Credit Information Companies in KoreaLicensed Services Equity Capital Company Established (USD million) Information Credit Debt Service Inquiry Collection
Nice D&B Oct. 12, 2002 7 ● ● NICE Information Service Feb. 28, 1985 27 ● SCI Information Service Apr. 23, 1992 16 ● ● ● e-Credible Aug. 6, 2001 5 ● Korea Credit Bureau (KCB) Feb. 22, 2005 9 ● ● Korea Enterprise Data Feb. 22, 2005 62 (KED) ● ●
Source: Financial Supervisory ServiceFinancial Supervisory Service.
3.3.2. Status
Korea’s corporate credit information management framework has a dual structure consisting of the Public Credit Registry (PCR), managed in compliance with relevant laws and regulations, and private credit information companies (Figure 3-10). The two components cooperate to provide services to financial institutions,
154 • 2016/17 Knowledge Sharing Program with Indonesia including banks and other users of individual and corporate credit information. Private credit information companies can be divided into Credit Bureaus (CBs) which deal with individual credit information (individual CBs), and credit information companies specializing in MSMEs (SME CBs).
Individual CBs collect various forms of financial and non-financial credit information on individuals, including credit card and telecommunication information and utility bills, in addition to financial transaction data provided by the PCR. The CBs then assess the data to generate a credit rating for each individual. The credit ratings and credit information for individuals provided by individual CBs are the primary determinants of whether a loan application at a financial institution will be successful. On the other hand, SME CBs collect the latest corporate information based on loan and guarantee evaluation data provided by commercial banks and credit guarantee institutions. They process the data in order to compile and issue corporate credit ratings and company reports. The growth in the number of individual and SME CBs has made a significant contribution to facilitating the extension of loans by banks and non-banking financial institutions in Korea.
[Figure 3-10] Korea’s Credit Information Infrastructure
Financial Institutions Public Entities (Court, tax agency, (Bank, credit card, etc.) public insurance)
PCR KCIS (Korea Credit Information Service)
Banks, Financial Institutions Guarantee Institutions CB SME CB (F/s and assessment) (NICE, KCB) (KED, NICE) Private companies FSS & Dart (Electricity, telecom, (financial statement) trade information)
Financial Public Private Companies Institutions Organizations
Source: Author’s Own Analysis.
Unlike many other nations where central banks serve as PCRs, this role was taken by the Korea Federation of Banks. However, with a revision of the law in January 2016, Korea Credit Information Services was founded to serve as an independent PCR. This institution integrates and manages the credit information collected from
Chapter 3 _ Improvement of the Credit Program Information System to Support Micro, Small and Medium Enterprises in Indonesia • 155 various financial institutions, including the Credit Finance Association, Life Insurance Association, and General Insurance Association. The credit information managed by the PCR includes general credit information, technology information, and insurance information. General credit information (loan data) is collected to help financial institutions assess borrowers’ credit status. Recently, financial institutions have begun to use technology information in their technology assessments of companies applying for corporate loans. Information is also gathered on insurance contracts and insurance claim payments to prevent insurance fraud.
The Data Analysis, Retrieval and Transfer (DART) system run by the FSS is a comprehensive corporate disclosure system where corporations who have received external audits can submit their disclosure documents, including financial statements, to the Internet, through which users, including investors, can review the submitted information. SME CBs can collect these audit reports, corporate financial statements, and business reports from the DART system, enabling them to evaluate companies accurately and efficiently.
3.3.3. Achievements and Implications
Korea’s credit information infrastructure has served as a strong foundation for the expansion of the SME loan market. As in many other countries, Korea’s commercial banks typically prefer to see evidence of solid collateral when extending loans to individuals and corporate debtors. However, a loan market based on credit ratings rather than collateral has rapidly grown. To discourage collateral-dependent loan practices, it is essential that credit information is actively shared across the entire financial market.
