ANALYSIS OF CREDIT RISK MEASUREMENT OF HOUSING LOAN
USING INTERNAL MODEL CREDIT RISK+ IN BANK X
FINAL PROJECT
By
Rizky Alfa Bramanto 19007008
Undergraduate Program
School of Business and Management
Institut Teknologi Bandung
VALIDATION PAGE
ANALYSIS OF CREDIT RISK MEASUREMENT OF HOUSING LOAN
USING INTERNAL MODEL CREDIT RISK+ IN BANK X
By
RIZKY ALFA BRAMANTO
ID No: 19007008
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 23, 2010
Validated By
Ir. Achmad Herlanto Anggono, MBA
NIP: 999089103
ABSTRACT
The purpose of this research is to find out a method that is going to be used to calculate how high the risk of Housing Loan by using the method of internal model CreditRisk+. Aside from that, Bank X can also measure the expected loss and the unexpected loss, as well as the amount of economic capital that has to be provided by Bank X to cover the unexpected loss.
A general view on the method that is going to be used is as follows: 1. Collecting data of Housing Loan debtor in the predetermined period 2. Arranging Band and Exposure Default per Band
3. Measuring the Recovery Rate
4. Measuring the Severity Loss or Loss Given Default
5. Measuring the Probability of Default and Cumulative Probability of Default 6. Measuring Expected Loss and Unexpected Loss
7. Measuring the Economic Capital
CreditRisk+ is a method of measuring the risk which was developed by Credit Suisse First Boston (CSFB) in December 1996. In this method, there are two focus points that are being dealt with. One is default and non-default, and the other is the expected losses and unexpected losses. In the CreditRisk+ method, the cause of the default is not to be concerned.
Input data comes from history data. They are the exposure data of the Housing Loan debtor and the data of exposure at default of the Housing Loan debtor and the frequency of default event which is caused by a series of events.
The benefit of using CreditRisk+ method is quite easy to be implemented because it focuses more to the default, so that it needs only few estimation and inputs. For each instrument, we only need exposure at default and counting the probability of default. CreditRisk+ method are suitable for consumer credit due to the high number of accounts and the credit is relatively lower.
The weakness of CreditRisk+ is the assumption that credit risk does not relate to market risk. It excludes migration risk, and the exposure of each debtor is constant and insensitive to the credit quality or the variability of interest rate. In addition, CreditRisk+ method does the measuring to a group of Housing Loan debtors, and that makes it difficult to find out the risk of each debtor.
Based on the simplicity of the CreditRisk+ method, Bank X can take into considerations of using the method to measure the Housing Loan risk in their company.
The use of internal model is smaller than the standardized model in the minimum use of capital, thus it can be an alternative model to measure the risk for Bank X.
Regarding those consumer credit products such as Automotives Loan, Credit Card, and Personal Loan has the similar characteristics with Housing Loan that is high number of Customer with credit value that is relatively small and individual, thus CreditRisk+ method can also be used to measure credit risk for consumer loan other than the Housing Loan itself.
Measurement results show the value of CreditRisk+, the unexpected loss is Rp.204,800,000,000,-. While economic capital that can be closed Unexpected loss amounted to Rp. 64,000,000,000,-
ABSTRAK
Tujuan dari penelitian ini adalah untuk mengetahui metode yang akan digunakan untuk menghitung berapa tinggi resiko KPR dengan menggunakan metode internal model CreditRisk+. Selain itu, Bank X juga dapat mengukur expected loss dan unexpected loss, serta jumlah economic capital yang harus dicadangkan oleh Bank X untuk menutup unexpected loss..
Pandangan umum tentang metode yang akan digunakan adalah sebagai berikut: 1. Pengumpulan data debitur Kredit Perumahan pada periode yang ditentukan 2. Mengatur Band dan Default Eksposur per Band
3. Mengukur recovery rate
4. Mengukur Loss atau Rugi Mengingat Severity Default
5. Mengukur Probabilitas Default dan Probabilitas kumulatif Default 6. Mengukur expected loss dan unexpected loss
7. Mengukur economic capital
CreditRisk+ adalah metode untuk mengukur risiko yang dikembangkan oleh Credit Suisse First Boston (CSFB) pada bulan Desember 1996. Dalam metode ini, ada dua titik fokus yang sedang ditangani. Salah satunya adalah default dan non-standar, dan yang lainnya adalah expected loss dan unexpected loss. Dalam metode CreditRisk+, penyebab default tidak dipertimbangkan.
Data input berasal dari data sejarah. Data adalah data eksposur dari debitur Kredit Perumahan dan data exposure at default dari debitur Kredit Perumahan dan frekuensi kejadian default yang disebabkan oleh rangkaian acara.
Keuntungan menggunakan metode CreditRisk+ cukup mudah untuk dilaksanakan karena lebih fokus ke default, sehingga hanya beberapa estimasi kebutuhan dan masukan. Untuk masing-masing instrumen, kita hanya perlu paparan di default dan menghitung probabilitas default. CreditRisk+ yang cocok untuk kredit konsumen karena tingginya jumlah account dan kredit relatif lebih rendah.
Kelemahan CreditRisk+ adalah asumsi bahwa risiko kredit tidak berhubungan dengan risiko pasar. Ini termasuk resiko migrasi, dan eksposur debitur masing-masing adalah konstan dan tidak sensitif terhadap kualitas kredit atau variabilitas tingkat suku bunga. Selain itu, CreditRisk+ melakukan pengukuran kepada sekelompok debitur KPR, dan yang membuat sulit untuk mengetahui risiko dari setiap debitur. Berdasarkan kesederhanaan metode CreditRisk+, Bank X dapat mengambil menjadi pertimbangan menggunakan metode ini untuk mengukur risiko KPR dalam perusahaan mereka.
