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THE ANALYSIS OF FINANCIAL RATIOS TO DETERMINE THE PROBABILITY OF DEFAULT OF CORPORATE LOAN BANK X FINAL REPORT. By Mevira Munindra

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THE ANALYSIS OF FINANCIAL RATIOS TO DETERMINE THE

PROBABILITY OF DEFAULT OF CORPORATE LOAN BANK X

FINAL REPORT

By

Mevira Munindra

19007102

Undergraduate Program

School of Business and Management

Institut Teknologi Bandung

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VALIDATION PAGE

THE ANALYSIS OF FINANCIAL RATIOS TO DETERMINE THE

PROBABILITY OF DEFAULT OF CORPORATE LOAN BANK X

By

MEVIRA MUNINDRA

ID No: 19007102

A Final Project in Partial Fulfillment

of the Requirement for the Degree of Bachelor of Management

Undergraduate Program of Management Study

School of Business and Management

Institut Teknologi Bandung

July, 2010

Validated By

____________________________________

Ir. Achmad Herlanto Anggono, MBA.

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iii

ABSTRACT

Bank X, the public listed company, is one of the biggest bank in Indonesia. The good management system supports the growing and developing performance which had been through for about 6 years in banking industry. Concerning to Bank Indonesia’s regulations, Bank X implements risk management to support the good performance. Bank X provides a proper and effective management in controlling and monitoring the risk, including credit risk. To measure the credit risk, banks need to determine probability of default, exposure at default, and loss given default. Since credit risk is one of the important risk that should be managed by consumer bank, bank needs to have the fit measurement in deciding credit approval to the debtors. The fit measurement is needed to prevent the blown-up numbers of non-performing loan or even default. The applied measurement in Bank X is using credit rating for Corporate Segment, as the internal rating-based approach. The credit rating could also prepare the capital allocation for bank, in preparing the debtors’ default. Credit rating has two parameters involved, quantitative and qualitative parameters. The quantitative parameter, as the mandatory parameter, is using financial ratios. The qualitative parameter, as the supporting data, is using the debtors or corporates actual performance data. At the end, credit rating of debtors produces the probability of default.

Since financial ratios of debtors are defined to be mandatory parameter, it would be necessary to review the effect financial ratios in determining probability of default. Therefore, Bank X could watch and evaluate those debtors’ financial ratios in order to prevent the high amounts of default. There are also more opportunities for Bank X developing the tools or system to mititgate the credit risk.

Binary logit model indicates that all or several financial ratios of debtors are affecting to determine the probability of default, since H0 is rejected. From 20 (twenty) financial ratios in year 2006-2008, there are several financial ratios which have significant effect to the probability of default. Those affecting ratios are Operating Margin, Assets Turnover, Ebitda to Debt and Ebitda to Liabilities. The most affecting ratio is Operating Margin and the least one is Ebitda to Liabilities. As looking through the result, those ratios in debtors’ performance are better being watched and monitored by bank in order to control credit risk the bank itself. Banks will become easier to warn and support the debtors in accomplish the better performance. Furthermore, the bank will be also able to manage and prepare the credit portfolio inside. Those ratios gives the effect to the probability of default cannot be described specifically. Assets Turnover examined how the corporates activity to be safe from default by generating sales, Ebitda to Liabilities examined how the corporates real value or performance is determined by its liabilities. Ebitda to Debt examined how the corporates real value or performance is determined by its debt, and the Operating Margin examined how the corporates performance in maintaining the sales and expenses after getting loan. However, the other financial ratios have to be watched over and evaluated. The fluctuative trends in all industries could be attempted in affecting the corporates to be default. Bank X, as one of the big banks in Indonesia, should manage and evaluate carefully the bank’s portfolios in mitigating the risk, especially the credit risk.

