. Sorting the Banks According to Their Success Groups
MMOORA MMOORA
SORT
BANK ID Ranking Sorting
Deutsche Bank A.Ş. a20 1 C3
Arap Türk Bankası A.Ş. a15 2 C3
Bank of Tokyo-
Mitsubishi UFJ Turkey
A.Ş. a16 3 C3
Citibank A.Ş. a18 4 C3
Turkish Bank A.Ş. a9 5 C3
Akbank T.A.Ş. a4 6 C3
Profile 2 a27 7
Türkiye Cumhuriyeti
Ziraat Bankası A.Ş. a1 8 C2
Türkiye Garanti Bankası
A.Ş. a11 9 C2
Turkland Bank A.Ş. a25 10 C2
Türkiye İş Bankası A.Ş. a12 11 C2
Fibabanka A.Ş. a6 12 C2
Yapı ve Kredi Bankası
A.Ş. a13 13 C2
ING Bank A.Ş. a23 14 C2
Tekstil Bankası A.Ş. a8 16 C2
Odea Bank A.Ş. a24 15 C2
Türk Ekonomi Bankası a10 16 C2
43 A.Ş.
Türkiye Vakıflar
Bankası T.A.O. a3 17 C2
Türkiye Halk Bankası
A.Ş. a2 18 C2
Anadolubank A.Ş. a5 19 C2
Profile 1 a26 20
Burgan Bank A.Ş. a17 21 C1
Denizbank A.Ş. a19 22 C1
Alternatifbank A.Ş. a14 23 C1
Finans Bank A.Ş. a21 24 C1
HSBC Bank A.Ş. a22 26 C1
Şekerbank T.A.Ş. a7 27 C1
In the study we have two aims first aim is to group the banks due to their financial performance and this aim is realized in table 3 with the help of Multimoora sort. The second aim is determining the actions to prevent the financial failures. To achieve the second aim the financial ratios of the banks in group C1 (Şekerbank, HSBC, Finansbank, Alternatifbank, Denizbank and Burganbank) are evaluated. After the evaluation the most important financial ratios in the failure of C1 group are determined as Loans Under Follow-up (gross) / Total Loans and Receivable (X4), Liquid Assets / Short-term Liabilities (X5), Permanent Assets / Total Assets (X6), Other Operating Expenses / Total Assets (X7) and Net Interest Income After Specific Provisions / Total Assets (X1).
After determining the financial success criteria and sorting the banks based on their financial performances, a set of actions that may have possible positive impact on the financial performance of unsuccessful banks are determined as follows:
44 No Actions
A1 Increase the investment in current assets A2 Selling permanent assets
A3 Decrease short term liability
A4 Finding long term funds with low interest rates A5 Increase the efficiency of workers
A6 Using scoring system in the credit evaluation system A7 Increasing the customer visits
A8
Perodically updating the financial data of credit customers
In order to determine the relationship between financial performances and actions that influence the financial success, a well known QFD matrix, named as House of Quality, is constructed.
Financial ratios of the banks are stated on the left side of the matrix as shown below. For each financial ratio, the decision maker priorities, using a 1 to 5 rating, are assigned. The priorities are determined for each bank individually based on the bank’s strong or weak criteria. Then the relationships between the financial ratios and the actions by using symbols for strong, medium and weak relationships. We also determine potential positive and negative interactions between the actions planned using symbols for positive or negative relationships. Eventually, we calculated the weighted importance ratings by assigning a weighting factor to relationship symbols 5-3-1, respectively.
The following example shows the house of quality for Sekerbank which is already classified into the unsuccessful banks category. It should be noted that the QFD matrix suggests actions “Selling permanent assets”, “Using scoring system in the credit evaluation system”, “Increasing the customer visits” and “Periodically updating the financial data of credit customers” are selected as the highest priority. In figure 2 the house of quality for the banks in the unsuccessful can be seen.
45 Figur 2: House of Quality for the Banks in the Unsuccessful Bank Group
5. Conclusion
The study has two phases according to its aim. In the first phase, the banks is classified according to the determined measures with the help of multi criteria decision making method called as Multimoora sort. Each bank determines its relative position in the group.
In the second part of the study, a prevention map is tried to be prepared which helps to prevent the failures of unsuccessful banks. In the preparation phase of the prevention map, quality function deployment method is used. The relationship between the financial ratios and the financial action that affect the financial ratios are analyzed with the help of quality function deployment. With the consideration of this relation, the prevention map helps to decide which financial action will be taken for making the banks to pass the upper class.
Relations
● Weak Relation
○ Medium Relation
▲ Strong Relation
Interactions
8 Positive
Negative
Relative Importance (%) Direction of Improvement Financial Ratios
Importance
13 13
9 13
55 55
10 21 10 11
44 87 43 45 39 55
○ ● ●
○ ○
X9:Interest Expenditures / Total Assets 4 ●
● ○
● ●
X6:Permanent Assets / Total Assets 5 ○ ▲
▲ ▲ ● ●
▲ ▲
X5:Liquid Assets / Short-term Liabilities 5 ▲ ▲
● ● ▲
● ●
X4:Loans Under Follow-up (gross) / Total Loans and Receivable 4 ●
● ●
● ●
X3:Shareholders' Equity / (Total Deposits+Non Deposit Funds) 2 ○
● ●
Perodically updating the financial data of credit customers
X2:Shareholders' Equity / Total Assets 2 ○
○ ▲ ●
Increasing the customer visits
X1:Net Interest Income After Specific Provisions / Total Assets 2
Relative Importance or Weight Increase the investment in current assets Selling permanent assets Decrease short term liability Finding long term funds with low interest rates Increase the efficiency of workers Using scoring system in the credit evaluation system 8 8
8 8
8
Actions
8 8 8
X8:Total Income/ Total Expenditures 2 ○ ●
▲ ○ ○ ○
● ● ●
X7:Other Operating Expenses / Total Assets 3 ▲
46 This study makes contribution to the field of the prevention of financial failures and helps the banks to pass to upper success class. As a failure of a bank affects whole economic system negatively, it is thought that this study will have positive effects on the whole economy. Beside of this benefit the study will contribute to literature by examining the prevention of financial failure which is not studied before. Research institutions, universities and banks will be able to use of the study’s findings.
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