Penggunaan internal model lebih kecil dibandingkan dengan model standar dalam penggunaan modal minimal, sehingga dapat menjadi model alternatif untuk mengukur risiko.
Mengenai produk-produk kredit konsumen seperti Otomotif Kredit, Kartu Kredit dan Personal Loan memiliki karakteristik yang mirip dengan KPR yang tingginya angka Pelanggan dengan nilai kredit yang relatif kecil dan individu, sehingga metode CreditRisk+ juga dapat digunakan untuk mengukur kredit risiko kredit konsumen selain Pinjaman Perumahan itu sendiri.
Hasil pengukuran menunjukkan nilai CreditRisk+, kerugian tak terduga adalah Rp. 204,800,000,000 -. Sementara modal ekonomi yang dapat menutup kerugian yang tidak terduga sebesar Rp. 64,000,000,000,- kata kunci: CreditRisk+, exposure at default default, expected loss, unexpected loss, economic capital
FOREWORD
Alhamdulillah, my grace, turning to Allah SWT who gave his bless to me, makes me able to compile the final work, entitled “Analysis of Credit Risk Measurement of Housing Loan Using Internal model Credit Risk+ in Bank X”. This thesis is a research report compiled in order to fulfill one of the requirements to obtain a degree in Management, School of Business and Management, Institut Teknologi Bandung to the field of financial concentration.
In the process of this thesis, of course, there are a lot of help and encouragement from various parties. At this opportunity I would like to thank the infinite to:
1. Mr. Ahmad Herlanto Anggono, as my counselor, for supervising the thesis, always ready to help me, to give guidance and suggestions.
2. Beloved family, especially my mother and father, Tedjo Martojo and Ranila, and also my sister Mirza Devi Maharani, with all his love continue to give the spirit and encourage the writer to be able to finish this research.
3. Hanif and Ikrom, roommates who are always with me in my three years college life. 4. My partners, Dorojatun, Eswan, Esa, Ifad, Yasmin, Ines, for being partners-in-crime in
campus.
5. SBM friends batch 2010, thank you for this wonderful three years.
6. My lads Olga, Afina, Akwilla, Andrettya, Perdana, Syifa, Saha, Andra, Badrun, Manda, Sari, Riza, Dinda, Indah for being supportive all the time.
May Allah reward the many times over.
Bandung, July 23, 2010
LIST OF CONTENTS
ABSTRACT ... i
FOREWORD ... iii
LIST OF CONTENTS ... iv
LIST OF TABLES ... vi
LIST OF APPENDICES ... vii
CHAPTER I INTRODUCTION ... 1
1.1 Background ... 1
1.2 Principal Problem ... 3
1.3 Research Objectives ... 4
1.4 Research Methods ... 5
BAB II THEORETICAL FOUNDATION ... 6
BAB III METHODOLOGY ... 16
3.1 Problem Analysis ... 16
3.1.1 Research Object ... 16
3.1.2 Research Method ... 16
3.2 Improvement Proposal ... 17
3.2.1 Data Collection ... 17
3.2.2 Preparation of the Bands ... 18
3.2.3 Data Processing ... 19
3.2.3.1 Credit exposure at default ... 19
3.2.3.3 Recovery rate ... 19
3.2.3.4 Measurement of Probability of Default ... 19
3.2.3.5 Distribution of Default Events ... 20
3.2.3.6 Default Number ... 20
3.2.3.7 Measurement of Economic Capital ... 21
BAB IV DATA ANALYSIS ... 22
4.1 Overview of Housing Credit in Bank X ... 22
4.2 Housing Loan Credit Risk Measurement with CreditRisk+ Model ... 24
4.2.1 Preparation of Credit Risk Exposure per Band ... 24
4.2.2 Recovery Rates ... 26
4.2.3 Real Loss ... 27
4.2.4 Number of Default ... 28
4.2.5 Cumulative Probability of Default ... 29
4.2.6 Expected Loss and Unexpected Loss ... 30
4.2.7 Measurement of Losses ... 32 4.2.8 Economic Capital ... 33 BAB V CONCLUSION ... 34 5.1 Conclusions ... 34 5.2 Suggestions... 35 REFERENCES ... 36 APPENDIX ... 38
LIST OF TABLES
Table 4.1: Composition of the Housing Loan of Bank X Period of the Year 2009 ... ...23
Table 4.2: Total Credit Exposure at Default of 2009 in Bank X ... 25
Table 4.3: Housing Loan Exposure at Default ... 25
Table 4.4: Composition of Housing Loan Exposure at Default per Band (in Rp.) ... 26
Table 4.5: Recovery Rate of Housing Loan in Bank X ... 27
Table 4.6: Real Loss Value of 2009 ... 28
Table 4.7: Expected Number of Default (λ) of Housing in 2009 period in Bank X ... 29
Table 4.8: Cumulative Probability of Default of 2009 ... 30
Table 4.9: Value of Expected Loss and Unexpected Loss of Housing Loan ... 31
Table 4.10: Measured Losses per Year in 2009 ... 32
LIST OF APPENDICES
Appendix A: Processes of CreditRisk+ ... ...38 Appendix B: Consumer Loan Portfolio of Bank X Period of Year 2009 ... 39