Unlike Indonesia, when an individual or a company receives a bank loan in Korea, the information is shared with other banks in real time or at least updated daily. This rapid and efficient information sharing encourages competition between banks, which allows companies to borrow money under more favorable conditions. In Korea, even micro or small businesses can access bank loans without difficulty if they manage and control their credit well. Because this credit environment is familiar to SMEs, they are extra careful in managing their corporate credit, such as paying their loan interest before it is due and not defaulting on their taxes. In addition, companies make an extra effort to ensure transparent accounting and accurate financial statements, leading to corporate accounting and commercial transaction data having greater reliability in society. In addition, because as much public information and commercial transaction data as possible is shared without violating privacy, financial institutions and credit information companies have actively used this public information and data to develop a credit-based financial market.
156 • 2016/17 Knowledge Sharing Program with Indonesia In Indonesia, the development of credit information companies has been slow, even though the central bank began its efforts in the early 2000s. The government has to recognize the importance of developing the credit information infrastructure in order to expand the individual credit market, encourage the issuance of more MSME loans, and promote transparent commercial trade.
3.4. SME-Integrated Management System
3.4.1. Overview
Departments in the central government, municipal governments, and related organizations offer SME support programs for business startups, technology development, job creation, and investment. In 2014, both direct and indirect funding from the government was given to 1,322 projects totalling KRW 13.65 trillion. However, because there has been a lack of integration in terms of collecting and combining information about the beneficiaries of these support programs, financial distribution has been inefficient, with growing concern about redundant support and skewed support of certain companies. To improve the efficiency of the financial support for MSMEs, an integrated management system was established in three phases from 2013 to 2015. Before it began operation, the basis for establishing and operating the system was outlined in the Prime Minister Order (August 2013) revision of the Framework Act on Small and Medium Enterprises and the enforcement order and enactment of operation notification in October 2014. The Korea Small Business Institute was appointed to run the system.
3.4.2. Status
The integrated management system collects and manages information from government agencies and local governments related to the application and support history of companies (Figure 3-11). It also gathers corporate information from the Ministry of Employment and Labor, the National Tax Service, the Korea Customs Service, the Korean Intellectual Property Office, and private corporate credit information companies. It acts as a portal for SME support, as users can search and review relevant information on the various government assistance programs and SME beneficiaries.
Chapter 3 _ Improvement of the Credit Program Information System to Support Micro, Small and Medium Enterprises in Indonesia • 157 [Figure 3-11] SME Information Management System Framework (Oct. 2014)
Program Information Central Government MSME Information
Support Perfomance (2010~) 14 ministry & 156 programs 1.12 million beneficiaries
• Total 1.95 million case with • SMBA programs & • Basic info.(Tax agency, Credit KRW 185 trillion financing programs of other Bureau) ministries : 104 programs Tax ID, ownership, data of SMBA : 1.30 million cases • Workforce, export : 52 establishment with KRW 90 trillion programs Region, Industry sector, financial FSC : 0.44 million cases with status, etc. KRW 27 trillion
• Additional Information (combining sources of ministries) Revenue, business shutdown (Tax agency) • 1.12 million MSMEs 400 Programs No. of employee (Ministry of Labor) • Application data, support date, Export amount (Customs Service) support amount, etc. Local Government Intellectual Property (Patent Office)
Source: Small and Medium Business Administration.
The system offers real-time information on government-assistance programs; for example, the status of 1,332 SME support programs provided by 25 government departments and 17 local government agencies in 2014. Information is available on a company’s application history and duplication of support can be identified (Figure 3-12). Information is also provided on business performance including differences in performance before and after entering the support program.
[Figure 3-12] SIMS Operational Framework
Central Publicagency Integrated SME info. government Duplication Mgmt Statistics (Tax authority, etc) support check analysis mgmt history Support history Central Local government government support scheme Connected Optimized Information support support analysis Management system of local Local government SMEs government support scheme
Source: Small and Medium Business Administration.
158 • 2016/17 Knowledge Sharing Program with Indonesia 3.4.3. Implications
It is possible that the MSME support policies promoted by various ministries within the Indonesian government will lead to inefficient management and redundant support. In this situation, it is important to record which companies received what type of assistance, thus increasing the objectivity of policy evaluation and improving the efficiency of budget allocation and management. It will also contribute to reducing program redundancy among government departments because adopting an integrated management system will ensure that new projects are not too similar to existing projects.