`

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iv

ABSTRAK

Bank X, perusahaan publik, merupakan salah satu bank terbesar di Indonesia. Sistem manajemen yang baik mendukung tumbuh dan berkembangnya kinerja selama sekitar 6 tahun di industri perbankan. Dengan adanya peraturan Bank Indonesia, Bank X menerapkan manajemen risiko untuk mendukung kinerja yang lebih baik. Bank X memberikan manajemen yang tepat dan efektif dalam mengontrol dan memantau risiko, termasuk risiko kredit. Untuk mengukur risiko kredit, bank perlu untuk menentukan probability of default, exposure at default, dan loss

given default. Karena risiko kredit merupakan salah satu risiko yang penting yang harus dikelola

oleh bank konsumen, bank harus memiliki pengukuran yang sesuai dalam memutuskan persetujuan kredit kepada debitur. Pengukuran yang sesuai diperlukan untuk mencegah meledaknya kredit macet atau gagal bayar. Pengukuran diterapkan di Bank X menggunakan peringkat kredit untuk Segmen Korporat, yang merupakan sebagai pendekatan penilaian berbasis internal. Peringkat kredit juga dapat mengalokasikan modal bank, dalam penyusunan gagal bayar pada debitur. Peringkat kredit memiliki dua parameter yang terlibat, parameter kuantitatif dan kualitatif. Parameter kuantitatif, sebagai parameter wajib, adalah dengan menggunakan rasio keuangan. Parameter kualitatif, sebagai data pendukung, menggunakan data kinerja aktual debitur atau korporat. Pada akhirnya, peringkat kredit debitur menghasilkan probabilitas gagal bayar.

Sejak rasio keuangan debitur didefinisikan sebagai parameter wajib, perlu untuk meninjau pengaruh rasio keuangan dalam menentukan probabilitas gagal bayar. Oleh karena itu, Bank X dapat melihat dan mengevaluasi rasio keuangan debitur untuk mencegah jumlah gagal bayar yang tinggi. Ada juga kesempatan lebih bagi Bank X untuk mengembangkan alat atau sistem dalam mengurangi risiko kredit.

Model logit biner mengindikasikan bahwa semual atau beberapa rasio financial dari debitur mempengaruhi dalam determinasi probabilitas gagal bayar, setelah H0 ditolak. Dari 20 (dua puluh) rasio keuangan pada tahun 2006-2008, ada beberapa rasio keuangan yang berpengaruh signifikan terhadap probabilitas default, rasio tersebut mempengaruhi adalah Margin Operasi, Perputaran Aktiva, Ebitda untuk Hutang dan Ebitda untuk Kewajiban. Rasio yang paling berpengaruh adalah Margin Operasi, sedangkan yang paling tidak berpengaruh adalah Ebitda untuk Kewajiban. Rasio kinerja debitur lebih baik diawasi dan dipantau oleh bank dalam rangka pengendalian risiko kredit bank itu sendiri. Bank dapat menjadi lebih mudah untuk memperingatkan dan mendukung debitur dalam mencapai kinerja yang lebih baik. Selain itu, bank juga akan mampu mengelola dan menyiapkan portofolio kredit di dalamnya.

Rasio berpengaruh terhadap kemungkinan gagal bayar tidak dapat dijelaskan secara spesifik. Perputaran Aktiva meneliti bagaimana kegiatan korporasi aman dari gagal bayar dengan menghasilkan pendapatan, Ebitda untuk Kewajiban memeriksa bagaimana nilai nyata atau kinerja korporasi ditentukan oleh kewajibannya. Ebitda untuk Hutang memeriksa bagaimana nilai nyata atau kinerja korporasi ditentukan oleh utang, dan Margin Usaha memeriksa bagaimana kinerja korporasi dalam menjaga dan beban penjualan setelah mendapatkan pinjaman. Namun, rasio keuangan lainnya harus diawasi dan dievaluasi. Kecenderungan fluktuatif di semua industri dapat mempengaruhi korporat menjadi gagal bayar. Bank X, sebagai salah satu bank besar di Indonesia, harus mengelola dan mengevaluasi dengan hati-hati portofolio bank dalam meminimalisir risiko, khususnya risiko kredit.

Kata kunci: manajemen risiko, risiko kredit, peringkat kredit, probabilitas gagal bayar, rasio keuangan

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v

FOREWORD

After three years survived in this college, it is so relieving to feel this report is the last

one to finish. So many times spent through until the research applied, the problem

solved, the report finished, and the experience accomplished. Alhamdulillah.