4. Policy Recommendations 4.1. Improvement of the KUR
4.1.1. Clearly Defining Targets for the KUR Support
It is necessary to establish more specific KUR objectives. Currently, KUR is more similar to a financial inclusion program that supports low-income families rather than one that supports MSMEs. This is especially true for KUR Micro, given that the maximum loan per company is quite low at IDR 25 million. Despite this, setting clear KUR objectives for SME development may cause confusion when determining a policy direction. Thus, it should be made clear that KUR Micro is designed to support the livelihood of those living in poverty in rural areas. In contrast, KUR Retail is more like a SME development program, with its loan ceiling of IDR 500 million. Therefore, it may be necessary to take separate approaches to these two programs, even if it means that the budgeting, program design, and operating entities are separated. The targets of the programs can be differentiated depending on separate policy objectives. Because the objective of KUR Retail is to promote SME growth and economic development, eligibility criteria should be determined based on an SME’s potential for job creation and sustainable growth. On the other hand, eligibility for KUR Micro should reflect the fact that the program focuses on poverty reduction and should thus act as the first source of financing for low-income families, irrespective of what type of business they run.
It is also necessary to determine clear target businesses and industries for KUR support. Currently, priority target industries (agriculture, fishery, and manufacturing) account for only 23% of KUR support loans, while the wholesale and retail industries account for 66%. The government has already acknowledged this discrepancy. Another issue is that many customers with poor credit scores are rejected by the KUR program even though they are priority targets because banks focus more on
Chapter 3 _ Improvement of the Credit Program Information System to Support Micro, Small and Medium Enterprises in Indonesia • 159 customers with high credit ratings for internal risk management purposes. It appears that no clear guidelines have been presented to banks with regards to KUR eligibility in target industries.
To improve the situation, the government first needs to define KUR target businesses based on an analysis of the impact KUR support will have on particular industries and the specify the eligibility requirements in its KUR agreement with banks. In the future, interest subsidies or credit guarantee payments should be restricted for loans extended to companies outside the target industries. If the criteria for eligibility remain unclear, banks will inevitably focus more on companies with better credit histories to avoid risk and improve procedural efficiency.
It is also necessary to consider whether restricting KUR support to the agriculture, fishery, and manufacturing industries is the correct decision. The belief that the support of a small group of target industries is economically more beneficial may not necessarily be true in practice because industries are interconnected as part of a diverse and complex value chain. Beginning in 2017, the CMEA plans to extend KUR to priority industries only. However, banks oppose this plan, arguing that it is not ideal in terms of risk management or cost efficiency. It is natural for banks to extend loans based on credit status following market principles, thus the loan market should be based on market demand and not government intentions. Thus, instead of blocking access to KUR for companies in the wholesale and retail industries, who have been the main beneficiaries of KUR thus far, it would be better to set a loan ceiling for each industry and encourage gradual changes within the KUR loan portfolio.
4.1.2. Improvement in KUR Operations
To reduce MSME loan interest rates, it is more important to develop policies that encourage a gradual decrease in interest rates through market principles and competition than it is to rely on excessive government spending on KUR interest subsidies. As of 2016, IDR 3.6 trillion in interest subsidies were paid to banks by the government. Because the number of loans taken out through KUR will increase in the coming years, the money required for interest subsidies will also rise. The interest subsidy policy is a short-term contingency to accelerate the development of the low-interest loan market. It is worth considering whether KUR customers will still have access to bank loans if the government stops paying interest subsidies. If the use of KUR loans only increases in proportion to the size of government subsidies, it would be necessary to review the validity of the KUR policy itself. If the KUR Retail program is separated from the rest of KUR and redesigned to rely on credit guarantees instead of interest subsidies, government spending will reduce. However, the government may have to become more involved in credit guarantee institutions
160 • 2016/17 Knowledge Sharing Program with Indonesia such as Jamkrindo and regional credit guarantee institutions in order to ensure their efficient operation.
To address this situation, rather than providing a high interest rate subsidy (10%) to a limited number of companies, the size of the subsidy should be reduced but offered to as many companies as possible. At the same time, measures should be explored to further reduce the subsidy rate gradually, such as allowing companies with good repayment histories with KUR to borrow additional money from their bank. Loan conditions can also be improved by encouraging free competition among banks based on the sharing of information about companies using government funding programs, including KUR. To this end, it is necessary to improve the SIKP so that it can serve as an integrated management system for SME support information.