Gratitude to Allah SWT for keeping me sane through the hard days and biggest thanks

to these people in a moment to finish the final project:

1. Mr. and Mrs. Muhardjono, my beloved parents for the never ending prayers

2. Rania, Mardhika and Danawan, my beloved siblings for all time supports

3. Ir. Achmad Herlanto Anggono, MBA, my counselor for the kindness in

encouraging and supervising the research

4. Ir. Drs. H. Arson Aliludin, SE, DEA, my examiner and lecturer

5. Mr Huska Davinsi Anwar, Mrs. Dewi Gayatri, Mr. Sujito, Mr Arif Setiawan and

Miss Ameliah Diah, my supervisors in Bank X for the kindness in assisting the

research.

6. SBM-ITB lecturers and tutors, who always teach a lot of precious knowledge

and experiences.

7. Rinindi, Evita, Ines, Dhyla, Yasmin, Nidia, Emyr, Jatun, Ikrom, Ichan, for

always being a reminder, spirits and best friends in these 3 (three) past years.

8. Marsha, Dastie, Irna, Sassa, Ditha, Abby, Kathalizsa, Shervani, Bunga, Anindya,

Achi, Tya, Icang, Tantra, and Rizky, for always being here and there.

9. SBM batch 2010, especially Tutorial A , for all the shared moment together, for

all the laughing times, for all the memories within 3 (three) years.

It has been tough days, weeks, and months to finish this final research report titled “The

Analysis of Financial Ratios To Determine The Probability of Default Corporate

Loan Bank X”. The author is aware to the imperfections of this final project. Therefore,

critiques and recommendations are very welcome to enhance this final project.

Hopefully, this final project can be useful for all of us..

July, 2010

Author

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vi

LIST OF CONTENTS

COVER ...i

VALIDATION PAGE ...ii

ABSTRACT ...iii

ABSTRAK ...iv

FOREWORD ...v

LIST OF CONTENTS ...vi

LIST OF FIGURES ...viii

LIST OF TABLES ...ix

CHAPTER I INTRODUCTION ...1

1.1 Background ...1

1.2 Problem Identification ...3

1.3 Research Objectives ...3

1.4 Research Limitation and Assumption ...3

1.5 Systematical Writings...4

CHAPTER II THEORETICAL FOUNDATION ...7

2.1 Risk Management ...7

2.2 Credit Risk ...8

2.3 Credit Rating ...10

2.3.1 Quantitative Data ...14

2.3.2 Qualitative Data ...18

2.4 The Logit Model ...18

CHAPTER III METHODOLOGY ...23

3.1 Research Methodology ...23

3.1.1 Preliminary Observation ...23

3.1.2 Literature Study ...24

3.1.3 Data Collection and Calculation ...24

3.1.3.1 Dependent Variable ...25

3.1.3.2 Independent Variable ...27

3.1.4 Data Analysis ...28

3.1.4.1 Hypothesis Test ...28

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vii

3.2 Research Object ...29

CHAPTER IV DATA ANALYSIS ...31

4.1 Data Calculation ...31

4.2 Binary Logit Interpretation ...31

4.3 Result Analysis ...37

4.3.1 Significant Financial Ratios ...38

4.3.2 Other Financial Ratios ...40

CHAPTER V CONCLUSION AND RECOMMENDATION ...43

5.1 Conclusion ...43

5.2 Recommendation ...45

REFERENCES ...47

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viii

LIST OF FIGURES

Figure 2.1 Logit model graphs ...19

Figure 3.1 Research methodology ...23

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ix

LIST OF TABLES

Table 2.1 Loan rating description ...12

Table 2.2 Financial ratios formulation ...15

Table 3.1 Industry included in Corporate Segment in Bank X ...24

Table 3.2 Raw classification Probability of Default ...25

Table 3.3 Dependent variable classification ...26

Table 3.4 Independent variables classification ...27

Table 4.1 Dependent variable categorical ...31

Table 4.2 Binary logit result ...32

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