KUR should also be aligned with other financing schemes such as credit guarantees and regulation by the OJK in order to create a synergy between them. In Indonesia, as in other countries, the credit guarantee system is directly and indirectly financed with government money. Thus, rather than treating KUR as a separate policy from the credit guarantee scheme, it is worth combining the two to maximize their effect. Under KUR’s current system, Jamkrindo does not play a significant role because it automatically provides guarantees for loans. While maintaining the current KUR system for microbusinesses, it is worth considering expanding the role of credit guarantee institutions for small and medium businesses that are KUR Retail targets. At the same time, various incentives and penalties from financial authorities like the OJK could increase accessibility to bank loans for MSMEs.
4.1.3. External Assessment of KUR Performance
Given that significant government budgetary support is required for the operation of KUR, it is essential to evaluate KUR’s performance and achievements objectively and thoroughly. Provided that this assessment is favorable, the government can then continue to refine and expand the KUR scheme. Currently, the SIKP has been developed to make basic statistics available for various stakeholders. However, these statistics are not detailed enough to aid in the decision making surrounding KUR improvement. The statistics on regions, participating banks, business types, gender, and educational background that are currently collected and shared through the SIKP are not much help in improving the KUR system.
For a more systematic achievement and performance analysis, external experts, such as professors or researchers in the field, should be invited to analyze KUR’s performance and achievement. For SME support analysis, various statistical approaches are required, such as an extensive comparative analysis of companies receiving KUR and those who are not. SIKP data could be used for this purpose, but
Chapter 3 _ Improvement of the Credit Program Information System to Support Micro, Small and Medium Enterprises in Indonesia • 161 most of its data is too broad for this type of analysis. Therefore, qualitative measures using sampling and surveys are needed. In addition, it would be better to wait for a few years after launching the new KUR scheme before conducting a performance analysis because any effects of KUR support on the performance of beneficiaries will take time to appear.
4.2. Improvement of the SIKP
4.2.1. Credit Information Infrastructure Improvement
The SIKP has constructed a robust IT environment to amass MSME information. Based on network connections with local governments, relevant government departments, guarantee institutions, and financial institutions, key information is being collected, although there are differences in the quality and quantity depending on the information provider. Because the information that is shared is restricted to that relevant to KUR’s operation and management, the SIKP is limited in its capacity to become a full MSME information platform. However, it can become a key part of Indonesia’s credit information infrastructure if its limitations are overcome. The collection of credit information in the short term and the development of an integrated management system for MSME support in the long term are two key initiatives in this respect.
The collection of credit information in one place is a necessary first step towards the development of both an MSME credit rating model and an integrated management system for MSME support. The SIKP must collect as much MSME information as possible that is relevant to KUR and firms’ credit risk. The Ministry of Finance has already been collecting or plans to collect information from a diverse range of sources such as information on prospective KUR applicants from local governments and line ministries, SID (the SLIK after the upgrade) information from the OJK, public information from the government and relevant agencies, and KUR loan information from banks and guarantee institutions (Figure 3-13). Because the current sources of MSME information are not numerous enough for the SIKP to act as an MSME credit information hub and thus contribute to the expansion of the MSME loan market, the scope of SIKP data collection, which currently focuses only on microbusinesses, must be expanded to include larger SMEs and beneficiaries of other government-assistance programs.
If the SIKP successfully gathers a large pool of MSME credit information, then the Ministry of Finance needs to find ways to share this information with financial institutions. This information will be useful for many banks who are looking to expand their MSME loan programs. The development of a market-friendly MSME loan market through the sharing of credit information and free competition
162 • 2016/17 Knowledge Sharing Program with Indonesia between financial institutions is a key objective of the SIKP. Competition in the MSME loan market will gradually decrease the interest margins of financial institutions and expand the MSME loan market. In the long run, the government can reduce its spending on KUR and similar MSME assistance programs by relying more on free market principles.
[Figure 3-13] SIKP as an Integrated Management System for MSME Support
SIKP
KUR ② Government or Public Entity (Similar programs) (For additional support) Integrated Government Line Ministry Assistance Assistance Information
Local Government ① Financial Institution (Banks) Assistance MSME (For commercial loans) (Credit) Information Guarantee Institutions
③ Research Institutes SLIK Public Info. (Measuring policy performance) (OJK) (Tax, ID, etc)
Source: Author’s Own Analysis.
Once a sufficient amount of relevant information has been amassed, the government will need to analyze its SME support programs and plan the development of an integrated management system. In particular, relevant laws must be introduced to act as the basis for system development and operations, and an organization needs to be designated to run the system.
The following tasks are required to collect information from government- assistance programs: ① define criteria for the categorization of SME support projects, ② designate target projects subject to data collection and manage support history, and ③ define the items connected across projects. To ensure systematic criteria for the categorization of SME support projects, a framework based on function and target group must be established, with functions divided into finance, technology, HR, export, domestic consumption, startups, management, taxation, and mutual growth depending on the support project’s objectives. Meanwhile, targets should be grouped into startup ventures, small business owners (microbusinesses), and general SMEs. The projects that are subject to assistance history management are those capable of managing and providing assistance history data.
If the SIKP is transformed into an integrated management system for MSME
Chapter 3 _ Improvement of the Credit Program Information System to Support Micro, Small and Medium Enterprises in Indonesia • 163 support, it can provide information about the credit history of MSMEs that have received financial and non-financial assistance from the government. This information sharing will increase competition between commercial banks over MSME loans and provide better loan conditions, such as low interest rates and longer maturity periods, for MSME customers. In addition, the system will offer MSME support information that can prevent inefficient spending by allowing redundant support to be detected or optimal assistance to be delivered to promising MSMEs. Finally, researchers can also have access to this information, and any relevant research results that arise from this can be used to improve the government assistance programs in the long run.
4.2.2. Development of a Microbusiness Credit Rating Model
Based on the credit history of companies of similar business types or sizes, the variables that are strongly associated with credit risk can be identified. These variables can then be utilized in a correlation analysis to develop a credit rating model that allows the default risk of individual companies to be calculated and their rank listed. This model can ensure an objective and reliable evaluation of corporate credit risk. Given the quantitative and qualitative limitations of the data that KUR and the SIKP currently collect, this approach will be difficult to implement. Thus, a credit scoring system based on Korea’s comprehensive corporate scoring method is recommended (Figure 3-14).
[Figure 3-14] Rating Model for Potential KUR Customers
Local gov’t SIKP Banks SIKP
• Demand and MSME upload • Combine with SLIK, recommend • Refer to the rating upload • Feedback to local profile info. public information and • KUR loan approval or gov’t • Non-financial policy criteria qualitative assessment • Calculate final rating regection • Rating model upgrade
KUR Candidate Rating
Entity Model Category Weight Rating Factors Others
Local 1) Qualitative (1) management capability, (2) industry risk, (3) Non-statistic 30 Gov’t Assessment operational risk, (4) growth potential, (5) collateral judgement
Financial transaction record, delinquency 2) SLIK 30 OJK (Jan 2018~) information
DG Tax, Interior 3) Public Information 20 Tax payment record, sales amount SIKP Ministry, etc.
4) Policy Criteria 20 Priority sector, Number of emlpoyees, etc. MoF, CMEA
Source: Author’s Own Analysis.
164 • 2016/17 Knowledge Sharing Program with Indonesia A credit scoring system quantitatively evaluates the credit status of companies based on various credit-related variables and eligibility criteria. The scoring process includes ① selecting the evaluation variables, ② determining the weights for each variable, ③ calculating the scores for each variable, and ④ producing an overall credit score based on the sum of the variables. This system has the advantage of including both quantitative and qualitative criteria in its calculation, but it is limited in that there is room for subjective judgment in selecting credit variables and determining the weights.
To develop the proposed model shown in [Figure 3-14], changes must be made to the SIKP’s data collection. First, local governments must report the results of their qualitative assessment of MSME candidates, including information such as management capability, industrial risk, operation risk, growth potential, and collateral level. The SIKP must also collect credit information, such as financial transaction data and delinquency data, in cooperation with the OJK through the SLIK system. Public data such as tax payment information and annual revenue from DG Tax and the authentication of ID numbers from the Interior Ministry will also be necessary. Finally, policy-oriented criteria should be weighted to prioritize particular policy targets. Factors such as industry sector, number of employees, and regional location can be used for policy purposes. As an outcome of the credit rating procedure, the SIKP can generate credit ratings for potential KUR customers recommended by local governments. Based on these ratings, the Ministry of Finance can select applicants that can be directed towards a bank for a KUR loan. For the recommended companies, the deadline for bank feedback should set to manage and facilitate the actual loan extension process. Additionally, if a rating model for existing KUR customers is developed, it can be used for the management of credit risk of the portfolio and serve as an early warning.
4.2.3. SIKP Topology Improvement
To protect the SIKP’s internal IT resources from external risk, an information protection system such as a firewall should be put in place. Using a host-to-host connection to external entities should be integrated into the Web service to improve operational efficiency. The existing transaction server that handles program operation and access to the database should be replaced by a dedicated application server and a database server to speed up the process. In addition, the servers should be duplicated to create a double architecture to prevent errors within the system. To manage the excessive workload generated by the duplicate application servers, a load-balancing server should also be adopted. Adoption of a Storage Area Network (SAN) will ensure flexibility, expandability, and convenience in data management. The report and OLAP servers should remain as they are.
Chapter 3 _ Improvement of the Credit Program Information System to Support Micro, Small and Medium Enterprises in Indonesia • 165 [Figure 3-15] SIKP Topology Improvement
Internet WAN Firewall
Application Application Server 1 Server 2 Web Service Server
BANK, Loader Report Local Governments, Server Server Line Ministries, Etc. Database Database Server 1 Server 2
OLAP SAN Server storage
Source: Author’s Own Analysis.
166 • 2016/17 Knowledge Sharing Program with Indonesia References
Anton H Gunawan, Issues and Challenges in the Indonesia Banking Sector, 2017. Bank Mandiri, Result Presentation (FY 2016), 2017. Jamkrindo, The Development of Rating System for Indonesian MSMEs, 2016. KIF, Financial Market Review of Indonesia, 2015. KIF, Framework of SME Financing in Korea, 2015. Kim Ilhwan, Understanding of Credit Evaluation, 2005. KODIT, Improvement of KUR Program and Establishment of Credit Rating System for MSMEs in Indonesia (KSP Report), 2015. KODIT, Improvement of MSME Credit Rating system for Vietnam (KSP Report), 2014. KODIT, International Review of Credit Guarantee Schemes, 2012. Korea Credit Information Services, Credit Reporting System in Korea, 2017 OJK. Lee Inho, Credit Evaluation System of Korea, 2007. The World Bank, Impact of Assessment Framework: SME Finance, 2012.
Chapter 3 _ Improvement of the Credit Program Information System to Support Micro, Small and Medium Enterprises in Indonesia • 167
2016/17 Knowledge Sharing Program with Indonesia
.go.kr www. ksp ity 30149, Korea C
Center for International Development, KDI cid.kdi.re.kr Knowledge Sharing Program www.ksp.go.kr (set) www.kpmg.com/kr www.mosf.go.kr www.kdi.re.kr 5 3 www.kodit.co.kr Floor, Gangnam Finance Center, 152, Teheran-ro, Gangnam-gu, Seoul 06236, Korea Floor, Gangnam Finance Center, 152, Teheran-ro, Gangnam-gu, Seoul 06236, Korea SBN 979-11-5932-249- SBN 979-11-5932-227- I I th Tel. 82-1588-6565 Tel. 82-2-2112-0062 Korea Credit Guarantee Fund (KODIT) Cheomdallo 7 (Sinseo-dong), Dong-gu, Daegu Metropolitan City 41068, Korea Tel. 82-44-550-4114 Samjong KPMG Economic Research Institute Inc. 27 Korea Development Institute 263 Namsejong-ro, Sejong Special Self-Governing Ministry of Strategy and Finance Sejong Special Self-Governing City 30109, Korea Government Complex-Sejong, 477, Galmae-ro, Tel. 82-44-215-7762
